Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering
Keywords:Heuristic Search, Satisfiability Modulo Theories, Motion and Path Planning
AbstractWe introduce multi-goal multi agent path finding (MG-MAPF) which generalizes the standard discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate agents in an undirected graph from their starting vertices to one individual goal vertex per agent, MG-MAPF assigns each agent multiple goal vertices and the task is to visit each of them at least once. Solving MG-MAPF not only requires finding collision free paths for individual agents but also determining the order of visiting agent's goal vertices so that common objectives like the sum-of-costs are optimized. We suggest two novel algorithms using different paradigms to address MG-MAPF: a heuristic search-based algorithm called Hamiltonian-CBS (HCBS) and a compilation-based algorithm built using the satisfiability modulo theories (SMT), called SMT-Hamiltonian-CBS (SMT-HCBS).
How to Cite
Surynek, P. (2021). Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering. Proceedings of the AAAI Conference on Artificial Intelligence, 35(14), 12409-12417. https://doi.org/10.1609/aaai.v35i14.17472
AAAI Technical Track on Search and Optimization