Self-growing network based extraction of feasible motion region´s knowledge

Environmental map cognition includes two issues on the map knowledge extraction and comprehension. For the environmental comprehension of intelligent robot, an extraction method of the feasible motion area for mobile robot is proposed based on a self-growing network. Using the growth characteristics of Growing Neural Gas (GNG) algorithm, this method can abstracts the holistic knowledge of the surrounding environment by adding new node of topology network and builds an environmental map in which robot can easily understand, autonomously plan and make a strategic decision. The simulations and physical experiments verify the feasibility and effectiveness of the proposed method.