@inproceedings{29ff70cd10b54cd7bcb4a31429a22244,
title = "An Improved Task Planning Method for Unmanned Swarms with Coupled Physical and Logical Constraints",
abstract = "Traditional task allocation methods for unmanned swarm systems ignore the effects of actual paths, resulting in estimation accuracy reduction.This paper formulates task planning problem by incorporating physical and logical constraints, and establishes an integrated framework of task allocation and path planning.Conflict-based search method is used to address path planning with physical constraints.A genetic algorithm is employed to solve multi-traveling salesman allocation problem.A bounded suboptimal optimization, a data dictionary, and an island model are introduced to accelerate the convergence speed of the genetic algorithm.The experiments verify that compared to the decoupled task planning methods, the proposed method improves task execution efficiency and remains adaptability to various complex spatial maps.",
keywords = "mission planning, optimization algorithm, task allocation, unmanned swarms",
author = "Xiubin Chen and Lei Zhang and Fang Xu and Weiran Yao",
note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 IEEE International Conference on Unmanned Systems, ICUS 2024 ; Conference date: 18-10-2024 Through 20-10-2024",
year = "2024",
doi = "10.1109/ICUS61736.2024.10840164",
language = "英语",
series = "Proceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1969--1974",
editor = "Rong Song",
booktitle = "Proceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024",
address = "美国",
}