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An autonomous navigation approach for unmanned vehicle in outdoor unstructured terrain with dynamic and negative obstacles

Published online by Cambridge University Press:  27 January 2022

Bo Zhou Open the ORCID record for Bo Zhou [Opens in a new window] ,
Jianjun Yi ,
Xinke Zhang ,
Liwei Chen ,
Ding Yang ,
Fei Han  and
Hanmo Zhang
Bo Zhou
Affiliation:
School of Mechanical and Power Engineering, East China University of Science and Technology, Xuhui District, Shanghai 200237, China
Jianjun Yi*
Affiliation:
School of Mechanical and Power Engineering, East China University of Science and Technology, Xuhui District, Shanghai 200237, China
Xinke Zhang
Affiliation:
School of Mechanical and Power Engineering, East China University of Science and Technology, Xuhui District, Shanghai 200237, China
Liwei Chen
Affiliation:
School of Mechanical and Power Engineering, East China University of Science and Technology, Xuhui District, Shanghai 200237, China
Ding Yang
Affiliation:
School of Mechanical and Power Engineering, East China University of Science and Technology, Xuhui District, Shanghai 200237, China
Fei Han
Affiliation:
Shanghai Key Laboratory of Aerospace Intelligent Control Technology, Shanghai 201109, China Shanghai Aerospace Control Technology Institute, Shanghai 201109, China
Hanmo Zhang
Affiliation:
Shanghai Key Laboratory of Aerospace Intelligent Control Technology, Shanghai 201109, China Shanghai Aerospace Control Technology Institute, Shanghai 201109, China
*
*Corresponding author. E-mail: jjyi@ecust.edu.cn
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Abstract

At present, the study on autonomous unmanned ground vehicle navigation in an unstructured environment is still facing great challenges and is of great significance in scenarios where search and rescue robots, planetary exploration robots, and agricultural robots are needed. In this paper, we proposed an autonomous navigation method for unstructured environments based on terrain constraints. Efficient path search and trajectory optimization on octree map are proposed to generate trajectories, which can effectively avoid various obstacles in off-road environments, such as dynamic obstacles and negative obstacles, to reach the specified destination. We have conducted empirical experiments in both simulated and real environments, and the results show that our approach achieved superior performance in dynamic obstacle avoidance tasks and mapless navigation tasks compared to the traditional 2-dimensional or 2.5-dimensional navigation methods.

Keywords

unstructured terrainnegative obstaclesunmanned vehiclestrajectory optimization
Type
Research Article
Information
Robotica , Volume 40 , Issue 8 , August 2022 , pp. 2831 - 2854
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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