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Efficient Kinodynamic Multi-Robot Replanning in Known Workspaces

Arjav Desai, Matthew Collins, Nathan Michael

Year
2019
Citations
10

Abstract

In this work, we consider the problem of online centralized kinodynamic multi-robot replanning (from potentially non-stationary initial states) and coordination in known and cluttered workspaces. Offline state lattice reachability analysis is leveraged to decouple the planning problem into two sequential graph searches-one in the explicit geometric graph of the environment and the other in the graph of the higher-order derivatives of the robot's state-in a manner such that the intermediate vertices of a safe set of geometric paths are guaranteed to have a feasible assignment of higher-order derivatives. Without additional iterative refinement procedures, the resulting time parameterized polynomial trajectories are dynamically feasible and collision-free. Planning results with up to 20 robots in two and three dimensional workspaces suggest the suitability of the proposed approach for multi-robot replanning in known environments.

Keywords

ReachabilityWorkspaceRobotParameterized complexityComputer scienceGraphMotion planningMathematical optimizationRobot kinematicsTheoretical computer science

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