MST-based SOFM in hybrid robot architecture
Seokmin Yun, Jin‐Young Choi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2005
This paper presented a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provided real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework was verified by simulation.