Multi-agent path finding on real robots

Roman Barták, Jiří Švancara, Věra Škopková, David Nohejl, Ivan Krasičenko

PosterID: 16
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The problem of Multi-Agent Path Finding (MAPF) is to find paths for a fixed set of agents from their current locations to some desired locations in such a way that the agents do not collide with each other. This problem has been extensively theoretically studied, frequently using an abstract model, that expects uniform durations of moving primitives and perfect synchronization of agents/robots. In this paper we study the question of how the abstract plans generated by existing MAPF algorithms perform in practice when executed on real robots, namely Ozobots. In particular, we use several abstract models of MAPF, including a robust version and a version that assumes turning of a robot, we translate the abstract plans to sequences of motion primitives executable on Ozobots, and we empirically compare the quality of plan execution (real makespan, the number of collisions).

Session E9: Multi-Agent Planning
Canb 10/27/2020, 21:00 – 22:00
10/31/2020, 04:00 – 05:00
Paris 10/27/2020, 11:00 – 12:00
10/30/2020, 18:00 – 19:00
NYC 10/27/2020, 06:00 – 07:00
10/30/2020, 13:00 – 14:00
LA 10/27/2020, 03:00 – 04:00
10/30/2020, 10:00 – 11:00