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Dynamic Window with Virtual Goal (DW-VG): a New Reactive Obstacle Avoidance Approach Based on Motion Prediction

Published online by Cambridge University Press:  04 March 2019

Yu Xinyi ,
Zhu Yichen Open the ORCID record for Zhu Yichen [Opens in a new window] ,
Lu Liang  and
Ou Linlin
Yu Xinyi
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China. E-mails: [email protected], [email protected], [email protected]
Zhu Yichen
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China. E-mails: [email protected], [email protected], [email protected]
Lu Liang
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China. E-mails: [email protected], [email protected], [email protected]
Ou Linlin*
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Hangzhou 310023, China. E-mails: [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper proposes a dynamic window with virtual goal (DW-VG) method for local collision avoidance in dynamic environments. Firstly, the debounce filter and polynomial curve-fitting algorithm are combined to predict the trajectory of the obstacles with timestamps. Based on the motion prediction of the obstacles, the virtual goal is proposed to replace the real goal, so that the robot can escape from the concave trap and avoid the dynamic obstacles. According to the timestamps and virtual goal, the optimal linear and angular velocities are selected from the dynamic window, which drive the robot toward its real goal. The simulation and experimental results show that the DW-VG method can not only escape the local minima and avoid dynamic obstacles but also is applicable to the dense environment. Furthermore, the simulation results also verify that the DW-VG method drives the robot to reach its goal faster and safer than other reactive obstacle avoidance methods.

Keywords

Mobile robotsMotion predictionObstacle avoidanceDynamic windowReactive navigation
Type
Articles
Information
Robotica , Volume 37 , Issue 8 , August 2019 , pp. 1438 - 1456
Copyright
© Cambridge University Press 2019 

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