@inproceedings{f29b0e283538445ca6653792c8a86e6c,
title = "Estimation of Mars rover slip based on GA-BP algorithm",
abstract = "China{\textquoteright}s first Mars rover Zhurong has successfully began its exploration on Mars surface. It is important to estimate the rover slip while driving on the Mars, for the slip has a negative impact on the navigation accuracy and passing safety. In this paper, we establish the slip estimation model by BP and GA-BP algorithm for Zhurong rover. Pitch and roll of the rover, average current and velocity of the wheel drive motors are selected as input features to train the model. All data are obtained by Zhurong validator{\textquoteright}s indoor slip experiment. The results demonstrate that genetic algorithm effectively optimizes the weights and thresholds of the BP network, so that GA-BP performs better than the BP neural network in rover slip estimation. The GA-BP model established in this paper has reference value for the slip estimation of Zhurong rover.",
keywords = "BP neural network, Genetic algorithm, Slip estimation",
author = "Tianyi Zhang and Song Peng and Yang Jia and He Tian and Chuliang Yan",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 6th International Conference on Automation, Control and Robotics Engineering, CACRE 2021 ; Conference date: 15-07-2021 Through 17-07-2021",
year = "2021",
doi = "10.1109/CACRE52464.2021.9501362",
language = "英语",
series = "Proceedings - 2021 6th International Conference on Automation, Control and Robotics Engineering, CACRE 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "280--284",
editor = "Fumin Zhang and Ying Zhao",
booktitle = "Proceedings - 2021 6th International Conference on Automation, Control and Robotics Engineering, CACRE 2021",
address = "美国",
}