1.宁波大学 电气工程与自动化研究所 宁波 315211 2.华东理工大学 自动化研究所 上海 200237 3.School of Engineering, The University of Guelph, Guelph, Ontario, Canada N1G 2W1
Complete Coverage Path Planning of Mobile Robots: Biologically Inspired Neural Network and Heuristic Template Approach
QIU XueNa1, 2, LIU ShiRong1, YU JinShou2, Simon X. Yang3
1.Research Institute of Electrical Engineering and Automation, Ningbo University, Ningbo 315211 2.Research Institute of Automation, East China University of Science and Technology, Shanghai 200237 3.School of Engineering, The University of Guelph, Guelph, Ontario, Canada N1G 2W1
Abstract：In this paper, a novel complete coverage path planning method based on biologically inspired neural network for mobile robot motion planning is developed, which integrates heuristic searching algorithm, templatebased model and obstacle approaching algorithm. The biological neural network that is described by the shunting cooperativecompetitive feedback network is used to model the environment of the workspace of mobile robot. The templatebased model, heuristic searching algorithm and obstacle approaching algorithm are employed to plan the motion path of a mobile robot with obstacle avoidance. The obstacle approaching algorithm is used to cover the vicinity areas of the irregular obstacles so that the coverage area of the path planning is further improved. The simulation studies show that the performance of the path generated by the proposed method, such as the rate of the repeated coverage, is improved obviously, and the proposed algorithm is computationally simple and effective.
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2006, Vol. 19 
