Haris Balta

Senior Researcher

Robotics & Autonomous Systems,
Royal Military Academy

Address

Avenue De La Renaissance 30, 1000 Brussels, Belgium

Contact Information

Call: +32(0)2-44-14102

Email: haris.balta@rma.ac.be

Haris Balta is a Senior Researcher/ Technical Project Lead of the Robotics & Autonomous Systems unit of the department of Mechanics of the Royal Military Academy of Belgium. He received his Ph.D. in Engineering from the Royal Military Academy of Belgium in collaboration with the University Federico II Naples (Italy), a Postgraduate II Level Master’s degree in the field of Robotics and Intelligent Systems from the University Federico II Naples (Italy), completed postgraduate studies in the field of Software engineering at the University of Mostar (Bosnia and Herzegovina), and an Engineering degree in Information Technology from the University of Mostar (Bosnia and Herzegovina), from 2017, 2012 , 2010 and 2008, respectively.

Haris has participated in the leading role in several large-scale European projects, such as ICARUS on search and rescue (SAR) robotics, TIRAMISU on humanitarian demining robotics (both coordinated by the RMA) and MAFF on the deployment of UAVs for mine action. In addition, he is- holding a position as a technical coordinator within a Ministry of Defense project dealing with the development of a powerful toolbox combining UAV data for military operators and decision makers in order to enhance their situational awareness capabilities and reduce their cognitive load during mission critical operations. Together, these projects gather more than 55 partners (government, defense, industry-SME’s and academia) from all over Europe and Japan, with an overall budget of around€40 million.

His activities were related to the development of heterogeneous robotic systems (UAV & UGV) and bringing such systems to real-life crisis management missions (defense, search and rescue, humanitarian demining and remote inspection).He was acting as a certified and internationally operational UAV instructor and pilot, with more than 450 flight hours on different types of fixed-wing and rotary wing UAV systems while operating in 5 countries across Europe. Furthermore, he led several multinational UAV operations in the context of crisis management and was responsible for legal, safe and effective UAV mission execution. Based on this work a dedicated UAV team was formed and integrated into the standard operating procedures of the Federal Department of Civilian Protection (B&H) as one of the first UAV teams in EU Civil Protection Community.

Haris is active as a reviewer for the European Commission and other funding agencies. He has taught several professional, graduate and undergraduate courses and has published more than 25 scientific publications including book chapters and high-impact journal and conference papers. His work has been extensively reported by the international media press.

Publications

2020

  • H. Balta, J. Velagic, H. Beglerovic, G. De Cubber, and B. Siciliano, “3D Registration and Integrated Segmentation Framework for Heterogeneous Unmanned Robotic Systems," Remote Sensing, vol. 12, iss. 10, p. 1608, 2020.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    The paper proposes a novel framework for registering and segmenting 3D point clouds of large-scale natural terrain and complex environments coming from a multisensor heterogeneous robotics system, consisting of unmanned aerial and ground vehicles. This framework involves data acquisition and pre-processing, 3D heterogeneous registration and integrated multi-sensor based segmentation modules. The first module provides robust and accurate homogeneous registrations of 3D environmental models based on sensors’ measurements acquired from the ground (UGV) and aerial (UAV) robots. For 3D UGV registration, we proposed a novel local minima escape ICP (LME-ICP) method, which is based on the well known iterative closest point (ICP) algorithm extending it by the introduction of our local minima estimation and local minima escape mechanisms. It did not require any prior known pose estimation information acquired from sensing systems like odometry, global positioning system (GPS), or inertial measurement units (IMU). The 3D UAV registration has been performed using the Structure from Motion (SfM) approach. In order to improve and speed up the process of outliers removal for large-scale outdoor environments, we introduced the Fast Cluster Statistical Outlier Removal (FCSOR) method. This method was used to filter out the noise and to downsample the input data, which will spare computational and memory resources for further processing steps. Then, we co-registered a point cloud acquired from a laser ranger (UGV) and a point cloud generated from images (UAV) generated by the SfM method. The 3D heterogeneous module consists of a semi-automated 3D scan registration system, developed with the aim to overcome the shortcomings of the existing fully automated 3D registration approaches. This semi-automated registration system is based on the novel Scale Invariant Registration Method (SIRM). The SIRM provides the initial scaling between two heterogenous point clouds and provides an adaptive mechanism for tuning the mean scale, based on the difference between two consecutive estimated point clouds’ alignment error values. Once aligned, the resulting homogeneous ground-aerial point cloud is further processed by a segmentation module. For this purpose, we have proposed a system for integrated multi-sensor based segmentation of 3D point clouds. This system followed a two steps sequence: ground-object segmentation and color-based region-growing segmentation. The experimental validation of the proposed 3D heterogeneous registration and integrated segmentation framework was performed on large-scale datasets representing unstructured outdoor environments, demonstrating the potential and benefits of the proposed semi-automated 3D registration system in real-world environments.

    @Article{balta20203Dregistration,
    author = {Balta, Haris and Velagic, Jasmin and Beglerovic, Halil and De Cubber, Geert and Siciliano, Bruno},
    journal = {Remote Sensing},
    title = {3D Registration and Integrated Segmentation Framework for Heterogeneous Unmanned Robotic Systems},
    year = {2020},
    month = may,
    number = {10},
    pages = {1608},
    volume = {12},
    abstract = {The paper proposes a novel framework for registering and segmenting 3D point clouds of large-scale natural terrain and complex environments coming from a multisensor heterogeneous robotics system, consisting of unmanned aerial and ground vehicles. This framework involves data acquisition and pre-processing, 3D heterogeneous registration and integrated multi-sensor based segmentation modules. The first module provides robust and accurate homogeneous registrations of 3D environmental models based on sensors’ measurements acquired from the ground (UGV) and aerial (UAV) robots. For 3D UGV registration, we proposed a novel local minima escape ICP (LME-ICP) method, which is based on the well known iterative closest point (ICP) algorithm extending it by the introduction of our local minima estimation and local minima escape mechanisms. It did not require any prior known pose estimation information acquired from sensing systems like odometry, global positioning system (GPS), or inertial measurement units (IMU). The 3D UAV registration has been performed using the Structure from Motion (SfM) approach. In order to improve and speed up the process of outliers removal for large-scale outdoor environments, we introduced the Fast Cluster Statistical Outlier Removal (FCSOR) method. This method was used to filter out the noise and to downsample the input data, which will spare computational and memory resources for further processing steps. Then, we co-registered a point cloud acquired from a laser ranger (UGV) and a point cloud generated from images (UAV) generated by the SfM method. The 3D heterogeneous module consists of a semi-automated 3D scan registration system, developed with the aim to overcome the shortcomings of the existing fully automated 3D registration approaches. This semi-automated registration system is based on the novel Scale Invariant Registration Method (SIRM). The SIRM provides the initial scaling between two heterogenous point clouds and provides an adaptive mechanism for tuning the mean scale, based on the difference between two consecutive estimated point clouds’ alignment error values. Once aligned, the resulting homogeneous ground-aerial point cloud is further processed by a segmentation module. For this purpose, we have proposed a system for integrated multi-sensor based segmentation of 3D point clouds. This system followed a two steps sequence: ground-object segmentation and color-based region-growing segmentation. The experimental validation of the proposed 3D heterogeneous registration and integrated segmentation framework was performed on large-scale datasets representing unstructured outdoor environments, demonstrating the potential and benefits of the proposed semi-automated 3D registration system in real-world environments.},
    doi = {10.3390/rs12101608},
    project = {NRTP,ICARUS,TIRAMISU,MarSur},
    publisher = {MDPI},
    url = {https://www.mdpi.com/2072-4292/12/10/1608/pdf},
    unit= {meca-ras}
    }

2019

  • H. Balta, J. Velagic, G. De Cubber, and B. Siciliano, “Semi-Automated 3D Registration for Heterogeneous Unmanned Robots Based on Scale Invariant Method," in 2019 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), Wurzburg, Germany, 2019.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This paper addresses the problem of 3D registration of outdoor environments combining heterogeneous datasets acquired from unmanned aerial (UAV) and ground (UGV) vehicles. In order to solve this problem, we introduced a novel Scale Invariant Registration Method (SIRM) for semi-automated registration of 3D point clouds. The method is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, the SIRM does not require having a good initial overlap between two heterogeneous datasets. Our method strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous datasets and harsh outdoor environments) and fully manual registration approaches (which are labour-intensive). The experimental validation of the proposed 3D heterogeneous registration system was performed on large-scale datasets representing unstructured and harsh outdoor environments, demonstrating the potential and benefits of the proposed 3D registration system in real-world environments.

    @InProceedings{balta2019semi,
    author = {Balta, Haris and Velagic, Jasmin and De Cubber, Geert and Siciliano, Bruno},
    booktitle = {2019 {IEEE} International Symposium on Safety, Security, and Rescue Robotics ({SSRR})},
    title = {Semi-Automated {3D} Registration for Heterogeneous Unmanned Robots Based on Scale Invariant Method},
    year = {2019},
    month = sep,
    publisher = {{IEEE}},
    volume = {1},
    address = {Wurzburg, Germany},
    abstract = {This paper addresses the problem of 3D registration of outdoor environments combining heterogeneous datasets acquired from unmanned aerial (UAV) and ground (UGV) vehicles. In order to solve this problem, we introduced a novel Scale Invariant Registration Method (SIRM) for semi-automated registration of 3D point clouds. The method is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, the SIRM does not require having a good initial overlap between two heterogeneous datasets. Our method strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous datasets and harsh outdoor environments) and fully manual registration approaches (which are labour-intensive). The experimental validation of the proposed 3D heterogeneous registration system was performed on large-scale datasets representing unstructured and harsh outdoor environments, demonstrating the potential and benefits of the proposed 3D registration system in real-world environments.},
    doi = {10.1109/ssrr.2019.8848951},
    project = {NRTP},
    url = {https://ieeexplore.ieee.org/document/8848951},
    unit= {meca-ras}
    }

  • N. Nauwynck, H. Balta, G. De Cubber, and H. Sahli, “A proof of concept of the in-flight launch of unmanned aerial vehicles in a search and rescue scenario," ACTA IMEKO, vol. 8, iss. 4, p. 13–19, 2019.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This article considers the development of a system to enable the in-flight-launch of one aerial system by another. The article discusses how an optimal release mechanism was developed taking into account the aerodynamics of one specific mothership and child Unmanned Aerial Vehicle (UAV). Furthermore, it discusses the PID-based control concept that was introduced in order to autonomously stabilise the child UAV after being released from the mothership UAV. Finally, the article demonstrates how the concept of a mothership and child UAV combination could be taken advantage of in the context of a search and rescue operation.

