Abstract
This paper investigates a human walking behavior-based mobile robot control system. The Intelligent Space (iSpace) is a distributed sensory system, which is the background infrastructure to observe human walking in a limited area. The observation of human walking behavior is applied to train fuzzy-neural networks (FNN). The trained FNNs are applied to approximate the obstacle avoidance behavior of human walking. The paper introduces the iSpace and the mobile agents, which are mobile robots, utilizing the intelligence of the iSpace. The observed and trained human walking behaviors are applied to control the mobile agent in a human-robot shared environment. Experimental results demonstrate the effectiveness of the FNN-based control system.
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