{"title":"Obstacle avoidance for a power line inspection robot","authors":"Tim Rowell, E. Boje","doi":"10.1109/CARPI.2012.6473377","DOIUrl":null,"url":null,"abstract":"This paper presents an obstacle avoidance solution for an existing power line inspection robot (PLIR) prototype. The PLIR's workspace environment is represented by a discretised 3D map, which is used for obstacle avoidance manoeuvre planning for both known and unknown obstacles. Obstacles are represented in this workspace using a union of axis aligned bounding boxes. The Lazy Theta* algorithm is then used to find the shortest 3D graph path around the obstacle. The resulting path nodes are used to generate a B-spline trajectory. The trajectory is simulated to check for collisions and, if collision free, is used to command the actual robot. Experimental results show that this obstacle avoidance strategy is successful, with the prototype robot being able to manoeuvre around an obstacle in laboratory tests.","PeriodicalId":393732,"journal":{"name":"2012 2nd International Conference on Applied Robotics for the Power Industry (CARPI)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 2nd International Conference on Applied Robotics for the Power Industry (CARPI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CARPI.2012.6473377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
This paper presents an obstacle avoidance solution for an existing power line inspection robot (PLIR) prototype. The PLIR's workspace environment is represented by a discretised 3D map, which is used for obstacle avoidance manoeuvre planning for both known and unknown obstacles. Obstacles are represented in this workspace using a union of axis aligned bounding boxes. The Lazy Theta* algorithm is then used to find the shortest 3D graph path around the obstacle. The resulting path nodes are used to generate a B-spline trajectory. The trajectory is simulated to check for collisions and, if collision free, is used to command the actual robot. Experimental results show that this obstacle avoidance strategy is successful, with the prototype robot being able to manoeuvre around an obstacle in laboratory tests.