Title: | Environment prediction for a mobile robot in a dynamic environment |
Authors: | Chang, CC Song, KT 電控工程研究所 Institute of Electrical and Control Engineering |
Keywords: | artificial neural networks;environment prediction;mobile robots;moving obstacles;training algorithm |
Issue Date: | 1-Dec-1997 |
Abstract: | The problem of navigating a mobile robot among moving obstacles is usually solved on the condition of knowing the velocity of obstacles. However, it is difficult to provide such information to a robot in real time. In this paper, we present an environment predictor that provides an estimate of future environment configuration by fusing multisensor data in real time. The predictor is implemented by an artificial neural network (ANN) trained using a relative-error-backpropagation (REBP) algorithm. The REBP algorithm enables the ANN to provide output data with a minimum relative error, which is better than conventional backpropagation (BP) algorithms in this prediction application. The mobile robot can, therefore, respond to anticipated changes in the environment. The performance is verified by prediction simulation and navigation experiments. |
URI: | http://dx.doi.org/10.1109/70.650165 http://hdl.handle.net/11536/177 |
ISSN: | 1042-296X |
DOI: | 10.1109/70.650165 |
Journal: | IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION |
Volume: | 13 |
Issue: | 6 |
Begin Page: | 862 |
End Page: | 872 |
Appears in Collections: | Articles |
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