Real-Time Tactical Motion Planning and Obstacle Avoidance for Multi-Robot Cooperative Reconnaissance
Document Type
Conference Proceeding
Keywords
collision avoidance, dynamic vehicle control, mobile robots, navigation, path planning, trajectory generationDynamic environments, Hierarchical architectures, Incomplete information, Intelligence, surveillance and reconnaissances, Large urban environments, Multi-vehicles, Multirobots, Tactical planning, Trajectory generation, Unmanned ground vehicles, Vehicle Control, Collision avoidance, Control system synthesis, Cybernetics, Intelligent robots, Intelligent vehicle highway systems, Mobile robots, Navigation, Motion planning
Publisher
IEEE
Faculty
Faculty of Computing, Health and Science
School
School of Computer and Security Science
RAS ID
15005
Abstract
A key requirement for any mobile robot is achieving safe motions. This is especially difficult in a large dynamic environment where hostile objects must be avoided with incomplete information. This paper presents a novel hierarchical architecture that Team MAGICian developed, which integrates multi-vehicle tactical planning, path planning, collision avoidance, trajectory generation and dynamic vehicle control. The system is designed for a fleet of six Unmanned Ground Vehicles (UGVs) executing an Intelligence, Surveillance and Reconnaissance (ISR) mission in a large urban environment for the Multi Autonomous Ground-robotic International Challenge (MAGIC 2010).
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Comments
Boeing, A. , Pangeni, S., Braunl, T., & Lee, C. (2012). Real-Time Tactical Motion Planning and Obstacle Avoidance for Multi-Robot Cooperative Reconnaissance. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics. (pp. 3117-3122). Seoul, Korea. IEEE . Available here