{"title":"Multi-target Cooperative Path Planning for Air-Sea Heterogeneous Unmanned System","authors":"Shaoxin Qin, Xingwang Yang, Wangcheng Zhang, Mingyang Sun, Xingyu Liu, Z. Zhen","doi":"10.1109/ISAS59543.2023.10164371","DOIUrl":null,"url":null,"abstract":"This paper focuses on the cooperative path planning of multi-target heterogeneous unmanned systems in air-sea. In the face of multiple targets, Unmanned Aerial Vehicles (UAV) flies fast, but its range and load capacity are limited; Unmanned Surface Vehicles (USV) has strong load capacity and long endurance, but its navigation speed is slow. This paper studies the path planning problem of the air-sea heterogeneous unmanned system composed of UAVs and USVs for a large range and multiple targets, taking the time for the unmanned system to complete this task as the optimization objective. Firstly, distinguish targets with ReConDensity-Ratio based clustering algorithm, and find appropriate refueling points for UAVs and USVs in each classification. Secondly, the Double-deck Travel Modified Particle Swarm Optimization algorithm (DT-MPSO) is used to plan the path of targets and find the shortest route. Finally, the effectiveness of the proposed method is verified by simulation experiments.","PeriodicalId":199115,"journal":{"name":"2023 6th International Symposium on Autonomous Systems (ISAS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 6th International Symposium on Autonomous Systems (ISAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAS59543.2023.10164371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper focuses on the cooperative path planning of multi-target heterogeneous unmanned systems in air-sea. In the face of multiple targets, Unmanned Aerial Vehicles (UAV) flies fast, but its range and load capacity are limited; Unmanned Surface Vehicles (USV) has strong load capacity and long endurance, but its navigation speed is slow. This paper studies the path planning problem of the air-sea heterogeneous unmanned system composed of UAVs and USVs for a large range and multiple targets, taking the time for the unmanned system to complete this task as the optimization objective. Firstly, distinguish targets with ReConDensity-Ratio based clustering algorithm, and find appropriate refueling points for UAVs and USVs in each classification. Secondly, the Double-deck Travel Modified Particle Swarm Optimization algorithm (DT-MPSO) is used to plan the path of targets and find the shortest route. Finally, the effectiveness of the proposed method is verified by simulation experiments.