Learn all about Multi-Agent Path Finding (MAPF)
P. Surynek. Bounded Sub-Optimal Multi-Robot Path Planning Using Satisfiability Modulo Theory (SMT) Approach. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
Abstract: Multi-robot path planning (MRPP) is a task of planning collision free paths for a group of robots in a graph.Each robot starts in its individual starting vertex and its task is to reach a given goal vertex. Existing techniques for solving MRPP optimally under various objectives include search-based and compilation-based approaches. Often however finding an optimal solution is too difficult hence sub-optimal algorithms that trade-off the quality of solutions and the runtime have been devised. We suggest eSMT-CBS, a new bounded sub-optimal algorithm built on top of recent compilation-based method for optimal MRPP based on satisfiability modulo theories (SMT). We compare eSMT-CBS with ECBS, a major representative of bounded sub-optimal search-based algorithms.The experimental evaluation shows significant advantage of eSMT-CBS across variety of scenarios.