A Biologically Inspired Neural Network Approach to Real-Time Map Building and Path Planning

A Biologically Inspired Neural Network Approach to Real-Time Map Building and Path Planning

Simon X. Yang (University of Guelph, Canada)
Copyright: © 2003 |Pages: 18
DOI: 10.4018/978-1-59140-037-0.ch004
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Abstract

A novel biologically inspired neural network approach is proposed for real-time simultaneous map building and path planning with limited sensor information in a non-stationary environment. The dynamics of each neuron is characterized by a shunting equation with both excitatory and inhibitory connections. There are only local connections in the proposed neural network. The map of the environment is built during the real-time robot navigation with its sensor information that is limited to a short range. The real-time robot path is generated through the dynamic activity landscape of the neural network. The effectiveness and the efficiency are demonstrated by simulation studies.

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