Roger Datouo, F. B. Motto, B. E. Zobo, A. Melingui, Ismail Bensekrane, R. Merzouki
{"title":"Optimal motion planning for minimizing energy consumption of wheeled mobile robots","authors":"Roger Datouo, F. B. Motto, B. E. Zobo, A. Melingui, Ismail Bensekrane, R. Merzouki","doi":"10.1109/ROBIO.2017.8324742","DOIUrl":null,"url":null,"abstract":"This paper presents a novel approach of finding energy-efficient trajectories for mobile robots. The approach integrates new cost and heuristic functions into the conventional A∗ algorithm while considering ground conditions and obstacle positions. The resulting planner helps to manage obstacle avoidance and to choose intelligent displacements of the robot. A heuristic function with energy-related criterion is defined in order to generate energy-efficient paths. Splines continuity property is exploited to generate smoothed energy-paths. The optimal velocity profile for minimum travel time is found by solving Sequential Quadratic Problem. A series of simulations demonstrate the energy saving efficiency of the proposed method.","PeriodicalId":197159,"journal":{"name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"404 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO.2017.8324742","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
This paper presents a novel approach of finding energy-efficient trajectories for mobile robots. The approach integrates new cost and heuristic functions into the conventional A∗ algorithm while considering ground conditions and obstacle positions. The resulting planner helps to manage obstacle avoidance and to choose intelligent displacements of the robot. A heuristic function with energy-related criterion is defined in order to generate energy-efficient paths. Splines continuity property is exploited to generate smoothed energy-paths. The optimal velocity profile for minimum travel time is found by solving Sequential Quadratic Problem. A series of simulations demonstrate the energy saving efficiency of the proposed method.