{"title":"Path planning for multi-vehicle autonomous swarms in dynamic environment","authors":"Mudassir Jann, S. Anavatti, Sumana Biswas","doi":"10.1109/ICACI.2017.7974484","DOIUrl":null,"url":null,"abstract":"This paper aims at investigating the dynamic path planning of a multi-agent autonomous swarm to execute a task of traversing a certain terrain with specified start and goal state. The area under consideration also includes a specified number of secondary goals/checkpoints to be explored/visited by at-least one vehicle of the swarm while avoiding the static and dynamic obstacles. The decision about the traversal to the checkpoints is made by the swarm itself, thus providing a decentralized control. D∗lite is employed for dynamic path planning. Numerical simulation results are presented to validate the path planning algorithm with different number of agents and obstacles.","PeriodicalId":260701,"journal":{"name":"2017 Ninth International Conference on Advanced Computational Intelligence (ICACI)","volume":"268 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Ninth International Conference on Advanced Computational Intelligence (ICACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACI.2017.7974484","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
This paper aims at investigating the dynamic path planning of a multi-agent autonomous swarm to execute a task of traversing a certain terrain with specified start and goal state. The area under consideration also includes a specified number of secondary goals/checkpoints to be explored/visited by at-least one vehicle of the swarm while avoiding the static and dynamic obstacles. The decision about the traversal to the checkpoints is made by the swarm itself, thus providing a decentralized control. D∗lite is employed for dynamic path planning. Numerical simulation results are presented to validate the path planning algorithm with different number of agents and obstacles.