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Force tracking control for motion synchronization in human-robot collaboration
| Content Provider | Scilit |
|---|---|
| Author | Li, Yanan Ge, Shuzhi Sam |
| Copyright Year | 2014 |
| Description | SUMMARY In this paper, motion synchronization is investigated for human–robot collaboration such that the robot is able to “actively” follow its human partner. Force tracking is achieved with the proposed method under the impedance control framework, subject to uncertain human limb dynamics. Adaptive control is developed to deal with point-to-point movement, and learning control and neural networks control are developed to generate periodic and arbitrary continuous trajectories, respectively. Stability and tracking performance of the closed-loop system are discussed through rigorous analysis. The validity of the proposed method is verified through simulation and experiment studies. |
| Related Links | http://sro.sussex.ac.uk/id/eprint/72070/2/force21jul14.pdf https://www.cambridge.org/core/services/aop-cambridge-core/content/view/FCE6C37B08ED9A6250D731B9DE26DF4B/S0263574714002240a.pdf/div-class-title-force-tracking-control-for-motion-synchronization-in-human-robot-collaboration-div.pdf |
| Ending Page | 1281 |
| Page Count | 22 |
| Starting Page | 1260 |
| ISSN | 02635747 |
| e-ISSN | 14698668 |
| DOI | 10.1017/s0263574714002240 |
| Journal | Robotica |
| Issue Number | 6 |
| Volume Number | 34 |
| Language | English |
| Publisher | Cambridge University Press (CUP) |
| Publisher Date | 2016-06-01 |
| Access Restriction | Open |
| Subject Keyword | Robotica Cybernetical Science Motion Synchronization robot Collaboration Force Tracking |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Optimization Artificial Intelligence Rehabilitation Control and Systems Engineering Mechanical Engineering Computational Mechanics Modeling and Simulation Computer Science Applications Computer Vision and Pattern Recognition Software |
