Intelligent Mobile Robotics Czech Technical University in Prague Libor Přeučil The Gerstner Lab for Intelligent Decision Making Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague Intelligent Mobile Robotics at CTU, Challenges, Achievements and Applications

Presentation outline Intelligent Mobile Robotics Division, activity targeting Core R&D technologies available Hybrid human-robot systems, applications in rescue missions Autonomous exploration and mapping solutions Collective and cooperative robotics, formation control Technology for autonomous control of UGVs and UAVs Robot autonomy for outdoor environments Planning and scheduling for pro robotics

Intelligent Mobile Robotics division History, since research fellows (5 Ph.D. degree) 4 Ph.D. students 5-10 ordinary students R&D and other activities targeting: Basic and applied research Cooperations with industries Teaching Masters/Ph.D. courses European Framework Programs, Networks of Excellence (Future and Emerging Technologies, Cognitive Systems) SW development and prototyping for safety-critical applications Training robotics (courses) over IP

Hybrid human-robot systems Technology for building next generation telematic systems (mixed human-robot teams). Allows mutual substitution of participating entities – leads to performance boosting Core application field in search and rescue, exploration and inspection missions. Concept design verified within FET IST Projekt PeLoTe,

Autonomous exploration and mapping Autonomous environment exploration builds spatial knowledge. Represents backbone task for robot autonomous navigation May be designed for robot knowledge sharing with human entities Applications: Autonomous robot operation in real environments Autonomous surveillance, inspection and transportations systems

Cooperative robotics Coordination and cooperation of multiple robots allows flexible/more efficient performance and resource usage Distributed solution without unique control centre (robust to failures) System runtime adaptation to task solution status Scalable systems Applications: Multirobot exploration and surveillance Robot formation control, convoying

Autonomous control of UGVs and UAVs Visual navigation UAVs and UGVs making use of passive sensing (vision) Real time processing, extremely robust solution to lighting conditions and environmental variations Real indoor and outdoor environments capable No navigation infrastructure needed

Robot autonomy for outdoor environments LA RGE MA PS technology for representation of extremely large and sparse environments Developed for robot operation primarily in outdoor environments Ready to handle incomplete information, capable of reasoning about the environment Application in autonomous control/navigation of UGVs/UAVs, (autonomous exploration, inspection and surveillance tasks)

Planing and scheduling for robotics Technology for: Robot control along collision-free trajectories Activity scheduling and optimization in robot groups Mission control (operator support) These tasks exhibit many constrains and high computational complexity. Novel methods providing acceptable approximate solutions of NP complete (nonsolvable) tasks. Random Sampling planning Watchman Route Problem and (Multiple)Traveling Salesman Problem for scheduling

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