Using air–ground cooperation to perform tasks, such as detection and search on specific areas, is an essential means to accomplish special tasks. Research on the scheduling and matching of heterogeneous agents for intelligent tasks to meet special task requirements under the condition of satisfying multifaceted party requirements is a popular research topic in the field of task assignment using multiple agents. To overcome the shortcoming of traditional task assignment which only has a single matching dimension and does not consider task conflicts, this paper proposes a novel NSGA-III-based multi-objective task assignment algorithm for heterogeneous agents, namely heterogeneous conflict resolution multitasking optimization (HCRMO), to address the traditional task assignment process. The algorithm comprises a conflict-free minimum solution space and a task-agent conflict resolution module (TCCRM). The algorithm can build a search gene pool to meet the requirements, construct a solution space for each task, and quantify the potential conflict indicators of the task simultaneously to weaken the impact of agent conflicts due to variant search. Finally, the feasibility and effectiveness of the algorithm are verified through simulation.


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    Title :

    Multi-objective Collaborative Optimization Algorithm for Heterogeneous Cooperative Tasks Based on Conflict Resolution


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wu, Meiping (editor) / Niu, Yifeng (editor) / Gu, Mancang (editor) / Cheng, Jin (editor) / Zhang, Xuejun (author) / Liu, Hao (author) / Xue, Lele (author) / Li, Xiangmin (author) / Guo, Wei (author) / Yu, Shuangjiang (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Publication date :

    2022-03-18


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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