Bounded Sub-optimal Multi-Robot Path Planning Using Satisfiability Modulo Theory (SMT) Approach

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.