Andrew P. Sabelhaus, Abishek K. Akella, Z. A. Ahmad, Vytas SunSpiral
{"title":"柔性脊柱机器人的模型预测控制","authors":"Andrew P. Sabelhaus, Abishek K. Akella, Z. A. Ahmad, Vytas SunSpiral","doi":"10.23919/ACC.2017.7963738","DOIUrl":null,"url":null,"abstract":"The Underactuated Lightweight Tensegrity Robotic Assistive Spine (ULTRA Spine) project is an ongoing effort to develop a flexible, actuated backbone for quadruped robots. In this work, model-predictive control is used to track a trajectory in the robot's state space, in simulation. This is the first work that tracks an arbitrary trajectory, in closed-loop, in the state space of a spine-like tensegrity robot. The state trajectory used here corresponds to a bending motion of the spine, with translations and rotations of the three moving vertebrae. The controller uses a linearized model of the system dynamics, computed at each timestep, and has both constraints and weighted penalties to reduce linearization errors. For this robot, which measures 26cm × 26cm × 45cm, the tracking errors converge to less than 0.5cm even with disturbances, indicating that the controller is stable and could be used on a physical robot in future work.","PeriodicalId":422926,"journal":{"name":"2017 American Control Conference (ACC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Model-Predictive Control of a flexible spine robot\",\"authors\":\"Andrew P. Sabelhaus, Abishek K. Akella, Z. A. Ahmad, Vytas SunSpiral\",\"doi\":\"10.23919/ACC.2017.7963738\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Underactuated Lightweight Tensegrity Robotic Assistive Spine (ULTRA Spine) project is an ongoing effort to develop a flexible, actuated backbone for quadruped robots. In this work, model-predictive control is used to track a trajectory in the robot's state space, in simulation. This is the first work that tracks an arbitrary trajectory, in closed-loop, in the state space of a spine-like tensegrity robot. The state trajectory used here corresponds to a bending motion of the spine, with translations and rotations of the three moving vertebrae. The controller uses a linearized model of the system dynamics, computed at each timestep, and has both constraints and weighted penalties to reduce linearization errors. For this robot, which measures 26cm × 26cm × 45cm, the tracking errors converge to less than 0.5cm even with disturbances, indicating that the controller is stable and could be used on a physical robot in future work.\",\"PeriodicalId\":422926,\"journal\":{\"name\":\"2017 American Control Conference (ACC)\",\"volume\":\"21 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 American Control Conference (ACC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ACC.2017.7963738\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 American Control Conference (ACC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ACC.2017.7963738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Model-Predictive Control of a flexible spine robot
The Underactuated Lightweight Tensegrity Robotic Assistive Spine (ULTRA Spine) project is an ongoing effort to develop a flexible, actuated backbone for quadruped robots. In this work, model-predictive control is used to track a trajectory in the robot's state space, in simulation. This is the first work that tracks an arbitrary trajectory, in closed-loop, in the state space of a spine-like tensegrity robot. The state trajectory used here corresponds to a bending motion of the spine, with translations and rotations of the three moving vertebrae. The controller uses a linearized model of the system dynamics, computed at each timestep, and has both constraints and weighted penalties to reduce linearization errors. For this robot, which measures 26cm × 26cm × 45cm, the tracking errors converge to less than 0.5cm even with disturbances, indicating that the controller is stable and could be used on a physical robot in future work.