    @Article{nauwynck2019proof,
    author = {Nauwynck, Niels and Balta, Haris and De Cubber, Geert and Sahli, Hichem},
    journal = {{ACTA} {IMEKO}},
    title = {A proof of concept of the in-flight launch of unmanned aerial vehicles in a search and rescue scenario},
    year = {2019},
    month = dec,
    number = {4},
    pages = {13--19},
    volume = {8},
    abstract = {This article considers the development of a system to enable the in-flight-launch of one aerial system by another. The article discusses how an optimal release mechanism was developed taking into account the aerodynamics of one specific mothership and child Unmanned Aerial Vehicle (UAV). Furthermore, it discusses the PID-based control concept that was introduced in order to autonomously stabilise the child UAV after being released from the mothership UAV. Finally, the article demonstrates how the concept of a mothership and child UAV combination could be taken advantage of in the context of a search and rescue operation.},
    doi = {10.21014/acta_imeko.v8i4.681},
    publisher = {{IMEKO} International Measurement Confederation},
    project = {ICARUS, NRTP},
    url = {https://acta.imeko.org/index.php/acta-imeko/article/view/IMEKO-ACTA-08 (2019)-04-04},
    unit= {meca-ras}
    }

2018

  • Y. Baudoin, D. Doroftei, G. de Cubber, J. Habumuremyi, H. Balta, and I. Doroftei, “Unmanned Ground and Aerial Robots Supporting Mine Action Activities," Journal of Physics: Conference Series, vol. 1065, iss. 17, p. 172009, 2018.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    During the Humanitarian‐demining actions, teleoperation of sensors or multi‐sensor heads can enhance‐detection process by allowing more precise scanning, which is use‐ ful for the optimization of the signal processing algorithms. This chapter summarizes the technologies and experiences developed during 16 years through national and/or European‐funded projects, illustrated by some contributions of our own laboratory, located at the Royal Military Academy of Brussels, focusing on the detection of unexploded devices and the implementation of mobile robotics systems on minefields

    @Article{baudoin2018unmanned,
    author = {Baudoin, Yvan and Doroftei, Daniela and de Cubber, Geert and Habumuremyi, Jean-Claude and Balta, Haris and Doroftei, Ioan},
    title = {Unmanned Ground and Aerial Robots Supporting Mine Action Activities},
    year = {2018},
    month = aug,
    number = {17},
    organization = {IOP Publishing},
    pages = {172009},
    publisher = {{IOP} Publishing},
    volume = {1065},
    abstract = {During the Humanitarian‐demining actions, teleoperation of sensors or multi‐sensor heads can enhance‐detection process by allowing more precise scanning, which is use‐ ful for the optimization of the signal processing algorithms. This chapter summarizes the technologies and experiences developed during 16 years through national and/or European‐funded projects, illustrated by some contributions of our own laboratory, located at the Royal Military Academy of Brussels, focusing on the detection of unexploded devices and the implementation of mobile robotics systems on minefields},
    doi = {10.1088/1742-6596/1065/17/172009},
    journal = {Journal of Physics: Conference Series},
    project = {TIRAMISU},
    url = {https://iopscience.iop.org/article/10.1088/1742-6596/1065/17/172009/pdf},
    unit= {meca-ras}
    }

  • N. Nauwynck, H. Balta, G. De Cubber, and H. Sahli, “In-flight launch of unmanned aerial vehicles," in International Symposium on Measurement and Control in Robotics ISMCR2018, Mons, Belgium, 2018.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This paper considers the development of a system to enable the in-flight-launch of one aerial system by another. The paper will discuss how an optimal release mechanism was developed, taking into account the aerodynamics of one specific mother and child UAV. Furthermore, it will discuss the PID-based control concept that was introduced in order to autonomously stabilize the child UAV after being released from the mothership UAV. Finally, the paper will show how the concept of a mothership UAV + child UAV combination could be usefully taken into advantage in the context of a search and rescue operation.

    @InProceedings{nauwynck2018flight,
    author = {Nauwynck, Niels and Balta, Haris and De Cubber, Geert and Sahli, Hichem},
    booktitle = {International Symposium on Measurement and Control in Robotics ISMCR2018},
    title = {In-flight launch of unmanned aerial vehicles},
    year = {2018},
    volume = {1},
    abstract = {This paper considers the development of a system to enable the in-flight-launch of one aerial system by another. The paper will discuss how an optimal release mechanism was developed, taking into account the aerodynamics of one specific mother and child UAV. Furthermore, it will discuss the PID-based control concept that was introduced in order to autonomously stabilize the child UAV after being released from the mothership UAV. Finally, the paper will show how the concept of a mothership UAV + child UAV combination could be usefully taken into advantage in the context of a search and rescue operation.},
    doi = {10.5281/zenodo.1462605},
    file = {:nauwynck2018flight - In Flight Launch of Unmanned Aerial Vehicles.PDF:PDF},
    keywords = {Unmanned Aerial Vehicles, Control, Autonomous stabilization, Search and Rescue drones, Heterogeneous systems},
    project = {NRTP},
    address = {Mons, Belgium},
    url = {http://mecatron.rma.ac.be/pub/2018/Paper_Niels.pdf},
    unit= {meca-ras}
    }

  • H. Balta, J. Velagic, G. De Cubber, W. Bosschaerts, and B. Siciliano, “Fast Statistical Outlier Removal Based Method for Large 3D Point Clouds of Outdoor Environments," in 12th IFAC SYMPOSIUM ON ROBOT CONTROL – SYROCO 2018, Budapest, Hungary, 2018, p. 348–353.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This paper proposes a very effective method for data handling and preparation of the input 3D scans acquired from laser scanner mounted on the Unmanned Ground Vehicle (UGV). The main objectives are to improve and speed up the process of outliers removal for large-scale outdoor environments. This process is necessary in order to filter out the noise and to downsample the input data which will spare computational and memory resources for further processing steps, such as 3D mapping of rough terrain and unstructured environments. It includes the Voxel-subsampling and Fast Cluster Statistical Outlier Removal (FCSOR) subprocesses. The introduced FCSOR represents an extension on the Statistical Outliers Removal (SOR) method which is effective for both homogeneous and heterogeneous point clouds. This method is evaluated on real data obtained in outdoor environment.

    @InProceedings{balta2018fast01,
    author = {Balta, Haris and Velagic, Jasmin and De Cubber, Geert and Bosschaerts, Walter and Siciliano, Bruno},
    booktitle = {12th IFAC SYMPOSIUM ON ROBOT CONTROL - SYROCO 2018},
    title = {Fast Statistical Outlier Removal Based Method for Large {3D} Point Clouds of Outdoor Environments},
    year = {2018},
    number = {22},
    pages = {348--353},
    publisher = {Elsevier {BV}},
    volume = {51},
    abstract = {This paper proposes a very effective method for data handling and preparation of the input 3D scans acquired from laser scanner mounted on the Unmanned Ground Vehicle (UGV). The main objectives are to improve and speed up the process of outliers removal for large-scale outdoor environments. This process is necessary in order to filter out the noise and to downsample the input data which will spare computational and memory resources for further processing steps, such as 3D mapping of rough terrain and unstructured environments. It includes the Voxel-subsampling and Fast Cluster Statistical Outlier Removal (FCSOR) subprocesses. The introduced FCSOR represents an extension on the Statistical Outliers Removal (SOR) method which is effective for both homogeneous and heterogeneous point clouds. This method is evaluated on real data obtained in outdoor environment.},
    doi = {10.1016/j.ifacol.2018.11.566},
    file = {:balta2018fast - Fast Statistical Outlier Removal Based Method for Large 3D Point Clouds of Outdoor Environments.PDF:PDF},
    journal = {{IFAC}-{PapersOnLine}},
    project = {NRTP},
    address = {Budapest, Hungary},
    url = {https://www.sciencedirect.com/science/article/pii/S2405896318332725},
    unit= {meca-ras}
    }

  • H. Balta, J. Velagic, G. De Cubber, W. Bosschaerts, and B. Siciliano, “Fast Iterative 3D Mapping for Large-Scale Outdoor Environments with Local Minima Escape Mechanism," in 12th IFAC SYMPOSIUM ON ROBOT CONTROL – SYROCO 2018, Budapest, Hungary, 2018, p. 298–305.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This paper introduces a novel iterative 3D mapping framework for large scale natural terrain and complex environments. The framework is based on an Iterative-Closest-Point (ICP) algorithm and an iterative error minimization mechanism, allowing robust 3D map registration. This was accomplished by performing pairwise scan registrations without any prior known pose estimation information and taking into account the measurement uncertainties due to the 6D coordinates (translation and rotation) deviations in the acquired scans. Since the ICP algorithm does not guarantee to escape from local minima during the mapping, new algorithms for the local minima estimation and local minima escape process were proposed. The proposed framework is validated using large scale field test data sets. The experimental results were compared with those of standard, generalized and non-linear ICP registration methods and the performance evaluation is presented, showing improved performance of the proposed 3D mapping framework.

