Efficient Autonomous Navigation in Dynamic Environments: Algorithm Evaluation and Multi-Robot Coordination

Abstract

Navigating indoor mobile robots in dynamic environments poses significant challenges due to obstacles and uncharted terrain. This study explores autonomous navigation systems within a laboratory-scale Flexible Manufacturing System (FMS), addressing the need for more reliable and real-time navigation. Objectives include designing a 2D map using SLAM, creating an autonomous indoor navigation system with real-time obstacle avoidance, and establishing a multi-robot navigation framework. Performance of A*, D*, TEB, and DWA algorithms is evaluated in single and multi-robot scenarios. Findings highlight A*'s effectiveness in static environments, D*'s adaptability in dynamic settings, and TEB's superiority in obstacle avoidance over DWA. The study concludes by discussing the potential of A* and TEB in multi-robot applications and suggests future research in algorithm optimization and multi-robot coordination.