Shadoks Approach to Low-Makespan Coordinated Motion Planning
This addresses the multi-agent path finding problem for robotics and AI planning, but it is incremental as it applies heuristics to a specific competition setting.
The paper tackled the CG:SHOP 2021 challenge of coordinating multiple robots to reach targets without collisions while minimizing makespan in dense, unbounded grids, achieving first place with best solutions for 202 out of 203 instances and optimal solutions for at least 105.
This paper describes the heuristics used by the Shadoks team for the CG:SHOP 2021 challenge. This year's problem is to coordinate the motion of multiple robots in order to reach their targets without collisions and minimizing the makespan. It is a classical multi agent path finding problem with the specificity that the instances are highly dense in an unbounded grid. Using the heuristics outlined in this paper, our team won first place with the best solution to 202 out of 203 instances and optimal solutions to at least 105 of them. The main ingredients include several different strategies to compute initial solutions coupled with a heuristic called Conflict Optimizer to reduce the makespan of existing solutions.