    @InProceedings{balta2018fast02,
    author = {Balta, Haris and Velagic, Jasmin and De Cubber, Geert and Bosschaerts, Walter and Siciliano, Bruno},
    booktitle = {12th IFAC SYMPOSIUM ON ROBOT CONTROL - SYROCO 2018},
    title = {Fast Iterative {3D} Mapping for Large-Scale Outdoor Environments with Local Minima Escape Mechanism},
    year = {2018},
    number = {22},
    pages = {298--305},
    publisher = {Elsevier {BV}},
    volume = {51},
    abstract = {This paper introduces a novel iterative 3D mapping framework for large scale natural terrain and complex environments. The framework is based on an Iterative-Closest-Point (ICP) algorithm and an iterative error minimization mechanism, allowing robust 3D map registration. This was accomplished by performing pairwise scan registrations without any prior known pose estimation information and taking into account the measurement uncertainties due to the 6D coordinates (translation and rotation) deviations in the acquired scans. Since the ICP algorithm does not guarantee to escape from local minima during the mapping, new algorithms for the local minima estimation and local minima escape process were proposed. The proposed framework is validated using large scale field test data sets. The experimental results were compared with those of standard, generalized and non-linear ICP registration methods and the performance evaluation is presented, showing improved performance of the proposed 3D mapping framework.},
    doi = {10.1016/j.ifacol.2018.11.558},
    journal = {{IFAC}-{PapersOnLine}},
    address = {Budapest, Hungary},
    project = {NRTP},
    url = {https://www.sciencedirect.com/science/article/pii/S2405896318332646},
    unit= {meca-ras}
    }

2017

  • D. S. López, G. Moreno, J. Cordero, J. Sanchez, S. Govindaraj, M. M. Marques, V. Lobo, S. Fioravanti, A. Grati, K. Rudin, M. Tosa, A. Matos, A. Dias, A. Martins, J. Bedkowski, H. Balta, and G. De Cubber, “Interoperability in a Heterogeneous Team of Search and Rescue Robots," in Search and Rescue Robotics – From Theory to Practice, G. De Cubber and D. Doroftei, Eds., InTech, 2017.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    Search and rescue missions are complex operations. A disaster scenario is generally unstructured, time‐varying and unpredictable. This poses several challenges for the successful deployment of unmanned technology. The variety of operational scenarios and tasks lead to the need for multiple robots of different types, domains and sizes. A priori planning of the optimal set of assets to be deployed and the definition of their mission objectives are generally not feasible as information only becomes available during mission. The ICARUS project responds to this challenge by developing a heterogeneous team composed by different and complementary robots, dynamically cooperating as an interoperable team. This chapter describes our approach to multi‐robot interoperability, understood as the ability of multiple robots to operate together, in synergy, enabling multiple teams to share data, intelligence and resources, which is the ultimate objective of ICARUS project. It also includes the analysis of the relevant standardization initiatives in multi‐robot multi‐domain systems, our implementation of an interoperability framework and several examples of multi‐robot cooperation of the ICARUS robots in realistic search and rescue missions.

    @InBook{lopez2017interoperability,
    author = {Daniel Serrano L{\'{o}}pez and German Moreno and Jose Cordero and Jose Sanchez and Shashank Govindaraj and Mario Monteiro Marques and Victor Lobo and Stefano Fioravanti and Alberto Grati and Konrad Rudin and Massimo Tosa and Anibal Matos and Andre Dias and Alfredo Martins and Janusz Bedkowski and Haris Balta and De Cubber, Geert},
    editor = {De Cubber, Geert and Doroftei, Daniela},
    chapter = {Chapter 6},
    publisher = {{InTech}},
    title = {Interoperability in a Heterogeneous Team of Search and Rescue Robots},
    year = {2017},
    month = aug,
    abstract = {Search and rescue missions are complex operations. A disaster scenario is generally unstructured, time‐varying and unpredictable. This poses several challenges for the successful deployment of unmanned technology. The variety of operational scenarios and tasks lead to the need for multiple robots of different types, domains and sizes. A priori planning of the optimal set of assets to be deployed and the definition of their mission objectives are generally not feasible as information only becomes available during mission. The ICARUS project responds to this challenge by developing a heterogeneous team composed by different and complementary robots, dynamically cooperating as an interoperable team. This chapter describes our approach to multi‐robot interoperability, understood as the ability of multiple robots to operate together, in synergy, enabling multiple teams to share data, intelligence and resources, which is the ultimate objective of ICARUS project. It also includes the analysis of the relevant standardization initiatives in multi‐robot multi‐domain systems, our implementation of an interoperability framework and several examples of multi‐robot cooperation of the ICARUS robots in realistic search and rescue missions.},
    booktitle = {Search and Rescue Robotics - From Theory to Practice},
    doi = {10.5772/intechopen.69493},
    project = {ICARUS},
    unit= {meca-ras},
    url = {https://www.intechopen.com/books/search-and-rescue-robotics-from-theory-to-practice/interoperability-in-a-heterogeneous-team-of-search-and-rescue-robots},
    }

  • G. De Cubber, D. Doroftei, H. Balta, A. Matos, E. Silva, D. Serrano, S. Govindaraj, R. Roda, V. Lobo, M. Marques, and R. Wagemans, “Operational Validation of Search and Rescue Robots," in Search and Rescue Robotics – From Theory to Practice, G. De Cubber and D. Doroftei, Eds., InTech, 2017.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This chapter describes how the different ICARUS unmanned search and rescue tools have been evaluated and validated using operational benchmarking techniques. Two large‐scale simulated disaster scenarios were organized: a simulated shipwreck and an earthquake response scenario. Next to these simulated response scenarios, where ICARUS tools were deployed in tight interaction with real end users, ICARUS tools also participated to a real relief, embedded in a team of end users for a flood response mission. These validation trials allow us to conclude that the ICARUS tools fulfil the user requirements and goals set up at the beginning of the project.

    @InBook{de2017operational,
    author = {De Cubber, Geert and Daniela Doroftei and Haris Balta and Anibal Matos and Eduardo Silva and Daniel Serrano and Shashank Govindaraj and Rui Roda and Victor Lobo and M{\'{a}}rio Marques and Rene Wagemans},
    editor = {De Cubber, Geert and Doroftei, Daniela},
    chapter = {Chapter 10},
    publisher = {{InTech}},
    title = {Operational Validation of Search and Rescue Robots},
    year = {2017},
    month = aug,
    abstract = {This chapter describes how the different ICARUS unmanned search and rescue tools have been evaluated and validated using operational benchmarking techniques. Two large‐scale simulated disaster scenarios were organized: a simulated shipwreck and an earthquake response scenario. Next to these simulated response scenarios, where ICARUS tools were deployed in tight interaction with real end users, ICARUS tools also participated to a real relief, embedded in a team of end users for a flood response mission. These validation trials allow us to conclude that the ICARUS tools fulfil the user requirements and goals set up at the beginning of the project.},
    booktitle = {Search and Rescue Robotics - From Theory to Practice},
    doi = {10.5772/intechopen.69497},
    journal = {Search and Rescue Robotics: From Theory to Practice},
    project = {ICARUS},
    url = {https://www.intechopen.com/books/search-and-rescue-robotics-from-theory-to-practice/operational-validation-of-search-and-rescue-robots},
    unit= {meca-ras}
    }

  • K. Berns, A. Nezhadfard, M. Tosa, H. Balta, and G. De Cubber, “Unmanned Ground Robots for Rescue Tasks," in Search and Rescue Robotics – From Theory to Practice, G. De Cubber and D. Doroftei, Eds., InTech, 2017.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This chapter describes two unmanned ground vehicles that can help search and rescue teams in their difficult, but life-saving tasks. These robotic assets have been developed within the framework of the European project ICARUS. The large unmanned ground vehicle is intended to be a mobile base station. It is equipped with a powerful manipulator arm and can be used for debris removal, shoring operations, and remote structural operations (cutting, welding, hammering, etc.) on very rough terrain. The smaller unmanned ground vehicle is also equipped with an array of sensors, enabling it to search for victims inside semi-destroyed buildings. Working together with each other and the human search and rescue workers, these robotic assets form a powerful team, increasing the effectiveness of search and rescue operations, as proven by operational validation tests in collaboration with end users.

