{"title":"Socially-Driven Collective Path Planning for Robot Missions","authors":"J. A. G. Higuera, Anqi Xu, F. Shkurti, G. Dudek","doi":"10.1109/CRV.2012.62","DOIUrl":null,"url":null,"abstract":"We address the problem of path planning for robot missions based on waypoints suggested by multiple human users. These users may be operating under distinct mission objectives and hence suggest different locations for the robot to visit. We formulate this problem using a constrained optimization approach by imposing various operational considerations, such as the robot's maximum traversable distance. We then propose an approximative path planning algorithm with parameterized control over the degree of \"social fairness\" in the selection of waypoints from different users. Through a user study, we compared the performance of the proposed path planner under different fairness settings and for different mission scenarios.","PeriodicalId":372951,"journal":{"name":"2012 Ninth Conference on Computer and Robot Vision","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Ninth Conference on Computer and Robot Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2012.62","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
We address the problem of path planning for robot missions based on waypoints suggested by multiple human users. These users may be operating under distinct mission objectives and hence suggest different locations for the robot to visit. We formulate this problem using a constrained optimization approach by imposing various operational considerations, such as the robot's maximum traversable distance. We then propose an approximative path planning algorithm with parameterized control over the degree of "social fairness" in the selection of waypoints from different users. Through a user study, we compared the performance of the proposed path planner under different fairness settings and for different mission scenarios.