@inproceedings{e4f6909afe1d4f32ad6ccef65fde9472,
title = "Motion planning for lunar rover based on behavior decision field Q-learning",
abstract = "Autonomous behavior motion planning with kinematics constrains is improved for lunar rovers. The behavior controller is implemented by fuzzy system, and the hybrid architecture is adopted to ensure both the robustness and optimization. Velocity and turning radius are chosen as the output of fuzzy behavior to decouple the velocity and angle velocity. Behavior decision field (BDF) is presented, and kinematics constrains are re-written as the reward functions within the Q-learning process. This bottom-to-top design ensures motion planning the kinematics quality in BDF. Experiment results are shown to demonstrate the effectiveness and traceability of the trajectory.",
keywords = "BDF, Behavior derivative, Lunar rover, Motion planning, Q-learning",
author = "Haining Pan and Ye Yuan and Hehua Ju and Pingyuan Cui",
year = "2008",
doi = "10.1109/WCICA.2008.4593202",
language = "English",
isbn = "9781424421145",
series = "Proceedings of the World Congress on Intelligent Control and Automation (WCICA)",
pages = "1834--1839",
booktitle = "Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08",
note = "7th World Congress on Intelligent Control and Automation, WCICA'08 ; Conference date: 25-06-2008 Through 27-06-2008",
}