Research on a New Path Planning Method for Mobile Robot

DOI

10.2991/eeic-13.2013.66How to use a DOI?

Keywords

hybrid learning; automata; fuzzy inference system; supervised learning; path planning

Abstract

Aim at the path planning problem of a mobile vehicle in an unknown environment, a new hybrid learning method is proposed, which is based on the fuzzy inference system and assisted by the combination of supervised learning and bionic automata, the bionic learning endows the robot the capabilities of self-learning and self-organization, the supervised learning is used to tune the input membership function of the fuzzy inference system, that avoid the expert knowledge’s disadvantage of inaccurate estimation to the actual model. The simulation results show that the robot has learned the ability of obstacle avoidance and goal seeking and performs a better robustness in overcoming the local minima.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - XiaoPing Zhang
AU  - Xiaogang Ruan
AU  - Xiaoqing Zhu
AU  - Jing Huang
PY  - 2013/12
DA  - 2013/12
TI  - Research on a New Path Planning Method for Mobile Robot
BT  - Proceedings of the 3rd International Conference on Electric and Electronics
PB  - Atlantis Press
SP  - 283
EP  - 288
SN  - 1951-6851
UR  - https://doi.org/10.2991/eeic-13.2013.66
DO  - 10.2991/eeic-13.2013.66
ID  - Zhang2013/12
ER  -