{"title":"Path-planning for an unmanned aerial vehicle with energy constraint in a search and coverage mission","authors":"G. Gramajo, P. Shankar","doi":"10.1109/IGESC.2016.7790077","DOIUrl":null,"url":null,"abstract":"This paper describes the path planning algorithm for a search and coverage mission using a small UAV that optimizes the trajectory based on energy and maneuverability constraints. The proposed formulation has a high level of autonomy, without relying on the user to make the appropriate choice of optimization parameters. The computed trajectory maximizes spatial coverage while satisfying constraints such as the original flight plan of reaching a desired end state from the initial state for the initial available energy and the maneuverability limitations of the vehicle. Comparisons of this formulation to a path planning algorithm based on time constraint optimization show equivalent coverage performance but improvement in prediction of overall mission duration and terminal position of the vehicle.","PeriodicalId":231713,"journal":{"name":"2016 IEEE Green Energy and Systems Conference (IGSEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Green Energy and Systems Conference (IGSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IGESC.2016.7790077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper describes the path planning algorithm for a search and coverage mission using a small UAV that optimizes the trajectory based on energy and maneuverability constraints. The proposed formulation has a high level of autonomy, without relying on the user to make the appropriate choice of optimization parameters. The computed trajectory maximizes spatial coverage while satisfying constraints such as the original flight plan of reaching a desired end state from the initial state for the initial available energy and the maneuverability limitations of the vehicle. Comparisons of this formulation to a path planning algorithm based on time constraint optimization show equivalent coverage performance but improvement in prediction of overall mission duration and terminal position of the vehicle.