Y. Sugahara, K. Hashimoto, M. Kawase, T. Sawato, A. Hayashi, N. Endo, A. Ohta, C. Tanaka, Hun-ok Lim, A. Takanishi
{"title":"Walking Pattern Generation of a Biped Walking Vehicle Using a Dynamic Human Model","authors":"Y. Sugahara, K. Hashimoto, M. Kawase, T. Sawato, A. Hayashi, N. Endo, A. Ohta, C. Tanaka, Hun-ok Lim, A. Takanishi","doi":"10.1109/IROS.2006.281695","DOIUrl":null,"url":null,"abstract":"This paper describes a passive dynamic model of passenger for a biped walking vehicle. The walking pattern generation that enables stable walking even if passenger sits naturally is also described. The model consists of lower-limbs part assumed to be fixed to the robot, and the upper body assumed to be 1 particle with 2 DOF mounted on the seat via 2 springs and dampers. The parameters are identified through waist shaking experiments by using a force-torque sensor under the seat. The walking pattern generation method involves the proposed model being built onto a strict model of the robot, and through iteration computation, a stable walking pattern is generated. The effectiveness of the proposed method is confirmed through experiments","PeriodicalId":237562,"journal":{"name":"2006 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE/RSJ International Conference on Intelligent Robots and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.2006.281695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
This paper describes a passive dynamic model of passenger for a biped walking vehicle. The walking pattern generation that enables stable walking even if passenger sits naturally is also described. The model consists of lower-limbs part assumed to be fixed to the robot, and the upper body assumed to be 1 particle with 2 DOF mounted on the seat via 2 springs and dampers. The parameters are identified through waist shaking experiments by using a force-torque sensor under the seat. The walking pattern generation method involves the proposed model being built onto a strict model of the robot, and through iteration computation, a stable walking pattern is generated. The effectiveness of the proposed method is confirmed through experiments