    @InBook{berns2017unmanned,
    author = {Karsten Berns and Atabak Nezhadfard and Massimo Tosa and Haris Balta and De Cubber, Geert},
    editor = {De Cubber, Geert and Doroftei, Daniela},
    chapter = {Chapter 4},
    publisher = {{InTech}},
    title = {Unmanned Ground Robots for Rescue Tasks},
    year = {2017},
    month = aug,
    abstract = {This chapter describes two unmanned ground vehicles that can help search and rescue teams in their difficult, but life-saving tasks. These robotic assets have been developed within the framework of the European project ICARUS. The large unmanned ground vehicle is intended to be a mobile base station. It is equipped with a powerful manipulator arm and can be used for debris removal, shoring operations, and remote structural operations (cutting, welding, hammering, etc.) on very rough terrain. The smaller unmanned ground vehicle is also equipped with an array of sensors, enabling it to search for victims inside semi-destroyed buildings. Working together with each other and the human search and rescue workers, these robotic assets form a powerful team, increasing the effectiveness of search and rescue operations, as proven by operational validation tests in collaboration with end users.},
    booktitle = {Search and Rescue Robotics - From Theory to Practice},
    doi = {10.5772/intechopen.69491},
    project = {ICARUS},
    url = {https://www.intechopen.com/books/search-and-rescue-robotics-from-theory-to-practice/unmanned-ground-robots-for-rescue-tasks},
    unit= {meca-ras}
    }

  • G. D. Cubber, D. Doroftei, K. Rudin, K. Berns, A. Matos, D. Serrano, J. M. Sanchez, S. Govindaraj, J. Bedkowski, R. Roda, E. Silva, S. Ourevitch, R. Wagemans, V. Lobo, G. Cardoso, K. Chintamani, J. Gancet, P. Stupler, A. Nezhadfard, M. Tosa, H. Balta, J. Almeida, A. Martins, H. Ferreira, B. Ferreira, J. Alves, A. Dias, S. Fioravanti, D. Bertin, G. Moreno, J. Cordero, M. M. Marques, A. Grati, H. M. Chaudhary, B. Sheers, Y. Riobo, P. Letier, M. N. Jimenez, M. A. Esbri, P. Musialik, I. Badiola, R. Goncalves, A. Coelho, T. Pfister, K. Majek, M. Pelka, A. Maslowski, and R. Baptista, Search and Rescue Robotics – From Theory to Practice, G. De Cubber and D. Doroftei, Eds., InTech, 2017.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    In the event of large crises (earthquakes, typhoons, floods, …), a primordial task of the fire and rescue services is the search for human survivors on the incident site. This is a complex and dangerous task, which – too often – leads to loss of lives among the human crisis managers themselves. This book explains how unmanned search can be added to the toolkit of the search and rescue workers, offering a valuable tool to save human lives and to speed up the search and rescue process. The introduction of robotic tools in the world of search and rescue is not straightforward, due to the fact that the search and rescue context is extremely technology-unfriendly, meaning that very robust solutions, which can be deployed extremely quickly, are required. Multiple research projects across the world are tackling this problem and in this book, a special focus is placed on showcasing the results of the European Union ICARUS project on this subject. The ICARUS project proposes to equip first responders with a comprehensive and integrated set of unmanned search and rescue tools, to increase the situational awareness of human crisis managers, so that more work can be done in a shorter amount of time. The ICARUS tools consist of assistive unmanned air, ground, and sea vehicles, equipped with victim-detection sensors. The unmanned vehicles collaborate as a coordinated team, communicating via ad hoc cognitive radio networking. To ensure optimal human-robot collaboration, these tools are seamlessly integrated into the command and control equipment of the human crisis managers and a set of training and support tools is provided to them in order to learn to use the ICARUS system.

    @Book{de2017search,
    author = {Geert De Cubber and Daniela Doroftei and Konrad Rudin and Karsten Berns and Anibal Matos and Daniel Serrano and Jose Manuel Sanchez and Shashank Govindaraj and Janusz Bedkowski and Rui Roda and Eduardo Silva and Stephane Ourevitch and Rene Wagemans and Victor Lobo and Guerreiro Cardoso and Keshav Chintamani and Jeremi Gancet and Pascal Stupler and Atabak Nezhadfard and Massimo Tosa and Haris Balta and Jose Almeida and Alfredo Martins and Hugo Ferreira and Bruno Ferreira and Jose Alves and Andre Dias and Stefano Fioravanti and Daniele Bertin and German Moreno and Jose Cordero and Mario Monteiro Marques and Alberto Grati and Hafeez M. Chaudhary and Bart Sheers and Yudani Riobo and Pierre Letier and Mario Nunez Jimenez and Miguel Angel Esbri and Pawel Musialik and Irune Badiola and Ricardo Goncalves and Antonio Coelho and Thomas Pfister and Karol Majek and Michal Pelka and Andrzej Maslowski and Ricardo Baptista},
    editor = {De Cubber, Geert and Doroftei, Daniela},
    publisher = {{InTech}},
    title = {Search and Rescue Robotics - From Theory to Practice},
    year = {2017},
    month = aug,
    abstract = {In the event of large crises (earthquakes, typhoons, floods, ...), a primordial task of the fire and rescue services is the search for human survivors on the incident site. This is a complex and dangerous task, which - too often - leads to loss of lives among the human crisis managers themselves. This book explains how unmanned search can be added to the toolkit of the search and rescue workers, offering a valuable tool to save human lives and to speed up the search and rescue process. The introduction of robotic tools in the world of search and rescue is not straightforward, due to the fact that the search and rescue context is extremely technology-unfriendly, meaning that very robust solutions, which can be deployed extremely quickly, are required. Multiple research projects across the world are tackling this problem and in this book, a special focus is placed on showcasing the results of the European Union ICARUS project on this subject. The ICARUS project proposes to equip first responders with a comprehensive and integrated set of unmanned search and rescue tools, to increase the situational awareness of human crisis managers, so that more work can be done in a shorter amount of time. The ICARUS tools consist of assistive unmanned air, ground, and sea vehicles, equipped with victim-detection sensors. The unmanned vehicles collaborate as a coordinated team, communicating via ad hoc cognitive radio networking. To ensure optimal human-robot collaboration, these tools are seamlessly integrated into the command and control equipment of the human crisis managers and a set of training and support tools is provided to them in order to learn to use the ICARUS system.},
    doi = {10.5772/intechopen.68449},
    project = {ICARUS},
    url = {https://www.intechopen.com/books/search-and-rescue-robotics-from-theory-to-practice},
    unit= {meca-ras}
    }

  • Y. Baudoin, D. Doroftei, G. De Cubber, J. Habumuremyi, H. Balta, and I. Doroftei, “Unmanned Ground and Aerial Robots Supporting Mine Action Activities," in Mine Action – The Research Experience of the Royal Military Academy of Belgium, C. Beumier, D. Closson, V. Lacroix, N. Milisavljevic, and Y. Yvinec, Eds., InTech, 2017, vol. 1.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    During the Humanitarian‐demining actions, teleoperation of sensors or multi‐sensor heads can enhance-detection process by allowing more precise scanning, which is useful for the optimization of the signal processing algorithms. This chapter summarizes the technologies and experiences developed during 16 years through national and/or European‐funded projects, illustrated by some contributions of our own laboratory, located at the Royal Military Academy of Brussels, focusing on the detection of unexploded devices and the implementation of mobile robotics systems on minefields.

    @InBook{baudoin2017unmanned,
    author = {Baudoin, Yvan and Doroftei, Daniela and De Cubber, Geert and Habumuremyi, Jean-Claude and Balta, Haris and Doroftei, Ioan},
    editor = {Beumier, Charles and Closson, Damien and Lacroix, Vincianne and Milisavljevic, Nada and Yvinec, Yann},
    chapter = {Chapter 9},
    publisher = {{InTech}},
    title = {Unmanned Ground and Aerial Robots Supporting Mine Action Activities},
    year = {2017},
    month = aug,
    volume = {1},
    abstract = {During the Humanitarian‐demining actions, teleoperation of sensors or multi‐sensor heads can enhance-detection process by allowing more precise scanning, which is useful for the optimization of the signal processing algorithms. This chapter summarizes the technologies and experiences developed during 16 years through national and/or European‐funded projects, illustrated by some contributions of our own laboratory, located at the Royal Military Academy of Brussels, focusing on the detection of unexploded devices and the implementation of mobile robotics systems on minefields.},
    booktitle = {Mine Action - The Research Experience of the Royal Military Academy of Belgium},
    doi = {10.5772/65783},
    project = {TIRAMISU},
    url = {https://www.intechopen.com/books/mine-action-the-research-experience-of-the-royal-military-academy-of-belgium/unmanned-ground-and-aerial-robots-supporting-mine-action-activities},
    unit= {meca-ras}
    }

  • D. Lapandic, J. Velagic, and H. Balta, “Framework for automated reconstruction of 3D model from multiple 2D aerial images," in 2017 International Symposium ELMAR, Zadar, Croatia, 2017, pp. 173-176.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    The paper considers a problem of 3D environment model reconstruction from a set of 2D images acquired by the Unmanned Aerial Vehicle (UAV) in near real-time. The designed framework combines the FAST (Features from Accelerated Segment Test) algorithm and optical flow approach for detection of interest image points and adjacent images reconstruction. The robust estimation of camera locations is performed using the image points tracking. The coordinates of 3D points and the projection matrix are computed simultaneously using Structure-from-Motion (SfM) algorithm, from which the 3D model of environment is generated. The designed framework is tested using real image data and video sequences captured with camera mounted on the UAV. The effectiveness and quality of the proposed framework are verified through analyses of accuracy of the 3D model reconstruction and its time execution.

