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Path Planning of UGV Based on Bézier Curves

Published online by Cambridge University Press:  21 January 2019

Yanming Hu
Affiliation:
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China University of Chinese Academy of Sciences, Beijing 100049, China
Decai Li
Affiliation:
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
Yuqing He*
Affiliation:
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
Jianda Han
Affiliation:
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China College of Artificial Intelligence, Nankai University, Tianjing 300071, China E-mails: huyanming@sia.cn, lidecai@sia.cn, jdhan@sia.cn
*
*Corresponding author. E-mail: heyuqing@sia.cn

Summary

An effective path planner is critical for autonomous traversal of unmanned ground vehicles (UGVs) in harsh environments. This paper describes a novel path planning method considering Bézier curves and a two-layer planning framework. In the two-layer framework, a road centerline (RCL) estimator located on the upper layer works as a global planner to obtain the local target for the bottom local planner. The RCL is estimated from a series of candidate Bézier curves based on a safety criterion. In the bottom layer, an optimal trajectory planner and a speed planner make up the local planner to obtain the desired steering turning angle and linear speed. The criteria for optimal trajectory selection are designed for comfortable driving. Road safety is considered in the speed planner for robust driving. Three sets of simulations are used to evaluate and quantify the relative performance of variations of our path planning algorithm. The proposed path planning method is implemented on a modified Polaris RZR 800 UGV, too. Two experiments based on this UGV are set up in the country road environment to demonstrate the viability of the proposed method.

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Articles
Copyright
Copyright © Cambridge University Press 2019 

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