Lunar rover's behavior fusion learning based on nonholonomic dynamics

Haining Pan*, Pingyuan Cui, Hehua Ju

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The behavior-based motion planning with nonholonomic constrains for lunar rovers is discussed in this paper. For each fuzzy behavior controller, the hybrid coordinate scheme which combines competition with cooperation is proposed to ensure both the robustness and optimization. Force and torque of the wheels are chosen as the output of fuzzy behavior. The on-line Q-learning is used to obtain the behavior's coordinate scheme, ant its output is an optimal solution within a behavior decision set which is obtained according to the outputs from each behavior controller. Maggi equations are introduced to formulate the rover's transfer under the learnt controls. Experiment results demonstrate the effectiveness of this method and traceability of the trajectory.

Original languageEnglish
Title of host publicationIntelligent Robotics and Applications - First International Conference, ICIRA 2008, Proceedings
PublisherSpringer Verlag
Pages689-698
Number of pages10
EditionPART 1
ISBN (Print)3540885129, 9783540885122
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event1st International Conference on Intelligent Robotics and Applications, ICIRA 2008 - Wuhan, China
Duration: 15 Oct 200817 Oct 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5314 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Intelligent Robotics and Applications, ICIRA 2008
Country/TerritoryChina
CityWuhan
Period15/10/0817/10/08

Keywords

  • Behavior fusion
  • Lunar rover
  • Motion planning
  • Nonholonomic dynamics
  • Q-learning

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