Enhancing Lifelong Multi-Agent Path-finding by Using Artificial Potential Fields

We explore the use of Artificial Potential Fields (APFs) to solve Lifelong Multi-Agent Path Finding (LMAPF) problems. In LMAPF, a team of agents must move to their goal locations without collisions, and new goals are generated upon arrival. We propose methods for incorporating APFs in a range of LMAPF algorithms, including Prioritized Planning and MAPF-LNS2. Experimental results show that using APF yields up to a 7-fold increase in overall system throughput for LMAPF.

Authors

• Arseniy Pertzovsky a:1:{s:5:"en_US";s:34:"Ben-Gurion University of the Negev";}
• Roni Stern
• Ariel Felner Ben-Gurion University of the Negev
• Roie Zivan Ben-Gurion University

Keywords

• Multi-agent Pathfinding
• Artificial Potential Fields
• Multi-robot Path
• Planning