Automatic Navigation for Rat-Robots with Modeling of the Human Guidance  

作　　者：Chao Sun Nenggan Zheng Xinlu Zhang Weidong Chen Xiaoxiang Zheng 

机构地区：[1]Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou 310027, P. R. China [2]College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, P. R. China [3]Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, P. R. China

出　　处：《Journal of Bionic Engineering》2013年第1期46-56,共11页仿生工程学报（英文版）

基　　金：the National Key Basic Research Program of China，the National Natural Science Foundation of China，the National High Technology Research and Development Program of China，the National Natural Science Foundation of China，the Fundamental Research Funds for the Central Universities

摘　　要：A bio-robot system refers to an animal equipped with Brain-Computer Interface （BCI）, through which the outer stimulation is delivered directly into the animal＇s brain to control its behaviors. The development ofbio-robots suffers from the dependency on real-time guidance by human operators. Because of its inherent difficulties, there is no feasible method for automatic con- trolling of bio-robots yet. In this paper, we propose a new method to realize the automatic navigation for bio-robots. A General Regression Neural Network （GRNN） is adopted to analyze and model the controlling procedure of human operations. Com- paring to the traditional approaches with explicit controlling rules, our algorithm learns the controlling process and imitates the decision-making of human-beings to steer the rat-robot automatically. In real-time navigation experiments, our method suc- cessfully controls bio-robots to follow given paths automatically and precisely. This work would be significant for future ap- plications of bio-robots and provide a new way to realize hybrid intelligent systems with artificial intelligence and natural biological intelligence combined together.A bio-robot system refers to an animal equipped with Brain-Computer Interface （BCI）, through which the outer stimulation is delivered directly into the animal＇s brain to control its behaviors. The development ofbio-robots suffers from the dependency on real-time guidance by human operators. Because of its inherent difficulties, there is no feasible method for automatic con- trolling of bio-robots yet. In this paper, we propose a new method to realize the automatic navigation for bio-robots. A General Regression Neural Network （GRNN） is adopted to analyze and model the controlling procedure of human operations. Com- paring to the traditional approaches with explicit controlling rules, our algorithm learns the controlling process and imitates the decision-making of human-beings to steer the rat-robot automatically. In real-time navigation experiments, our method suc- cessfully controls bio-robots to follow given paths automatically and precisely. This work would be significant for future ap- plications of bio-robots and provide a new way to realize hybrid intelligent systems with artificial intelligence and natural biological intelligence combined together.

关 键 词：BIO-ROBOT rat-robots brain-computer interface automatic navigation 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP311[自动化与计算机技术—控制科学与工程]