Path Planning Techniques for Multi-robot Systems: A Systematic Review

Abstract

Numerous path planning studies have been conducted in past decades due to the challenges of obtaining optimal solutions. This paper provides a comprehensive review of multi-robot path planning approaches, focusing on classical, AI-based, and hybrid methods. Bio-inspired techniques are commonly used, and AI approaches are gaining popularity. The challenges faced by multi-robot systems include the number of robots, energy efficiency, fault tolerance, robustness, and dynamic targets. Therefore, developers are continuously researching for optimal solutions that can gather the benefits of multi-robot systems while overcoming the possible challenges. This paper provides a comprehensive assessment of various path planning techniques, highlights key problems in this field, and identifies research gaps for a better multi-robot path planning experience.