Persons
doc. Ing. Martin Saska, Dr. rer. nat.
head_person_supervisor
Ing. Matěj Petrlík
Onboard multi-robot sensor fusion for team of unmanned aerial vehicles
Parakh Manoj Gupta
Trajectory Generation and Control For Outdoor Fast and Agile Flight
Ing. Pavel Petráček
Robust UAV Localization in Perception-Degraded Environments
Ing. Jiří Horyna
Control a stabilization of a swarm of unmanned aerial vehicles
Ing. Matouš Vrba
Detection and relative localization for autonomous aerial vehicles
Supervisor specialist
Ing. Václav Pritzl
Cooperative Multi-UAV Navigation in GNSS-Denied Environments
Ing. Petr Štibinger
Perception-driven autonomy for mobile robots in hazardous environments
Archive of PhD students
Ing. Robert Pěnička, Ph.D.
Data Collection Planning For Aerial Vehicles
Ing. Tomáš Báča, Ph.D.
Cooperative Sensing by a Group of Unmanned Aerial Vehicles
Ing. Vít Krátký, Ph.D.
Cooperative Sensing by a Group of Unmanned Aerial Vehicles in Environments with Obstacles
Dissertation topics
Cooperative sensing by group of unmanned aerial vehicles in environment with obstacles
- Branch of study: Computer Science – Department of Cybernetics
- Department: Department of Cybernetics
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Description:
Progress in design of methods for stabilization of unmanned helicopters allows their deployment in specific robotic scenarios in real-world conditions. Aerial vehicles are mostly used for carrying standard robotic sensors (cameras, rang-finders) and also specialized sensory equipment (measurement of radiation, pollution). Utilization of small cooperating Micro Aerial Vehicles (MAVs) brings possibility of distributed measurement by heterogeneous sensors with extended fault-tolerance, while keeping constraints given by limited payload of MAVs. This thesis will be aimed at continuation of research conducted by Multi-robot Systems group in the field of control and coordination of MAV groups. In particular, theory and methodology required for cooperative sensing by teams of MAVs will be designed and suited for multi-robot applications in environment with densely distributed obstacles, where MAVs bring added value in comparison with available systems of unmanned airplanes. Finally, conditions of stability of the MAV group will be theoretically and experimentally studied based on characteristic of environment (density of obstacles) and range of onboard sensors. Requirements: practical and theoretical experience with MAVs, knowledge of programming in C, good knowledge of mathematics.
Motion planning for formations of micro aerial vehicles
- Branch of study: Computer Science – Department of Cybernetics
- Department: Department of Cybernetics
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Description:
Recent progress in development and miniaturization of micro unmanned vehicles (MAVs) allows us to consider deployment of large systems of simple helicopters for cooperative solving a given task. State-of-the-art methods are limited to stabilization of MAV groups in laboratories equipped with precise external localization system in control feedback. Nevertheless, the task of stabilization and control of MAVs in real-world conditions requires developing of new methodology that relies on onboard sensors and onboard computational resources. The aim of this PhD thesis is to continue with research of our group in the field of motion planning and optimal control for formations with compact shape. The designed methodology and consequently the implemented system should enable planning of complex maneuvers for MAV formations in demanding environment with dynamic obstacles. PhD student will focus on theoretical and practical determination of requirements on stability and convergence of the system, taking into account sensors being used for relative localization of team members. Requirements: knowledge of programming in C and/or in MATLAB, good knowledge of mathematics, experience with MAVs is an advantage. http://imr.felk.cvut.cz/People/Martin
Motion planning for task-constrained robotic systems
- Branch of study: Cybernetics and Robotics
- Department: Department of Cybernetics
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Description:
This topic aims to enable fast motion planning in cluttered environments while satisfying these additional task constraints. Motions of robotic systems can be limited not only by obstacles, but also by additional, task-specific constraints. For example, robots cooperatively transporting an object through an environment must avoid obstacles while maintaining the object fully manipulable. While classic motion planning methods focus on finding collision-free trajectories, they become ineffective when a set of general constraints has to be considered. Despite recent progress in sampling-based planning, planning under task-specific constraints is still a challenging and open problem. The solution to such a problem can improve the deployment of multi-robot systems in the cooperative task, especially in unknown environments where fast replanning is required. The research will be focused on the utilization of the sampling-based principle to search the space while satisfying the constraints, and boosting the search by using machine learning methods. The PhD student will work on the theoretical analysis and design of the methods, as well as their experimental verification on multi-robot systems. Requirements: practical and theoretical experience with robot planning or/and control, excellent knowledge of programming in C++/Python and unix systems, good knowledge of mathematics, good English writing skills.