    @INPROCEEDINGS{8124461,
    author={D. {Lapandic} and J. {Velagic} and H. {Balta}},
    booktitle={2017 International Symposium ELMAR},
    title={Framework for automated reconstruction of 3D model from multiple 2D aerial images},
    year={2017},
    volume={},
    number={},
    pages={173-176},
    abstract={The paper considers a problem of 3D environment model reconstruction from a set of 2D images acquired by the Unmanned Aerial Vehicle (UAV) in near real-time. The designed framework combines the FAST (Features from Accelerated Segment Test) algorithm and optical flow approach for detection of interest image points and adjacent images reconstruction. The robust estimation of camera locations is performed using the image points tracking. The coordinates of 3D points and the projection matrix are computed simultaneously using Structure-from-Motion (SfM) algorithm, from which the 3D model of environment is generated. The designed framework is tested using real image data and video sequences captured with camera mounted on the UAV. The effectiveness and quality of the proposed framework are verified through analyses of accuracy of the 3D model reconstruction and its time execution.},
    keywords={autonomous aerial vehicles;cameras;feature extraction;image reconstruction;image segmentation;image sensors;image sequences;remotely operated vehicles;video signal processing;automated reconstruction;multiple 2D aerial images;3D environment model reconstruction;UAV;optical flow approach;interest image points;robust estimation;camera locations;image data;3D model reconstruction;unmanned aerial vehicle;adjacent image reconstruction;structure-from-motion algorithm;features from accelerated segment test;Three-dimensional displays;Solid modeling;Image reconstruction;Two dimensional displays;Cameras;Feature extraction;Optical imaging;3D Model reconstruction;Aerial images;Structure from motion;Unmanned aerial vehicle},
    doi={10.23919/ELMAR.2017.8124461},
    ISSN={},
    project={NRTP,ICARUS},
    address = {Zadar, Croatia},
    publisher={IEEE},
    url={https://ieeexplore.ieee.org/document/8124461},
    month={Sep.},
    unit= {meca-ras}
    }

  • H. Balta, “Spatial registration of 3D data from aerial and ground-based unmanned robotic systems," PhD Thesis, 2017.
    [BibTeX] [Abstract]

    Robotic systems are more and more leaving the protected laboratory environment and entering our daily lives. These robotic entities can come in the form of aerial systems (drones), ground robots or unmanned maritime systems. Each of these robots gathers data about its environment for analysis and reasoning purposes. As more and more robotic systems are deployed, the amount of environmental data gathered by these systems also increases tremendously. This gives rise to a new problem: how to coherently combine the environmental information acquired by different robotic systems into one representation that is both accurate and easy to use by human end-users? In this thesis, we introduce novel methodologies to solve this data fusion problem, by proposing a novel framework for combining heterogeneous 3D data models acquired by different robotic systems, operated in unknown large unstructured outdoor environments into a common homogeneous model. The first proposed novelty of the research work is a fast and robust ground-based 3D map reconstruction methodology for large-scale unstructured outdoor environments. It is based on an enhanced Iterative-Closest- Point algorithm and an iterative error minimization structure, as well as the fast and computational very efficient method for outlier analysis and removal in 3D point clouds. The second proposed novelty of the research work is a registration methodology combining heterogeneous data-sets acquired from unmanned aerial and ground vehicles (UAV and UGV). This is accomplished by introducing a semi-automated 3D registration framework. The framework is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, it does not require a good initial overlap between the two heterogeneous UGV and UAV point clouds. Our framework strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous data-sets and harsh-outdoor environments) and fully manual registration approaches (which are labour-intensive). A special and defining aspect of this PhD. work was that we did not only focus on investigating scientific and technical innovations but that we also concentrated on bringing these innovations to the terrain in real operational environments in the security context. As an example, we deployed the technological tools developed in the framework of this research work to the field for demining and crisis relief operations in an actual crisis situation. This operational deployment was highly successful, based upon the feedback provided by the end-users.

    @PHDTHESIS {phdbalta,
    author = "Haris Balta",
    title = "Spatial registration of 3D data from aerial and ground-based unmanned robotic systems",
    school = "Royal Military Academy of Belgium",
    year = "2017",
    project={NRTP,ICARUS,TIRAMISU},
    abstract = {Robotic systems are more and more leaving the protected laboratory environment and entering our daily lives. These robotic entities can come in the form of aerial systems (drones), ground robots or unmanned maritime systems. Each of these robots gathers data about its environment for analysis and reasoning purposes. As more and more robotic systems are deployed, the amount of environmental data gathered by these systems also increases tremendously. This gives rise to a new problem: how to coherently combine the environmental information acquired by different robotic systems into one representation that is both accurate and easy to use by human end-users? In this thesis, we introduce novel methodologies to solve this data fusion problem, by proposing a novel framework for combining heterogeneous 3D data models acquired by different robotic systems, operated in unknown large unstructured outdoor environments into a common homogeneous model.
    The first proposed novelty of the research work is a fast and robust ground-based 3D map reconstruction methodology for large-scale unstructured outdoor environments. It is based on an enhanced Iterative-Closest- Point algorithm and an iterative error minimization structure, as well as the fast and computational very efficient method for outlier analysis and removal in 3D point clouds.
    The second proposed novelty of the research work is a registration methodology combining heterogeneous data-sets acquired from unmanned aerial and ground vehicles (UAV and UGV). This is accomplished by introducing a semi-automated 3D registration framework. The framework is capable of coping with an arbitrary scale difference between the point clouds, without any information about their initial position and orientation. Furthermore, it does not require a good initial overlap between the two heterogeneous UGV and UAV point clouds. Our framework strikes an elegant balance between the existing fully automated 3D registration systems (which often fail in the case of heterogeneous data-sets and harsh-outdoor environments) and fully manual registration approaches (which are labour-intensive).
    A special and defining aspect of this PhD. work was that we did not only focus on investigating scientific and technical innovations but that we also concentrated on bringing these innovations to the terrain in real operational environments in the security context. As an example, we deployed the technological tools developed in the framework of this research work to the field for demining and crisis relief operations in an actual crisis situation. This operational deployment was highly successful, based upon the feedback provided by the end-users.},
    unit= {meca-ras}
    }

2016

  • M. M. Marques, R. Parreira, V. Lobo, A. Martins, A. Matos, N. Cruz, J. M. Almeida, J. C. Alves, E. Silva, J. Bedkowski, K. Majek, M. Pelka, P. Musialik, H. Ferreira, A. Dias, B. Ferreira, G. Amaral, A. Figueiredo, R. Almeida, F. Silva, D. Serrano, G. Moreno, G. De Cubber, H. Balta, and H. Beglerovic, “Use of multi-domain robots in search and rescue operations — Contributions of the ICARUS team to the euRathlon 2015 challenge," in OCEANS 2016, Shanghai, China, 2016, p. 1–7.
    [BibTeX] [Download PDF] [DOI]
    @InProceedings{marques2016use,
    author = {Mario Monteiro Marques and Rui Parreira and Victor Lobo and Alfredo Martins and Anibal Matos and Nuno Cruz and Jose Miguel Almeida and Jose Carlos Alves and Eduardo Silva and Janusz Bedkowski and Karol Majek and Michal Pelka and Pawel Musialik and Hugo Ferreira and Andre Dias and Bruno Ferreira and Guilherme Amaral and Andre Figueiredo and Rui Almeida and Filipe Silva and Daniel Serrano and German Moreno and De Cubber, Geert and Haris Balta and Halil Beglerovic},
    booktitle = {{OCEANS} 2016},
    title = {Use of multi-domain robots in search and rescue operations {\textemdash} Contributions of the {ICARUS} team to the {euRathlon} 2015 challenge},
    year = {2016},
    month = apr,
    organization = {IEEE},
    pages = {1--7},
    publisher = {{IEEE}},
    doi = {10.1109/oceansap.2016.7485354},
    project = {ICARUS},
    unit= {meca-ras},
    address = {Shanghai, China},
    url = {http://mecatron.rma.ac.be/pub/2016/euRathlon2015_paper_final.pdf},
    }

  • H. Balta, J. Bedkowski, S. Govindaraj, K. Majek, P. Musialik, D. Serrano, K. Alexis, R. Siegwart, and G. De Cubber, “Integrated Data Management for a Fleet of Search-and-rescue Robots," Journal of Field Robotics, vol. 34, iss. 3, p. 539–582, 2016.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    Search‐and‐rescue operations have recently been confronted with the introduction of robotic tools that assist the human search‐and‐rescue workers in their dangerous but life‐saving job of searching for human survivors after major catastrophes. However, the world of search and rescue is highly reliant on strict procedures for the transfer of messages, alarms, data, and command and control over the deployed assets. The introduction of robotic tools into this world causes an important structural change in this procedural toolchain. Moreover, the introduction of search‐and‐rescue robots acting as data gatherers could potentially lead to an information overload toward the human search‐and‐rescue workers, if the data acquired by these robotic tools are not managed in an intelligent way. With that in mind, we present in this paper an integrated data combination and data management architecture that is able to accommodate real‐time data gathered by a fleet of robotic vehicles on a crisis site, and we present and publish these data in a way that is easy to understand by end‐users. In the scope of this paper, a fleet of unmanned ground and aerial search‐and‐rescue vehicles is considered, developed within the scope of the European ICARUS project. As a first step toward the integrated data‐management methodology, the different robotic systems require an interoperable framework in order to pass data from one to another and toward the unified command and control station. As a second step, a data fusion methodology will be presented, combining the data acquired by the different heterogenic robotic systems. The computation needed for this process is done in a novel mobile data center and then (as a third step) published in a software as a service (SaaS) model. The SaaS model helps in providing access to robotic data over ubiquitous Ethernet connections. As a final step, we show how the presented data‐management architecture allows for reusing recorded exercises with real robots and rescue teams for training purposes and teaching search‐and‐rescue personnel how to handle the different robotic tools. The system was validated in two experiments. First, in the controlled environment of a military testing base, a fleet of unmanned ground and aerial vehicles was deployed in an earthquake‐response scenario. The data gathered by the different interoperable robotic systems were combined by a novel mobile data center and presented to the end‐user public. Second, an unmanned aerial system was deployed on an actual mission with an international relief team to help with the relief operations after major flooding in Bosnia in the spring of 2014. Due to the nature of the event (floods), no ground vehicles were deployed here, but all data acquired by the aerial system (mainly three‐dimensional maps) were stored in the ICARUS data center, where they were securely published for authorized personnel all over the world. This mission (which is, to our knowledge, the first recorded deployment of an unmanned aerial system by an official governmental international search‐and‐rescue team in another country) proved also the concept of the procedural integration of the ICARUS data management system into the existing procedural toolchain of the search and rescue workers, and this in an international context (deployment from Belgium to Bosnia). The feedback received from the search‐and‐rescue personnel on both validation exercises was highly positive, proving that the ICARUS data management system can efficiently increase the situational awareness of the search‐and‐rescue personnel.

