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Multi-UAV path planning based on IB-ABC with restricted planned arrival sequence

Published online by Cambridge University Press:  12 December 2022

Li Tan ,
Jiaqi Shi Open the ORCID record for Jiaqi Shi [Opens in a new window] ,
Jing Gao ,
Haoyu Wang ,
Hongtao Zhang  and
Yu Zhang
Li Tan
Affiliation:
School of Computer Science and Engineering, Beijing Technology and Business University, Beijing 100048, China
Jiaqi Shi
Affiliation:
School of Computer Science and Engineering, Beijing Technology and Business University, Beijing 100048, China
Jing Gao*
Affiliation:
School of Computer Science and Engineering, Beijing Technology and Business University, Beijing 100048, China
Haoyu Wang
Affiliation:
School of Computer Science and Engineering, Beijing Technology and Business University, Beijing 100048, China
Hongtao Zhang
Affiliation:
School of Computer Science and Engineering, Beijing Technology and Business University, Beijing 100048, China
Yu Zhang
Affiliation:
School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
*
*Corresponding author. E-mail: gaojing@btbu.edu.cn
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Abstract

Path planning is a key research issue in the field of unmanned aerial vehicle (UAV) applications. In practical applications, multi-objective path planning is usually required for multi-UAVs, so this paper proposes the improved balanced artificial bee colony (IB-ABC) algorithm to optimize multi-objective path planning. The algorithm adopts the ABC algorithm that emphasizes the global search capability, which is based on iterative feedback information. It uses single-element points, multi-element points, and iteration constraints to optimize the strategies of employed bees, follower bees, and scout bees, respectively. In terms of time and priority, simulation experiments prove that the IB-ABC algorithm can balance local and global search capabilities, accelerate the speed of convergence, and realize multi-UAV path planning in complex mountain environments.

Keywords

ABC algorithmmulti-UAV path planningfeedbackelement point controlbalance strategy
Type
Research Article
Information
Robotica , Volume 41 , Issue 4 , April 2023 , pp. 1244 - 1257
Copyright
© Beijing Technology and Business University, 2022. Published by Cambridge University Press

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