Name
Abstract | ||
|---|---|---|
In this paper, we consider a dynamical system whose trajectory is a result of minimizing a multiphase cost function. The multiphase cost function is assumed to be a weighted sum of specified features (or basis functions) with phase-dependent weights that switch at some unknown phase transition points. A new inverse optimal control approach for recovering the cost weights of each phase and estimating the phase transition points is proposed. The key idea is to use a length-adapted window moving along the observed trajectory, where the window length is determined by finding the minimal observation length that suffices for a successful cost weight recovery. The effectiveness of the proposed method is first evaluated on a simulated robot arm, and then, demonstrated on a dataset of human participants performing a series of squatting tasks. The results demonstrate that the proposed method reliably retrieves the cost function of each phase and segments each phase of motion from the trajectory with a segmentation accuracy above 90%. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TRO.2019.2926388 | IEEE Transactions on Robotics |
Keywords | Field | DocType |
Cost function,Trajectory,Optimal control,Motion segmentation,Jacobian matrices,Feature extraction | Robotic arm,Phase transition,Control theory,Segmentation,Inverse optimal control,Basis function,Dynamical system,Mathematics,Trajectory | Journal |
Volume | Issue | ISSN |
35 | 6 | 1552-3098 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wanxin Jin | 1 | 5 | 2.83 |
| Dana Kulic | 2 | 810 | 69.21 |
| Jonathan Feng-Shun Lin | 3 | 27 | 4.07 |
| Shaoshuai Mou | 4 | 395 | 29.80 |
| Sandra Hirche | 5 | 961 | 106.36 |