TY - GEN
T1 - Local Path Planning Algorithm for UGV Based on Improved Covariance Matrix Adaptive Evolution Strategy
AU - Zhao, Jiangbo
AU - Zhang, Jiaquan
AU - Wang, Junzheng
AU - Zhang, Xin
AU - Wang, Yanlong
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Local path planning algorithm is one of the key technologies for unmanned ground vehicle(UGV). In order to reduce the computational complexity of the local path planning algorithm and ensure the real-time performance of the algorithm, a non-uniform column grid lines modeling method is introduced, and on this basis, a modeling method for planning paths is proposed. Aiming at the path planning problem in a multi -obstacle environment, the evaluation function of the path is constructed from four aspects, and the covariance matrix adaptive evolution strategy(CMA-ES) is used to solve the nonlinear optimization problem. In order to further reduce the amount of calculation, the CMA-ES algorithm is improved by the dynamic adjustment strategy of population size. Experiment results show that the path planning algorithm can effectively realize the local path planning in complex environment.
AB - Local path planning algorithm is one of the key technologies for unmanned ground vehicle(UGV). In order to reduce the computational complexity of the local path planning algorithm and ensure the real-time performance of the algorithm, a non-uniform column grid lines modeling method is introduced, and on this basis, a modeling method for planning paths is proposed. Aiming at the path planning problem in a multi -obstacle environment, the evaluation function of the path is constructed from four aspects, and the covariance matrix adaptive evolution strategy(CMA-ES) is used to solve the nonlinear optimization problem. In order to further reduce the amount of calculation, the CMA-ES algorithm is improved by the dynamic adjustment strategy of population size. Experiment results show that the path planning algorithm can effectively realize the local path planning in complex environment.
KW - CMA-ES
KW - Local path planning
KW - Unmanned ground vehicle
UR - http://www.scopus.com/inward/record.url?scp=85125202474&partnerID=8YFLogxK
U2 - 10.1109/CCDC52312.2021.9601399
DO - 10.1109/CCDC52312.2021.9601399
M3 - Conference contribution
AN - SCOPUS:85125202474
T3 - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
SP - 1085
EP - 1091
BT - Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 33rd Chinese Control and Decision Conference, CCDC 2021
Y2 - 22 May 2021 through 24 May 2021
ER -