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Multi-agent system motion planning under temporal logic specifications and control barrier function

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Abstract

In this paper, we provide a novel scheme to solve the motion planning problem of multi-agent systems under high-level task specifications. First, linear temporal logic is applied to express the global task specification. Then an efficient and decentralized algorithm is proposed to decompose it into local tasks. Moreover, we use control barrier function to synthesize the local controller for each agent under the linear temporal logic motion plan with safety constraint. Finally, simulation results show the effectiveness and efficiency of our proposed scheme.

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Authors and Affiliations

  1. College of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China

    Xinyuan Huang, Li Li & Jie Chen

  2. Shanghai Research Institute for Intelligent Autonomous Systems, Shanghai, 201210, China

    Xinyuan Huang, Li Li & Jie Chen

Authors
  1. Xinyuan Huang
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  2. Li Li
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  3. Jie Chen
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Corresponding author

Correspondence to Li Li.

Additional information

This work was partially supported by the National Natural Science Foundation of China (No. 51475334), the National Key Research and Development Program of Science and Technology of China (No.2018YFB1305304) and the Shanghai Science and Technology Pilot Project (No. 19511132100).

Xinyuan HUANG received the B.Sc. degree in Electronics and Information Engineering from Tongji University, China, in 2019. He is currently pursuing his Ph.D. degree at the Department of Control Science and Engineering, Tongji University. His research interests include multi-agent collaborative control and formal methods-based control.

Li LI received the B.Sc. and M.Sc. degrees from Shengyang Agriculture University, China in 1996 and 1999, respectively, and the Ph.D. degree from Shenyang Institute of Automation, Chinese Academy of Science, in 2003. She is currently a Professor at the Department of Control Science and Engineering, Tongji University. Her research interests are data-driven modeling & optimization and computational intelligence.

Jie CHEN received the B.Sc., M.Sc., Ph.D. degrees in Control Theory and Control Engineering from the Beijing Institute of Technology, Beijing, China, in 1986, 1996 and 2001, respectively. He was a Visiting Scholar with California State University, Long Beach, CA, U.S.A., from 1989 to 1990. From 1996 to 1997, he was a Research Fellow with the School of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham, U.K. He is currently a Professor at the Department of Control Science and Engineering, Tongji University, where he is also the Chief Scientist of Shanghai Research Institute for Intelligent Autonomous Systems. His current research interests include multiobjective optimization and decision in complex systems, intelligent control, nonlinear control, and optimization methods. Dr. Chen serves as a Managing Editor of the Journal of Systems Science and Complexity (2014-2017), and an Associate Editor for the IEEE Transactions on Cybernetics (2016-2018), as well as several other international journals. He is Fellow of IEEE and Fellow of IFAC

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Huang, X., Li, L. & Chen, J. Multi-agent system motion planning under temporal logic specifications and control barrier function. Control Theory Technol. 18, 269–278 (2020). https://doi.org/10.1007/s11768-020-0110-6

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  • DOI: https://doi.org/10.1007/s11768-020-0110-6

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