Behavior-based intelligent mobile robot using an immunized reinforcement adaptive learning mechanism |
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| Affiliation: | 1. School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China;2. Department of Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI 02881, USA;3. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;1. School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China;2. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China;3. The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China |
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| Abstract: | In this paper, a novel immunized reinforcement adaptive learning mechanism employing a behavior-based knowledge and the on-line adapting capabilities of the immune system is proposed and applied to an intelligent mobile robot. Rather than building a detailed mathematical model of immune systems, we try to explore principles in the immune system focusing on its self-organization, adaptive capability and immune memory. Two levels of the immune system, underlying the ‘micro’ level of cell interactions, and emergent ‘macro’ level of the behavior of the system are investigated.To evaluate the proposed immunized architecture, a ‘food foraging work’ simulation environment containing a mobile robot, foods, with/without obstacles is created to simulate the real world. The simulation results validate several significant characteristics of the immunized architecture: adaptability, learning, self-organizing, and stable ecological niche approaching. |
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