    @Article{balta2017integrated,
    author = {Haris Balta and Janusz Bedkowski and Shashank Govindaraj and Karol Majek and Pawel Musialik and Daniel Serrano and Kostas Alexis and Roland Siegwart and De Cubber, Geert},
    journal = {Journal of Field Robotics},
    title = {Integrated Data Management for a Fleet of Search-and-rescue Robots},
    year = {2016},
    month = jul,
    number = {3},
    pages = {539--582},
    volume = {34},
    abstract = {Search‐and‐rescue operations have recently been confronted with the introduction of robotic tools that assist the human search‐and‐rescue workers in their dangerous but life‐saving job of searching for human survivors after major catastrophes. However, the world of search and rescue is highly reliant on strict procedures for the transfer of messages, alarms, data, and command and control over the deployed assets. The introduction of robotic tools into this world causes an important structural change in this procedural toolchain. Moreover, the introduction of search‐and‐rescue robots acting as data gatherers could potentially lead to an information overload toward the human search‐and‐rescue workers, if the data acquired by these robotic tools are not managed in an intelligent way. With that in mind, we present in this paper an integrated data combination and data management architecture that is able to accommodate real‐time data gathered by a fleet of robotic vehicles on a crisis site, and we present and publish these data in a way that is easy to understand by end‐users. In the scope of this paper, a fleet of unmanned ground and aerial search‐and‐rescue vehicles is considered, developed within the scope of the European ICARUS project. As a first step toward the integrated data‐management methodology, the different robotic systems require an interoperable framework in order to pass data from one to another and toward the unified command and control station. As a second step, a data fusion methodology will be presented, combining the data acquired by the different heterogenic robotic systems. The computation needed for this process is done in a novel mobile data center and then (as a third step) published in a software as a service (SaaS) model. The SaaS model helps in providing access to robotic data over ubiquitous Ethernet connections. As a final step, we show how the presented data‐management architecture allows for reusing recorded exercises with real robots and rescue teams for training purposes and teaching search‐and‐rescue personnel how to handle the different robotic tools. The system was validated in two experiments. First, in the controlled environment of a military testing base, a fleet of unmanned ground and aerial vehicles was deployed in an earthquake‐response scenario. The data gathered by the different interoperable robotic systems were combined by a novel mobile data center and presented to the end‐user public. Second, an unmanned aerial system was deployed on an actual mission with an international relief team to help with the relief operations after major flooding in Bosnia in the spring of 2014. Due to the nature of the event (floods), no ground vehicles were deployed here, but all data acquired by the aerial system (mainly three‐dimensional maps) were stored in the ICARUS data center, where they were securely published for authorized personnel all over the world. This mission (which is, to our knowledge, the first recorded deployment of an unmanned aerial system by an official governmental international search‐and‐rescue team in another country) proved also the concept of the procedural integration of the ICARUS data management system into the existing procedural toolchain of the search and rescue workers, and this in an international context (deployment from Belgium to Bosnia). The feedback received from the search‐and‐rescue personnel on both validation exercises was highly positive, proving that the ICARUS data management system can efficiently increase the situational awareness of the search‐and‐rescue personnel.},
    doi = {10.1002/rob.21651},
    publisher = {Wiley},
    project = {ICARUS},
    unit= {meca-ras},
    url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/rob.21651},
    }

2015

  • H. Balta, G. De Cubber, Y. Baudoin, and D. Doroftei, “UAS deployment and data processing during the Balkans flooding with the support to Mine Action," in 8th IARP Workshop on Robotics for Risky Environments, Lisbon, Portugal, 2015.
    [BibTeX] [Abstract] [Download PDF]

    In this paper, we provide a report on a real relief operation mission, jointly conducted by two European research projects, in response to the massive flooding in the Balkan in spring 2014. Un Unmanned Aerial System was deployed on-site in collaboration with traditional relief workers, to support them with damage assessment, area mapping, visual inspection and re-localizing the many explosive remnants of war which have been moved due to the flooding and landslides. The destructive impact of landslides, sediment torrents and floods on the mine fields and the change of mine action situation resulted with significant negative environmental and security consequences. Novel robotic technologies and data processing methodologies were brought from the research labs and directly applied onto the terrain in order to support the relief workers and minimize human suffering.

    @InProceedings{balta2015uas,
    author = {Balta, Haris and De Cubber, Geert and Baudoin, Yvan and Doroftei, Daniela},
    booktitle = {8th IARP Workshop on Robotics for Risky Environments},
    title = {{UAS} deployment and data processing during the {Balkans} flooding with the support to Mine Action},
    year = {2015},
    abstract = {In this paper, we provide a report on a real relief operation mission, jointly conducted by two European research projects, in response to the massive flooding in the Balkan in spring 2014. Un Unmanned Aerial System was deployed on-site in collaboration with traditional relief workers, to support them with damage assessment, area mapping, visual inspection and re-localizing the many explosive remnants of war which have been moved due to the flooding and landslides. The destructive impact of landslides, sediment torrents and floods on the mine fields and the change of mine action situation resulted with significant negative environmental and security consequences. Novel robotic technologies and data processing methodologies were brought from the research labs and directly applied onto the terrain in order to support the relief workers and minimize human suffering.},
    project = {ICARUS},
    address = {Lisbon, Portugal},
    url = {http://mecatron.rma.ac.be/pub/2015/RISE_2015_Haris_Balta_RMA.PDF},
    unit= {meca-ras}
    }

  • G. De Cubber and H. Balta, “Terrain Traversability Analysis using full-scale 3D Processing," in 8th IARP Workshop on Robotics for Risky Environments, Lisbon, Portugal, 2015.
    [BibTeX] [Abstract] [Download PDF]

    Autonomous robotic systems which aspire to navigate through rough unstructured terrain require the capability to reason about the environmental characteristics of their environment. As a first priority, the robotic systems need to assess the degree of traversability of their immediate environment to ensure their mobility while navigating through these rough environments. This paper presents a novel terrain-traversability analyis methodology which is based on processing the full 3D model of the terrain, not on a projected or downscaled version of this model. The approach is validated using field tests using a time-of-flight camera.

    @InProceedings{de2015terrain,
    author = {De Cubber, Geert and Balta, Haris},
    booktitle = {8th IARP Workshop on Robotics for Risky Environments},
    title = {Terrain Traversability Analysis using full-scale {3D} Processing},
    year = {2015},
    abstract = {Autonomous robotic systems which aspire to navigate through rough unstructured terrain require the capability to reason about the environmental characteristics of their environment. As a first priority, the robotic systems need to assess the degree of traversability of their immediate environment to ensure their mobility while navigating through these rough environments. This paper presents a novel terrain-traversability analyis methodology which is based on processing the full 3D model of the terrain, not on a projected or downscaled version of this model. The approach is validated using field tests using a time-of-flight camera.},
    project = {ICARUS},
    address = {Lisbon, Portugal},
    url = {http://mecatron.rma.ac.be/pub/2015/Terrain Traversability Analysis.pdf},
    unit= {meca-ras}
    }

  • O. De Meyst, T. Goethals, H. Balta, G. De Cubber, and R. Haelterman, “Autonomous guidance for a UAS along a staircase," in International Symposium on Visual Computing, Las Vegas, USA, 2015, p. 466–475.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    In the quest for fully autonomous unmanned aerial systems (UAS), multiple challenges are faced. For enabling autonomous UAS navigation in indoor environments, one of the major bottlenecks is the capability to autonomously traverse narrow 3D – passages, like staircases. This paper presents a novel integrated system that implements a semi-autonomous navigation system for a quadcopter. The navigation system permits the UAS to detect a staircase using only the images provided by an on-board monocular camera. A 3D model of this staircase is then automatically reconstructed and this model is used to guide the UAS to the top of the detected staircase. For validating the methodology, a proof of concept is created, based on the Parrot AR.Drone 2.0 which is a cheap commercial off-the-shelf quadcopter.

    @InProceedings{de2015autonomous,
    author = {De Meyst, Olivier and Goethals, Thijs and Balta, Haris and De Cubber, Geert and Haelterman, Rob},
    booktitle = {International Symposium on Visual Computing},
    title = {Autonomous guidance for a {UAS} along a staircase},
    year = {2015},
    organization = {Springer, Cham},
    pages = {466--475},
    abstract = {In the quest for fully autonomous unmanned aerial systems (UAS), multiple challenges are faced. For enabling autonomous UAS navigation in indoor environments, one of the major bottlenecks is the capability to autonomously traverse narrow 3D - passages, like staircases. This paper presents a novel integrated system that implements a semi-autonomous navigation system for a quadcopter. The navigation system permits the UAS to detect a staircase using only the images provided by an on-board monocular camera. A 3D model of this staircase is then automatically reconstructed and this model is used to guide the UAS to the top of the detected staircase. For validating the methodology, a proof of concept is created, based on the Parrot AR.Drone 2.0 which is a cheap commercial off-the-shelf quadcopter.},
    doi = {10.1007/978-3-319-27857-5_42},
    project = {ICARUS},
    address = {Las Vegas, USA},
    unit= {meca-ras},
    url = {https://link.springer.com/chapter/10.1007/978-3-319-27857-5_42},
    }

  • E. Avdic, H. Balta, and T. Ivelja, “UAS deployment and data processing of natural disaster with impact to mine action in B and H, case study: Region Olovo," in International Symposium Mine Action 2015, Biograd, Croatia, 2015, pp. 5-12.
    [BibTeX] [Abstract] [Download PDF]

    In this paper, we present a case study report on how novel robotics technologies like the Unmanned Aerial System (UAS) and data processing methodologies could be used in order to support the traditional mine action procedures and be directly applied onto the terrain while increasing the operational efficiency, supporting mine action workers and minimizing human suffering in case of natural disaster with impact to mine action. Our case study is focusing on the region Olovo (Central Bosnia and Herzegovina) in response to massive flooding, landslides and sediment torrents in spring- summer of 2014. Such destructive impact of the natural disaster on the mine action situation resulted with a re-localizing of many explosive remnants of war which have been moved due to the flooding and landslides with significant negative environmental and security consequences increasing new potentially suspected hazardous areas. What will be elaborated in this paper is the following: problem definition with a statement of needs, data acquisition procedures with UAS, data processing and quality assessment and usability in further mine action procedures.

