11 March 1993 Polynomial-neural-network-based mobile robot path planning
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Abstract
A polynomial-neural-network-based (PNN-based) path planning with an obstacle avoidance scheme is proposed for mobile robot navigation. The PNN is a feature-based mapping neural network which can be successfully trained to interpolate an unknown function by observing few samples. In this work, a very useful method of data analysis technique called the group method of data handling (GMDH) is used to build the PNN. The built PNNs are used for the path planning of a sonar sensor guided mobile robot. The major advantage of using the PNNs is to efficiently use the environment data and to reduce the computational complexity. Also, in this approach, no preprocessing of range data is required.
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C. L. Philip Chen, C. L. Philip Chen, Farid Ahmed, Farid Ahmed, "Polynomial-neural-network-based mobile robot path planning", Proc. SPIE 1964, Applications of Artificial Intelligence 1993: Machine Vision and Robotics, (11 March 1993); doi: 10.1117/12.141780; https://doi.org/10.1117/12.141780
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