AAAI Publications, Workshops at the Twenty-Sixth AAAI Conference on Artificial Intelligence

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Reciprocal Collision Avoidance for Quadrotor Helicopters Using LQR-Obstacles
Daman Bareiss, Jur van den Berg

Last modified: 2012-07-15

Abstract


In this paper we present a formal approach to reciprocal collision avoidance for multiple mobile robots sharing a common 2-D or 3-D workspace whose dynamics are subject to linear differential constraints. Our approach defines a protocol for robots to select their control input independently (i.e. without coordination with other robots) while guaranteeing collision-free motion for all robots, assuming the robots can perfectly observe each other's state. To this end, we use the concept of LQR-Obstacles that define sets of forbidden control inputs that lead a robot to collision with obstacles, and extend it for reciprocal collision avoidance among multiple robots. We implemented and tested our approach in 3-D simulation environments for reciprocal collision avoidance of quadrotorhelicopters, which have complex dynamics in 16-D state spaces. Our results suggest that our approach avoids collisions among over a hundred quadrotors in tight workspaces at real-time computation rates.

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