Name
Abstract | ||
|---|---|---|
In this paper we present an architecture for autonomous manipulation. Our approach is based on the belief that contact interactions during manipulation should be exploited to improve dexterity and that optimizing motion plans is useful to create more robust and repeatable manipulation behaviors. We therefore propose an architecture where state of the art force/torque control and optimization-based motion planning are the core components of the system. We give a detailed description of the modules that constitute the complete system and discuss the challenges inherent to creating such a system. We present experimental results for several grasping and manipulation tasks to demonstrate the performance and robustness of our approach. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10514-013-9365-9 | Auton. Robots |
Keywords | Field | DocType |
Grasping,Manipulation,Force control,Optimization | Motion planning,Architecture,Torque,Computer science,Simulation,Robustness (computer science) | Journal |
Volume | Issue | ISSN |
36 | 1-2 | 0929-5593 |
Citations | PageRank | References |
21 | 1.09 | 45 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ludovic Righetti | 1 | 711 | 54.91 |
| Mrinal Kalakrishnan | 2 | 636 | 33.36 |
| Peter Pastor | 3 | 1139 | 50.44 |
| Jonathan Binney | 4 | 137 | 8.44 |
| Jonathan Kelly | 5 | 650 | 48.82 |
| Randolph C. Voorhies | 6 | 28 | 2.03 |
| Gaurav S. Sukhatme | 7 | 5469 | 548.13 |
| Stefan Schaal | 8 | 6081 | 530.10 |