The development of object-oriented knowledge base and adaptive motion planning for autonomous mobile robots

Abstract

Motion planning plays an important role in the field of autonomous mobile robots. We propose a hybrid intelligent system including the object-oriented knowledge base and adaptive motion planning (AMP) algorithm. There are four major procedures in the intelligent system: a priori environment building, on-line topology map generation, candidate path searching, and behavior commands generation. The adaptive motion planning (AMP) algorithm acquires the a priori defined map and the latest or dynamic information. The algorithm then determines path and generates a sequence of motion behavior description commands for navigation. The experimental results indicate that the object-oriented knowledge base can be updated easily. The AMP algorithm can produce the suitable path and behavior commands, and fuse these behaviors to navigate the mobile robot in the dynamic environment. The proposed method is implemented on the "Chung Cheng I" autonomous mobile robot to demonstrate the reliability and flexibility.