    @INPROCEEDINGS{balta2015article,
    author={Avdic, Esad and Balta, Haris and Ivelja, Tamara},
    booktitle={International Symposium Mine Action 2015},
    year = {2015},
    address = {Biograd, Croatia},
    pages = {5-12},
    keywords = {Mine Action Support, Unmanned Aerial System, Natural Disaster},
    title = {UAS deployment and data processing of natural disaster with impact to mine action in B and H, case study: Region Olovo},
    keyword = {Mine Action Support, Unmanned Aerial System, Natural Disaster},
    publisher = {HCR-CTRO d.o.o.},
    publisherplace = {Biograd, Hrvatska},
    project={TIRAMISU},
    url={http://mecatron.rma.ac.be/pub/2015/HUDEM_2015_Avdic_Balta_Ivelja_final_ver.pdf},
    abstract= {In this paper, we present a case study report on how novel robotics technologies like the Unmanned Aerial System (UAS) and data processing methodologies could be used in order to support the traditional mine action procedures and be directly applied onto the terrain while increasing the operational efficiency, supporting mine action workers and minimizing human suffering in case of natural disaster with impact to mine action. Our case study is focusing on the region Olovo (Central Bosnia and Herzegovina) in response to massive flooding, landslides and sediment torrents in spring- summer of 2014. Such destructive impact of the natural disaster on the mine action situation resulted with a re-localizing of many explosive remnants of war which have been moved due to the flooding and landslides with significant negative environmental and security consequences increasing new potentially suspected hazardous areas. What will be elaborated in this paper is the following: problem definition with a statement of needs, data acquisition procedures with UAS, data processing and quality assessment and usability in further mine action procedures.},
    unit= {meca-ras}
    }

2014

  • G. De Cubber, H. Balta, and C. Lietart, “Teodor: A semi-autonomous search and rescue and demining robot," in Advanced Concepts on Mechanical Engineering (ACME), Iasi, Romania, 2014.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    In this paper, we present a ground robotic system which is developed to deal with rough outdoor conditions. The platform is to be used as an environmental monitoring robot for 2 main application areas: 1) Humanitarian demining: The vehicle is equipped with a specialized multichannel metal detector array. An unmanned aerial system supports it for locating suspected locations of mines, which can then be confirmed by the ground vehicle. 2) Search and rescue: The vehicle is equipped with human victim detection sensors and a 3D camera enabling it to assess the traversability of the terrain in front of the robot in order to be able to navigate autonomously. This paper discusses both the mechanical design of these platforms as the autonomous perception capabilities on board of these vehicles.

    @InProceedings{de2014teodor,
    author = {De Cubber, Geert and Balta, Haris and Lietart, Claude},
    booktitle = {Advanced Concepts on Mechanical Engineering (ACME)},
    title = {Teodor: A semi-autonomous search and rescue and demining robot},
    year = {2014},
    abstract = {In this paper, we present a ground robotic system which is developed to deal with rough outdoor conditions. The platform is to be used as an environmental monitoring robot for 2 main application areas: 1) Humanitarian demining: The vehicle is equipped with a specialized multichannel metal detector array. An unmanned aerial system supports it for locating suspected locations of mines, which can then be confirmed by the ground vehicle. 2) Search and rescue: The vehicle is equipped with human victim detection sensors and a 3D camera enabling it to assess the traversability of the terrain in front of the robot in order to be able to navigate autonomously. This paper discusses both the mechanical design of these platforms as the autonomous perception
    capabilities on board of these vehicles.},
    doi = {10.4028/www.scientific.net/amm.658.599},
    project = {ICARUS},
    address = {Iasi, Romania},
    url = {http://mecatron.rma.ac.be/pub/2014/Teodor - A semi-autonomous search and rescue and demining robot - full article.pdf},
    unit= {meca-ras}
    }

  • G. De Cubber, H. Balta, D. Doroftei, and Y. Baudoin, “UAS deployment and data processing during the Balkans flooding," in 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics (2014), Toyako-cho, Hokkaido, Japan, 2014, p. 1–4.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    This project paper provides a report on a real relief operation mission, jointly conducted by two European research projects, in response to the massive flooding in the Balkan in spring 2014. Un Unmanned Aerial System was deployed on-site in collaboration with traditional relief workers, to support them with damage assessment, area mapping, visual inspection and re-localizing the many explosive remnants of war which have been moved due to the flooding and landslides. Novel robotic technologies and data processing methodologies were brought from the research labs and directly applied onto the terrain in order to support the relief workers and minimize human suffering.

    @InProceedings{de2014uas,
    author = {De Cubber, Geert and Balta, Haris and Doroftei, Daniela and Baudoin, Yvan},
    booktitle = {2014 IEEE International Symposium on Safety, Security, and Rescue Robotics (2014)},
    title = {{UAS} deployment and data processing during the Balkans flooding},
    year = {2014},
    organization = {IEEE},
    pages = {1--4},
    abstract = {This project paper provides a report on a real relief operation mission, jointly conducted by two European research projects, in response to the massive flooding in the Balkan in spring 2014. Un Unmanned Aerial System was deployed on-site in collaboration with traditional relief workers, to support them with damage assessment, area mapping, visual inspection and re-localizing the many explosive remnants of war which have been moved due to the flooding and landslides. Novel robotic technologies and data processing methodologies were brought from the research labs and directly applied onto the terrain in order to support the relief workers and minimize human suffering.},
    doi = {10.1109/ssrr.2014.7017670},
    project = {ICARUS},
    address = {Toyako-cho, Hokkaido, Japan},
    url = {http://mecatron.rma.ac.be/pub/2014/SSRR2014_proj_037.pdf},
    unit= {meca-ras}
    }

  • M. Pelka, K. Majek, J. Bedkowski, P. Musialik, A. Maslowski, G. de Cubber, H. Balta, A. Coelho, R. Goncalves, R. Baptista, J. M. Sanchez, and S. Govindaraj, “Training and Support system in the Cloud for improving the situational awareness in Search and Rescue (SAR) operations," in 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics (2014), Toyako-cho, Hokkaido, Japan, 2014, p. 1–6.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    In this paper, a Training and Support system for Search and Rescue operations is described. The system is a component of the ICARUS project (http://www.fp7-icarus.eu) which has a goal to develop sensor, robotic and communication technologies for Human Search And Rescue teams. The support system for planning and managing complex SAR operations is implemented as a command and control component that integrates different sources of spatial information, such as maps of the affected area, satellite images and sensor data coming from the unmanned robots, in order to provide a situation snapshot to the rescue team who will make the necessary decisions. Support issues will include planning of frequency resources needed for given areas, prediction of coverage conditions, location of fixed communication relays, etc. The training system is developed for the ICARUS operators controlling UGVs (Unmanned Ground Vehicles), UAVs (Unmanned Aerial Vehicles) and USVs (Unmanned Surface Vehicles) from a unified Remote Control Station (RC2). The Training and Support system is implemented in SaaS model (Software as a Service). Therefore, its functionality is available over the Ethernet. SAR ICARUS teams from different countries can be trained simultaneously on a shared virtual stage. In this paper we will show the multi-robot 3D mapping component (aerial vehicle and ground vehicles). We will demonstrate that these 3D maps can be used for Training purpose. Finally we demonstrate current approach for ICARUS Urban SAR (USAR) and Marine SAR (MSAR) operation training.

    @InProceedings{pelka2014training,
    author = {Michal Pelka and Karol Majek and Janusz Bedkowski and Pawel Musialik and Andrzej Maslowski and Geert de Cubber and Haris Balta and Antonio Coelho and Ricardo Goncalves and Ricardo Baptista and Jose Manuel Sanchez and Shashank Govindaraj},
    booktitle = {2014 {IEEE} International Symposium on Safety, Security, and Rescue Robotics (2014)},
    title = {Training and Support system in the Cloud for improving the situational awareness in Search and Rescue ({SAR}) operations},
    year = {2014},
    month = oct,
    organization = {IEEE},
    pages = {1--6},
    publisher = {{IEEE}},
    abstract = {In this paper, a Training and Support system for Search and Rescue operations is described. The system is a component of the ICARUS project (http://www.fp7-icarus.eu) which has a goal to develop sensor, robotic and communication technologies for Human Search And Rescue teams. The support system for planning and managing complex SAR operations is implemented as a command and control component that integrates different sources of spatial information, such as maps of the affected area, satellite images and sensor data coming from the unmanned robots, in order to provide a situation snapshot to the rescue team who will make the necessary decisions. Support issues will include planning of frequency resources needed for given areas, prediction of coverage conditions, location of fixed communication relays, etc. The training system is developed for the ICARUS operators controlling UGVs (Unmanned Ground Vehicles), UAVs (Unmanned Aerial Vehicles) and USVs (Unmanned Surface Vehicles) from a unified Remote Control Station (RC2). The Training and Support system is implemented in SaaS model (Software as a Service). Therefore, its functionality is available over the Ethernet. SAR ICARUS teams from different countries can be trained simultaneously on a shared virtual stage. In this paper we will show the multi-robot 3D mapping component (aerial vehicle and ground vehicles). We will demonstrate that these 3D maps can be used for Training purpose. Finally we demonstrate current approach for ICARUS Urban SAR (USAR) and Marine SAR (MSAR) operation training.},
    doi = {10.1109/ssrr.2014.7017644},
    project = {ICARUS},
    address = {Toyako-cho, Hokkaido, Japan},
    url = {https://ieeexplore.ieee.org/document/7017644?arnumber=7017644&sortType=asc_p_Sequence&filter=AND(p_IS_Number:7017643)=},
    unit= {meca-ras}
    }

  • G. De Cubber and H. Balta, “ICARUS RPAS AND THEIR OPERATIONAL USE IN Bosnia," in RPAS 2014, Brussels, Belgium, 2014.
    [BibTeX] [Abstract] [Download PDF]

    This is a report in the field mission with an unmanned aircraft system in Spring 2014 in Bosnia, to help with flood relief and mine clearing operations.

