Iori Kumagai, M. Morisawa, Shin'ichiro Nakaoka, F. Kanehiro
{"title":"基于足部和质心摆动的仿人机器人全身避碰高效运动规划","authors":"Iori Kumagai, M. Morisawa, Shin'ichiro Nakaoka, F. Kanehiro","doi":"10.1109/HUMANOIDS.2018.8624927","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a locomotion planning framework for a humanoid robot with an efficient footstep and whole-body collision avoidance planning, which enables the robot to traverse an unknown narrow space while utilizing its body structure like a human. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by executing global footstep planning first, which has a much smaller search space, and then performing a sequential whole-body posture planning while utilizing the resulting footsteps and a centroidal trajectory as a guide. In the global footstep planning phase, we modify bounding box of the robot based on the centroidal sway motion. This idea enables the planner to obtain appropriate footsteps for next whole-body motion planning. Then, we execute sequential whole-body collision avoidance motion planning by prioritized inverse kinematics based on the resulting footsteps and centroidal trajectory, which enables the robot to plan whole-body collision avoidance motion for each step within less than 100ms at worst. The major contribution of our paper is solving the problem of the increasing computational cost for whole-body motion planning and enabling a humanoid robot to execute adaptive locomotion planning on the spot in an unknown narrow space.","PeriodicalId":433345,"journal":{"name":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Efficient Locomotion Planning for a Humanoid Robot with Whole-Body Collision Avoidance Guided by Footsteps and Centroidal Sway Motion\",\"authors\":\"Iori Kumagai, M. Morisawa, Shin'ichiro Nakaoka, F. Kanehiro\",\"doi\":\"10.1109/HUMANOIDS.2018.8624927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a locomotion planning framework for a humanoid robot with an efficient footstep and whole-body collision avoidance planning, which enables the robot to traverse an unknown narrow space while utilizing its body structure like a human. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by executing global footstep planning first, which has a much smaller search space, and then performing a sequential whole-body posture planning while utilizing the resulting footsteps and a centroidal trajectory as a guide. In the global footstep planning phase, we modify bounding box of the robot based on the centroidal sway motion. This idea enables the planner to obtain appropriate footsteps for next whole-body motion planning. Then, we execute sequential whole-body collision avoidance motion planning by prioritized inverse kinematics based on the resulting footsteps and centroidal trajectory, which enables the robot to plan whole-body collision avoidance motion for each step within less than 100ms at worst. The major contribution of our paper is solving the problem of the increasing computational cost for whole-body motion planning and enabling a humanoid robot to execute adaptive locomotion planning on the spot in an unknown narrow space.\",\"PeriodicalId\":433345,\"journal\":{\"name\":\"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HUMANOIDS.2018.8624927\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HUMANOIDS.2018.8624927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient Locomotion Planning for a Humanoid Robot with Whole-Body Collision Avoidance Guided by Footsteps and Centroidal Sway Motion
In this paper, we propose a locomotion planning framework for a humanoid robot with an efficient footstep and whole-body collision avoidance planning, which enables the robot to traverse an unknown narrow space while utilizing its body structure like a human. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by executing global footstep planning first, which has a much smaller search space, and then performing a sequential whole-body posture planning while utilizing the resulting footsteps and a centroidal trajectory as a guide. In the global footstep planning phase, we modify bounding box of the robot based on the centroidal sway motion. This idea enables the planner to obtain appropriate footsteps for next whole-body motion planning. Then, we execute sequential whole-body collision avoidance motion planning by prioritized inverse kinematics based on the resulting footsteps and centroidal trajectory, which enables the robot to plan whole-body collision avoidance motion for each step within less than 100ms at worst. The major contribution of our paper is solving the problem of the increasing computational cost for whole-body motion planning and enabling a humanoid robot to execute adaptive locomotion planning on the spot in an unknown narrow space.