{"title":"On-line trajectory planning for autonomous robotic excavation based on force/torque sensor measurements","authors":"Fei-Yue Wang, P. Lever","doi":"10.1109/MFI.1994.398430","DOIUrl":null,"url":null,"abstract":"This paper describes the authors' initial investigation into on-line trajectory planning for autonomous robotic excavation. A dynamic model for arm/environment interaction is proposed. Excavation trajectories are generated using a trapezoidal velocity profile under the maximum force/torque constraints. A scheme for real-time identification of dynamic arm/environment interaction parameters is implemented with a first-order algorithm of Saridis-Stein stochastic approximation. The result of a simulation study is presented to illustrate the proposed trajectory planning approach.<<ETX>>","PeriodicalId":133630,"journal":{"name":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 IEEE International Conference on MFI '94. Multisensor Fusion and Integration for Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MFI.1994.398430","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 describes the authors' initial investigation into on-line trajectory planning for autonomous robotic excavation. A dynamic model for arm/environment interaction is proposed. Excavation trajectories are generated using a trapezoidal velocity profile under the maximum force/torque constraints. A scheme for real-time identification of dynamic arm/environment interaction parameters is implemented with a first-order algorithm of Saridis-Stein stochastic approximation. The result of a simulation study is presented to illustrate the proposed trajectory planning approach.<>