Action Selection for Single- and Multi-Robot Tasks Using Cooperative Extended Kohonen Maps

Abstract

This paper presents an action selection framework based on an assemblage of self-organizing neural networks called Cooperative Extended Kohonen Maps. This framework encapsulates two features that significantly enhance a robot’s action selection capability: self-organization in the continuous state and action spaces to provide smooth, efficient and fine motion control; action selection via the cooperation and competition of Extended Kohonen Maps to achieve more complex motion tasks. Qualitative and quantitative comparisons for singleand multirobot tasks show our framework can provide better action selection than do potential fields method.

Extracted Key Phrases

2 Figures and Tables

Cite this paper

@inproceedings{Low2003ActionSF, title={Action Selection for Single- and Multi-Robot Tasks Using Cooperative Extended Kohonen Maps}, author={Kian Hsiang Low and Wee Kheng Leow and Marcelo H. Ang}, booktitle={IJCAI}, year={2003} }