Real-Time Tactical Motion Planning and Obstacle Avoidance for Multi-Robot Cooperative Reconnaissance
Faculty of Computing, Health and Science
School of Computer and Security Science
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).
Not open access