標題: Environment prediction for a mobile robot in a dynamic environment
作者: Chang, CC
Song, KT
電控工程研究所
Institute of Electrical and Control Engineering
關鍵字: artificial neural networks;environment prediction;mobile robots;moving obstacles;training algorithm
公開日期: 1-十二月-1997
摘要: 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
期刊: IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION
Volume: 13
Issue: 6
起始頁: 862
結束頁: 872
顯示於類別:期刊論文


文件中的檔案:

  1. 000071064200008.pdf