Name
Abstract | ||
|---|---|---|
This paper demonstrates simultaneous identification and control of an $n$-DOF robot in a computationally-efficient fashion utilizing Spatial Vector Algebra (SVA). In particular, the inertia, Coriolis and gravity terms for the dynamics of a robot are computed using spatial inertia tensors. With the assumption that the link lengths or the distance between the joint axes are accurately known, it will be shown that inertial properties of a robot can be directly evaluated from the inertia tensor. An algorithm is proposed to evaluate the regressor, yielding a run time of $O(n^2)$. The efficiency of this algorithm yields a means for online system identification via the SVA--based regressor and, as a byproduct, a method for accurate model-based control. Experimental validation of the proposed method is provided through its implementation in three case studies: offline identification of a double pendulum and a $4$-DOF robotic leg, and online identification and control of a 4-DOF robotic arm. |
Year | Venue | Field |
|---|---|---|
2016 | arXiv: Optimization and Control | Moment of inertia,Robotic arm,Mathematical optimization,Euclidean vector,Control theory,Double pendulum,Inertia,Robot,System identification,Mathematics,Computation |
DocType | Volume | Citations |
Journal | abs/1608.02683 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shishir Kolathaya | 1 | 67 | 7.40 |
| Benjamin J. Morris | 2 | 0 | 0.34 |
| Ryan W. Sinnet | 3 | 60 | 4.50 |
| Aaron D. Ames | 4 | 1202 | 136.68 |