Name
Abstract | ||
|---|---|---|
This paper presents a method to estimate external forces exerted on a manipulator during motion, avoiding the use of a sensor. The method is based on task-oriented dynamics model learning and a robust disturbance state observer. The combination of both leads to an efficient torque observer that can be incorporated to any control scheme. The use of a learning-based approach avoids the need of analytical models of joints' friction or Coriolis dynamics effects. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICRA.2013.6631072 | Robotics and Automation |
Keywords | Field | DocType |
force control,friction,learning systems,manipulator dynamics,motion control,observers,robust control,torque control,Coriolis dynamics effects,compliant robot manipulation,control scheme,external force estimation,friction,learning-based approach,manipulator,motion,robust disturbance state observer,task-oriented dynamics model learning,torque observer | State observer,Motion control,Control theory,Manipulator,Control engineering,Torque observer,Engineering,Robot,Robust control,Coriolis force,Model learning | Conference |
Volume | Issue | ISSN |
2013 | 1 | 1050-4729 |
ISBN | Citations | PageRank |
978-1-4673-5641-1 | 10 | 0.68 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adria Colome | 1 | 30 | 5.89 |
| Diego Pardo | 2 | 12 | 1.80 |
| Guillem Alenyà | 3 | 219 | 27.43 |
| Carme Torras | 4 | 1155 | 115.66 |