    @InProceedings{de2014icarus,
    author = {De Cubber, Geert and Balta, Haris},
    booktitle = {RPAS 2014},
    title = {{ICARUS RPAS} AND THEIR OPERATIONAL USE IN {Bosnia}},
    year = {2014},
    organization = {UVS International},
    abstract = {This is a report in the field mission with an unmanned aircraft system in Spring 2014 in Bosnia, to help with flood relief and mine clearing operations.},
    project = {ICARUS},
    address = {Brussels, Belgium},
    url = {http://mecatron.rma.ac.be/pub/2014/Icarus Project - RPAS in Bosnia_.pdf},
    unit= {meca-ras}
    }

2013

  • H. Balta, G. De Cubber, D. Doroftei, Y. Baudoin, and H. Sahli, “Terrain traversability analysis for off-road robots using time-of-flight 3d sensing," in 7th IARP International Workshop on Robotics for Risky Environment-Extreme Robotics, Saint-Petersburg, Russia, 2013.
    [BibTeX] [Abstract] [Download PDF]

    In this paper we present a terrain traversability analysis methodology which classifies all image pixels in the TOF image as traversable or not, by estimating for each pixel a traversability score which is based upon the analysis of the 3D (depth data) and 2D (IR data) content of the TOF camera data. This classification result is then used for the (semi) – autonomous navigation of two robotic systems, operating in extreme environments: a search and rescue robot and a humanitarian demining robot. Integrated in autonomous robot control architecture, terrain traversability classification increases the environmental situational awareness and enables a mobile robot to navigate (semi) – autonomously in an unstructured dynamical outdoor environment.

    @InProceedings{balta2013terrain,
    author = {Balta, Haris and De Cubber, Geert and Doroftei, Daniela and Baudoin, Yvan and Sahli, Hichem},
    booktitle = {7th IARP International Workshop on Robotics for Risky Environment-Extreme Robotics},
    title = {Terrain traversability analysis for off-road robots using time-of-flight 3d sensing},
    year = {2013},
    abstract = {In this paper we present a terrain traversability analysis methodology which classifies all image pixels in the TOF image as traversable or not, by estimating for each pixel a traversability score which is based upon the analysis of the 3D (depth data) and 2D (IR data) content of the TOF camera data. This classification result is then used for the (semi) – autonomous navigation of two robotic systems, operating in extreme environments: a search and rescue robot and a humanitarian demining robot. Integrated in autonomous robot control architecture, terrain traversability classification increases the environmental situational awareness and enables a mobile robot to navigate (semi) – autonomously in an unstructured dynamical outdoor environment.},
    project = {ICARUS},
    address = {Saint-Petersburg, Russia},
    url = {http://mecatron.rma.ac.be/pub/2013/Terrain Traversability Analysis ver 4-HS.pdf},
    unit= {meca-ras}
    }

  • H. Balta, S. Rossi, S. Iengo, B. Siciliano, A. Finzi, and G. De Cubber, “Adaptive behavior-based control for robot navigation: A multi-robot case study," in 2013 XXIV International Conference on Information, Communication and Automation Technologies (ICAT), Sarajevo, Bosnia and Herzegovina, 2013, p. 1–7.
    [BibTeX] [Abstract] [Download PDF] [DOI]

    The main focus of the work presented in this paper is to investigate the application of certain biologically-inspired control strategies in the field of autonomous mobile robots, with particular emphasis on multi-robot navigation systems. The control architecture used in this work is based on the behavior-based approach. The main argument in favor of this approach is its impressive and rapid practical success. This powerful methodology has demonstrated simplicity, parallelism, perception-action mapping and real implementation. When a group of autonomous mobile robots needs to achieve a goal operating in complex dynamic environments, such a task involves high computational complexity and a large volume of data needed for continuous monitoring of internal states and the external environment. Most autonomous mobile robots have limited capabilities in computation power or energy sources with limited capability, such as batteries. Therefore, it becomes necessary to build additional mechanisms on top of the control architecture able to efficiently allocate resources for enhancing the performance of an autonomous mobile robot. For this purpose, it is necessary to build an adaptive behavior-based control system focused on sensory adaptation. This adaptive property will assure efficient use of robot’s limited sensorial and cognitive resources. The proposed adaptive behavior-based control system is then validated through simulation in a multi-robot environment with a task of prey/predator scenario.

    @InProceedings{balta2013adaptive,
    author = {Balta, Haris and Rossi, Silvia and Iengo, Salvatore and Siciliano, Bruno and Finzi, Alberto and De Cubber, Geert},
    booktitle = {2013 XXIV International Conference on Information, Communication and Automation Technologies (ICAT)},
    title = {Adaptive behavior-based control for robot navigation: A multi-robot case study},
    year = {2013},
    organization = {IEEE},
    pages = {1--7},
    abstract = {The main focus of the work presented in this paper is to investigate the application of certain biologically-inspired control strategies in the field of autonomous mobile robots, with particular emphasis on multi-robot navigation systems. The control architecture used in this work is based on the behavior-based approach. The main argument in favor of this approach is its impressive and rapid practical success. This powerful methodology has demonstrated simplicity, parallelism, perception-action mapping and real implementation. When a group of autonomous mobile robots needs to achieve a goal operating in complex dynamic environments, such a task involves high computational complexity and a large volume of data needed for continuous monitoring of internal states and the external environment. Most autonomous mobile robots have limited capabilities in computation power or energy sources with limited capability, such as batteries. Therefore, it becomes necessary to build additional mechanisms on top of the control architecture able to efficiently allocate resources for enhancing the performance of an autonomous mobile robot. For this purpose, it is necessary to build an adaptive behavior-based control system focused on sensory adaptation. This adaptive property will assure efficient use of robot's limited sensorial and cognitive resources. The proposed adaptive behavior-based control system is then validated through simulation in a multi-robot environment with a task of prey/predator scenario.},
    doi = {10.1109/icat.2013.6684083},
    address = {Sarajevo, Bosnia and Herzegovina},
    project = {ICARUS},
    url = {https://ieeexplore.ieee.org/document/6684083?tp=&arnumber=6684083},
    unit= {meca-ras}
    }

  • H. Balta, G. De Cubber, and D. Doroftei, “Increasing Situational Awareness through Outdoor Robot Terrain Traversability Analysis based on Time- Of-Flight Camera," in Spring School on Developmental Robotics and Cognitive Bootstrapping, Athens, Greece: , 2013, p. 8.
    [BibTeX] [Abstract]

    Poster paper

    @InCollection{balta2013increasing,
    author = {Balta, Haris and De Cubber, Geert and Doroftei, Daniela},
    booktitle = {Spring School on Developmental Robotics and Cognitive Bootstrapping},
    title = {Increasing Situational Awareness through Outdoor Robot Terrain Traversability Analysis based on Time- Of-Flight Camera},
    year = {2013},
    number = {Developmental Robotics and Cognitive Bootstrapping},
    pages = {8},
    abstract = {Poster paper},
    address = {Athens, Greece},
    project = {ICARUS},
    unit= {meca-ras}
    }

2012

  • A. Conduraru, I. Conduraru, E. Puscalau, G. De Cubber, D. Doroftei, and H. Balta, “Development of an autonomous rough-terrain robot," in IROS2012 Workshop on Robots and Sensors integration in future rescue INformation system (ROSIN’12), Villamoura, Portugal, 2012.
    [BibTeX] [Abstract] [Download PDF]

    In this paper, we discuss the development process of a mobile robot intended for environmental observation applications. The paper describes how a standard tele-operated Explosive Ordnance Disposal (EOD) robot was upgraded with electronics, sensors, computing power and autonomous capabilities, such that it becomes able to execute semi-autonomous missions, e.g. for search & rescue or humanitarian demining tasks. The aim of this paper is not to discuss the details of the navigation algorithms (as these are often task-dependent), but more to concentrate on the development of the platform and its control architecture as a whole.

    @InProceedings{conduraru2012development,
    author = {Conduraru, Alina and Conduraru, Ionel and Puscalau, Emanuel and De Cubber, Geert and Doroftei, Daniela and Balta, Haris},
    booktitle = {IROS2012 Workshop on Robots and Sensors integration in future rescue INformation system (ROSIN'12)},
    title = {Development of an autonomous rough-terrain robot},
    year = {2012},
    abstract = {In this paper, we discuss the development process of a mobile robot intended for environmental observation applications. The paper describes how a standard tele-operated Explosive Ordnance Disposal (EOD) robot was upgraded with electronics, sensors, computing power and autonomous capabilities, such that it becomes able to execute semi-autonomous missions, e.g. for search & rescue or humanitarian demining tasks. The aim of this paper is not to discuss the details of the navigation algorithms (as these are often task-dependent), but more to concentrate on the development of the platform and its control architecture as a whole.},
    project = {ICARUS},
    address = {Villamoura, Portugal},
    url = {https://pdfs.semanticscholar.org/884e/6a80c8768044a1fd68ee91f45f17e5125153.pdf},
    unit= {meca-ras}
    }