{"title":"Rapid Transport of Suspended Payloads","authors":"G. Starr, John E. Wood, R. Lumia","doi":"10.1109/ROBOT.2005.1570310","DOIUrl":null,"url":null,"abstract":"The topic of composing inputs for systems with mechanical flexibility has received attention for many years. Two popular methods are (1) shaping a nominal trajectory by convolution with an impulse sequence which itself cancels the flexibility, and (2) trajectory parameter optimization using structured basis functions, e.g. bang-coast-bang. However, each of these methods deteriorates in a different way when the motion is rapid compared to the natural period of the flexibility. Motions synthesized using dynamic programming offer clear advantages in these situations: (1) the resulting motions are smoother than those using impulse-convolution, and (2) dynamic programming is deterministic and does not rely on a convex objective function like gradient-based parameter optimization. Examples of the shortcomings of impulse-convolution and parameter-optimization will be shown; then we present both simulation and experimental evaluation of rapid transport of a suspended object using a robot manipulator and a minimum-energy trajectory obtained by dynamic programming.","PeriodicalId":350878,"journal":{"name":"Proceedings of the 2005 IEEE International Conference on Robotics and Automation","volume":"178 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2005 IEEE International Conference on Robotics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBOT.2005.1570310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
The topic of composing inputs for systems with mechanical flexibility has received attention for many years. Two popular methods are (1) shaping a nominal trajectory by convolution with an impulse sequence which itself cancels the flexibility, and (2) trajectory parameter optimization using structured basis functions, e.g. bang-coast-bang. However, each of these methods deteriorates in a different way when the motion is rapid compared to the natural period of the flexibility. Motions synthesized using dynamic programming offer clear advantages in these situations: (1) the resulting motions are smoother than those using impulse-convolution, and (2) dynamic programming is deterministic and does not rely on a convex objective function like gradient-based parameter optimization. Examples of the shortcomings of impulse-convolution and parameter-optimization will be shown; then we present both simulation and experimental evaluation of rapid transport of a suspended object using a robot manipulator and a minimum-energy trajectory obtained by dynamic programming.