Acquisition of a destination path accompanied by obstacle avoiding actions for quadruped robots using neural network

Tomohiro Yamaguchi, Keigo Watanabe, Kiyotaka Izumi, Kazuo Kiguchi

Research output: Contribution to journalArticle

Abstract

In the obstacle avoidance of a legged type robot, it is not necessary to avoid all of obstacles by only turning, because it can get over or stride some of them, depending on the obstacle configuration and the state of the robot, unlike a wheel type or a crawler type robot. It is thought that the mobility efficiency to the destination is improved by getting-over or striding. In this paper, a neural network (NN) is used to determine the action of a quadruped robot in the obstacle avoidance path by using information on the destination, the obstacle configuration, and the robot's self-state. The design parameters of NN are adjusted by genetic algorithm (GA) offline. The effectiveness of the present method is proved through an actual experiment.

Original languageEnglish
Pages (from-to)2880-2887
Number of pages8
JournalNihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C
Volume69
Issue number11
Publication statusPublished - Nov 2003
Externally publishedYes

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Robots
Neural networks
Collision avoidance
Wheels
Genetic algorithms
Experiments

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

Cite this

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