Multi-robot aerial systems in real-world conditions
- Branch of study: Cybernetics and Robotics
- Department: Department of Cybernetics
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Description:
This topic addresses the agility of teams of fully autonomous micro-scale aerial robots deployed in demanding real-world workspaces. Multimodal sensing capabilities onboard unmanned aerial vehicles (UAVs) will be integrated with agile control methodology to achieve robust, fully-decentralized group behavior. Swarm intelligence will be used as a tool for applying group perception to increase the robustness of UAV ego-motion and state estimation independent of the properties of the workspace. Minimalist data sharing by implicit bio-inspired communication among group members will be used for improving the agility of groups of UAVs cooperating in a compact arrangement. Theoretical analyses of the stability of the nonlinear control approach using limited computational and communication capabilities onboard UAV teams will be conducted, followed by numerical statistical analyses and experimental verification in GNSS (Global Navigation Satellite Systems) denied indoor and outdoor real-world conditions. Requirements: practical and theoretical experience with robotics, knowledge of programming in C++, good knowledge of mathematics, good English writing skills.
Multi-robot persistent monitoring and spatial coverage
- Branch of study: Computer Science – Department of Cybernetics
- Department: Department of Cybernetics
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Description:
Persistent monitoring of large environments by mobile robots is one of the most promising robotic applications. It is expected that the robots will be deployed in these scenarios in different complexity, from compact formations of closely cooperating robots to large swarms that enable information gathering simultaneously in different locations. These topics become attractive nowadays mainly due to the recent progress in development and miniaturization of Micro Aerial Vehicles (MAVs) and other aerial and ground vehicles. The thesis will be aimed at theoretical research of challenges motivated by deployment of large groups of robots in these long-term applications and by using limited onboard computational resources. Onboard processing is crucial for achieving full autonomy. In addition to the optimal coverage and coordination tasks, new strategies for optimal usage of redundant robots with limited operational time and for their replacement in case of failures will be investigated. Theoretical analyses of designed principles experimentally verified in relevant multi-robot scenarios will be part of the thesis. The experimental verification of theoretical results will be realized with MAVs of Multi-Robot Systems group and with other robots of Departments of Cybernetics and Computer Science and Engineering within the Center for Robotics and Autonomous Systems. Requirements: experience with robotics, knowledge of programming in C and in MATLAB, excellent knowledge of mathematics, experience with MAVs is an advantage.
Planning and control for aerial systems in cluttered environments
- Branch of study: Cybernetics and Robotics
- Department: Department of Cybernetics
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Description:
This PhD topic focuses on the research of methods for online trajectory planning and control of unmanned aerial vehicles in cluttered environments. The goal of the topic is to enable agile high-speed flight of autonomous aerial vehicles in unknown environments densely cluttered with obstacles. Though the astonishing agility of currently existing planning and control has been demonstrated in many research labs, solving both planning and control problems in cluttered environments on-the-fly while using the maximum agility of drones is still an open problem. Designing such methods is challenging mainly due to the tradeoff between the computational speed required for online planning and the feasibility of the trajectories that influence how agile the flight can be. However, solving this problem can significantly improve deployment of the drones in many fields such as search and rescue where decreasing the time to find survivors can save lives. The research will be focused on designing either model-based or learning-based methods for agile flight control. At the same time, the study of fast trajectory planning methods with diverse fidelity of trajectory representation is needed to allow online collision avoidance. The student’s work will span both theoretical modeling and experimental verification of the aforementioned methods. Requirements: practical and theoretical experience with robot planning or/and control, knowledge of programming in C++ and python, good knowledge of mathematics, good English writing skills.
