Prioritized Planning Algorithms for Trajectory Coordination of Multiple Mobile Robots
This work addresses collision prevention in autonomous multi-robot systems, offering incremental improvements in completeness and speed for practical applications.
The paper tackles the problem of collision-free trajectory planning for multiple mobile robots by proposing a revised prioritized planning algorithm that reliably solves a wider class of instances where classical methods fail, and an asynchronous decentralized variant that finds solutions faster than previous synchronized approaches.
An important capability of autonomous multi-robot systems is to prevent collision among the individual robots. One approach to this problem is to plan conflict-free trajectories and let each of the robots follow its pre-planned trajectory. A widely used practical method for multi-robot trajectory planning is prioritized planning, which has been shown to be effective in practice, but is in general incomplete. Formal analysis of instances that are provably solvable by prioritized planning is still missing. Moreover, prioritized planning is a centralized algorithm, which may be in many situations undesirable. In this paper we a) propose a revised version of prioritized planning and characterize the class of instances that are provably solvable by the algorithm and b) propose an asynchronous decentralized variant of prioritized planning, which maintains the desirable properties of the centralized version and in the same time exploits the distributed computational power of the individual robots, which in most situations allows to find the joint trajectories faster. The experimental evaluation performed on real-world indoor maps shows that a) the revised version of prioritized planning reliably solves a wide class of instances on which both classical prioritized planning and popular reactive technique ORCA fail and b) the asynchronous decentralized algorithm provides solution faster than the previously proposed synchronized decentralized algorithm.