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Optimal Path Planning Satisfying Complex Task Requirement in Uncertain Environment

Published online by Cambridge University Press:  08 April 2019

Xin-Yi Yu ,
Zhen-Yong Fan ,
Lin-Lin Ou ,
Feng Zhu  and
Yong-Kui Guo
Xin-Yi Yu
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Zhejiang Province, Hangzhou, China E-mails: [email protected], [email protected], [email protected], [email protected]
Zhen-Yong Fan
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Zhejiang Province, Hangzhou, China E-mails: [email protected], [email protected], [email protected], [email protected]
Lin-Lin Ou*
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Zhejiang Province, Hangzhou, China E-mails: [email protected], [email protected], [email protected], [email protected]
Feng Zhu
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Zhejiang Province, Hangzhou, China E-mails: [email protected], [email protected], [email protected], [email protected]
Yong-Kui Guo
Affiliation:
Department of Automation, College of Information Engineering, Zhejiang University of Technology, Zhejiang Province, Hangzhou, China E-mails: [email protected], [email protected], [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

Robots often need to accomplish some complex tasks such as surveillance, response and obstacle avoidance. In this paper, a dynamic search method is proposed to generate optimal robot trajectories satisfying complex task requirement in uncertain environment. The LTL-A* algorithm is presented to generate a global optimal path and the A* algorithm is provided to modify the global optimal path. The task is specified by a linear temporal logic (LTL) formula, and a weighted transition system according to the known information in uncertain environment is modeled to describe the robot motion. Subsequently, a product automaton is constructed by combining the transition system with the task requirement. Based on the product automaton, the LTL-A* algorithm is proposed to generate a global optimal path. The local path planning based on the A* algorithm is employed to deal with the environment change during the process of tracking the global optimal path for the robot. The results of the simulation and experiments show that the proposed method can not only meet the complex task requirement in uncertain environment but also improve the search efficiency.

Keywords

Path planningComplex tasksLTLA* algorithmUncertain environment
Type
Articles
Information
Robotica , Volume 37 , Issue 11 , November 2019 , pp. 1956 - 1970
Copyright
© Cambridge University Press 2019 

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