{"title":"Adaptive step duration in biped walking: A robust approach to nonlinear constraints","authors":"N. Bohorquez, Pierre-Brice Wieber","doi":"10.1109/HUMANOIDS.2017.8246952","DOIUrl":null,"url":null,"abstract":"When a biped robot is walking in a crowd, being able to adapt the duration of steps is a key element to avoid collisions. Model Predictive Control (MPC) schemes for biped walking usually assume a fixed step duration since adapting it leads to a nonlinear problem, in general. Nonlinear solvers do not guarantee the satisfaction of nonlinear constraints at every iterate and this can be problematic for the real-time operation of robots. We propose a method to make sure that all iterates satisfy the nonlinear constraints by borrowing concepts from robust control: we make the problem robust to nonlinearities within some bounds. These bounds are linear with respect to the variables of the problem and can be adapted online.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":"507 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HUMANOIDS.2017.8246952","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
When a biped robot is walking in a crowd, being able to adapt the duration of steps is a key element to avoid collisions. Model Predictive Control (MPC) schemes for biped walking usually assume a fixed step duration since adapting it leads to a nonlinear problem, in general. Nonlinear solvers do not guarantee the satisfaction of nonlinear constraints at every iterate and this can be problematic for the real-time operation of robots. We propose a method to make sure that all iterates satisfy the nonlinear constraints by borrowing concepts from robust control: we make the problem robust to nonlinearities within some bounds. These bounds are linear with respect to the variables of the problem and can be adapted online.