A novel imitation approach on human's obstacle avoidance ability considering knowledge radius

Abstract

In order to apply human's action intelligence to improving the path and trajectory planning of autonomous mobile robots, we focus on the imitation of human's obstacle avoidance ability. Based on a developed teleoperation system, human's adaptive operation data considering local and global information on complex environment can be obtained. In this paper, from the perspective of emphasizing knowledge usage, we propose a novel imitation approach on human's obstacle avoidance ability by using the distance-type fuzzy reasoning method with knowledge radius. Firstly, the fuzzy rules representing operator's obstacle avoidance ability are effectively obtained from operation data by means of the learning algorithm for distance-type fuzzy reasoning method; then the imitation of human's obstacle avoidance is achieved by combining effective knowledge radius in the reasoning process. Moreover, the properties of knowledge radius are summarized and will provide further guideline to the search of knowledge radius for specific problem. Finally, the effectiveness of proposed method is illuminated through any trial experiment