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A hybrid obstacle avoidance method for mobile robot navigation in unstructured environment

Huaidong Zhou (School of Mechanical Engineering and Automation, Beihang University, Beijing, China)
Pengbo Feng (Department of Robotics and Intelligent Manufacturing, Beihang Goer (Weifang) Intelligent Robot Co., Ltd, Weifang, China)
Wusheng Chou (School of Mechanical Engineering and Automation, Beihang University, Beijing, China)

Industrial Robot

ISSN: 0143-991x

Article publication date: 12 July 2022

Issue publication date: 2 January 2023




Wheeled mobile robots (WMR) are the most widely used robots. Avoiding obstacles in unstructured environments, especially dynamic obstacles such as pedestrians, is a serious challenge for WMR. This paper aims to present a hybrid obstacle avoidance method that combines an informed-rapidly exploring random tree* algorithm with a three-dimensional (3D)-object detection approach and model prediction controller (MPC) to conduct obstacle perception, collision-free path planning and obstacle avoidance for WMR in unstructured environments.


Given a reference orientation and speed, the hybrid method uses parametric ellipses to represent obstacle expansion boundaries based on the 3D target detection results, and a collision-free reference path is planned. Then, the authors build on a model predictive control for tracking the collision-free reference path by incorporating the distance between the robot and obstacles. The proposed framework is a mapless method for WMR.


The authors present experimental results with a mobile robot for obstacle avoidance in indoor environments crowded with obstacles, such as chairs and pedestrians. The results show that the proposed hybrid obstacle avoidance method can satisfy the application requirements of mobile robots in unstructured environments.


In this study, the parameter ellipse is used to represent the area occupied by the obstacle, which takes the velocity as the parameter. Therefore, the motion direction and position of dynamic obstacles can be considered in the planning stage, which enhances the success rate of obstacle avoidance. In addition, the distance between the obstacle and robot is increased in the MPC optimization function to ensure a safe distance between the robot and the obstacle.



This research was supported by the National Key Research and Development Program of China (grant no. 2019YFB1310802). The authors would also like to thank the anonymous reviewers and the academic editor for their comments and suggestions.


Zhou, H., Feng, P. and Chou, W. (2023), "A hybrid obstacle avoidance method for mobile robot navigation in unstructured environment", Industrial Robot, Vol. 50 No. 1, pp. 94-106.



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