Relative localization and stabilization of large groups of UAVs
- Branch of study: Cybernetics and Robotics
- Department: Department of Cybernetics
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Description:
The topic is focused on designing a reliable onboard localization of aerial objects (none-cooperative or cooperative group members) in proximity of unmanned aerial vehicles (UAVs). The goal of the work is designing a proper methodology for autonomous detection of fast-moving objects by sensors carried by UAVs that may fly also fast and close to obstacles that are disturbing the onboard sensors. The research will be targeted at designing real-time data processing required for agile control feedback using limited computational power carried by UAVs. Students may explore various robotic sensing capabilities such as RGB and 3D cameras, lidars, radars, UWB and fuse them into a reliable smart sensor with requirements of agile and compact multi-robot systems. Theoretical and practical properties will be analyzed with respect of various environment and transition between these environments resulting into a theory specifying assumptions for safe autonomous flight relying on such a methodology. Beside the research focused on the onboard perception, UAV ego-motion estimation and neighbor/target behavior classification and estimation will be used for designing new methods of informed tracking of fast flying objects. Requirements: practical and theoretical experience with robotics, knowledge of programming in C++, good knowledge of mathematics, good English writing skills.
Stabilization and control of swarms of micro aerial vehicles
- Branch of study: Computer Science – Department of Cybernetics
- Department: Department of Cybernetics
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Description:
Swarms of low-cost micro unmanned vehicles (MAVs) may be efficiently deployed in numerous security and other commercial applications, such as e.g. robotic surveillance, search and rescue, mapping, and environment monitoring. A group of simple MAVs is usually able to cooperatively accomplish given tasks more effectively (faster and mainly more reliable), than if using a better equipped and in total more expensive single helicopter. The aim of this PhD thesis is to design a mechanism for control and stabilization of MAV groups, which would fully exploit all key properties of swarm behavior, such as possibility of redundancy, interchangeability of swarm members, and decentralized control, with the aim to increase reliability and decrease requirements on communication. One of the possible approaches is to utilize rules of swarm behavior observed in nature, since the sense organs of animals in swarms may be described by a similar model as the sensors that can be used onboard of MAVs. The important part of the student’s work will be theoretical and experimental analysis of swarm stability in real-world conditions. Requirements: knowledge of programming in C and/or in MATLAB, good knowledge of mathematics, experience with MAVs is an advantage. http://imr.felk.cvut.cz/People/Martin
Visual relative localization and stabilization of groups of unmanned helicopters
- Branch of study: Computer Science – Department of Cybernetics
- Department: Department of Cybernetics
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Description:
The topic is focused on design of a robust visual localization of neighboring swarm members without a necessity of placing artificial identification tags on particular unmanned aerial vehicles (UAVs). The goal of the work is design of a proper methodology for autonomous detection of moving objects in front of a moving background. The research will be targeted at sufficiently fast processing of images using limited computational power carried by UAVs aimed at direct integration of outputs into the feedback control. Beyond conventional approaches of visual detection and object tracking, coordination and cooperation of swarm members will be employed to increase precision of the relative localization and its robustness. Beside the research of real time embedded solution of onboard relative localization in control feedback, this topic enables an interesting multidisciplinary research of behavior of swarms in nature. It is very difficult or impossible to study influence of changing perception of swarm members on their collective behavior in nature. The proposed system of visual relative localization enables to emulate these changes and to study their impact in artificial swarms controlled by rules observed in nature. Requirements: practical and theoretical experience with computer vision, knowledge of programming in C, good knowledge of mathematics.
