Special Issue: Artificial Intelligence and Pattern Recognition

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Situated Learning of a Behavior-Based Mobile Robot Path Planner

Yao Shu; Zhang Bo;   

  1. Department of Computer Science and Technology; Tsinghua UnivereityBeijing 100084;
  • Online:1995-07-10 Published:1995-07-10

In this paper, we propose a behaviorbased path planner that can self learn in anunknown environment. A situated learning algorithm is designed which allows therobot to learn to coordinate several concurrent behaviors and improve its performanceby interacting with the environmellt. Behaviors are implemented using CMAC neuralnetworks. A simulation environment is set up and some simulation experiments arecarried out to rest our learning algorithm.

Key words: CSCW; Cova; transaction model; service integration; XML;



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CN 11-2296/TP

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