J. J. Acevedo, Á. Castaño, J. L. Andrade-Pineda, A. Ollero
{"title":"A 4D grid based approach for efficient conflict detection in large-scale multi-UAV scenarios","authors":"J. J. Acevedo, Á. Castaño, J. L. Andrade-Pineda, A. Ollero","doi":"10.1109/REDUAS47371.2019.8999724","DOIUrl":null,"url":null,"abstract":"This paper proposes an algorithm to detect conflicts among UAVs from a strategic point of view. The method is based on the representation of the airspace as a 4D grid of cells. Given a set of UAVs with their scheduled 4D trajectories (their flight plans), the whole scenario is discretized as a 4D grid and the problem is solved by filling the appropriate cell for each way-point from the trajectories and checking the neighboring cells. The proposed method is tested and compared against a traditional algorithm getting a significantly better performance. The proposed method also scales very well with increasing number of UAVs and way-points per trajectory.","PeriodicalId":351115,"journal":{"name":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED UAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REDUAS47371.2019.8999724","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 proposes an algorithm to detect conflicts among UAVs from a strategic point of view. The method is based on the representation of the airspace as a 4D grid of cells. Given a set of UAVs with their scheduled 4D trajectories (their flight plans), the whole scenario is discretized as a 4D grid and the problem is solved by filling the appropriate cell for each way-point from the trajectories and checking the neighboring cells. The proposed method is tested and compared against a traditional algorithm getting a significantly better performance. The proposed method also scales very well with increasing number of UAVs and way-points per trajectory.