Autonomous cognitive of the environment map based on Growing Neural Gas in unknown environment

Environmental map cognition is composed of two aspects of map information acquision and comprehension. From the intelligent robot´s own demands for environmental cognition, a map cognitive model is proposed based on the Mental Model Imprinting (MMI) framework. Using the growth characteristics of Growing Neural Gas (GNG) algorithm, this model abstracts the holistic knowledge of the surrounding environment by adding new node of topology network and builds an environmental map which robot can understand easily. This cognitive model is asynchronous, self-learning and adaptive. Simulation results show the feasibility and effectiveness of the proposed method.