Name
Abstract | ||
|---|---|---|
A general theory of movement-pattern perception based on bi-directional theory for sensory-motor integration can be used for motion capture and learning by watching in robotics. We demonstrate our methods using the game of Kendama, executed by the SARCOS Dextrous Slave Arm, which has a very similar kinematic structure to the human arm. Three ingredients have to be integrated for the successful execution of this task. The ingredients are (1) to extract via-points from a human movement trajectory using a forward-inverse relaxation model, (2) to treat via-points as a control variable while reconstructing the desired trajectory from all the via-points, and (3) to modify the via-points for successful execution. In order to test the validity of the via-point representation, we utilized a numerical model of the SARCOS arm, and examined the behavior of the system under several conditions. Copyright © 1996 Elsevier Science Ltd. |
Year | DOI | Venue |
|---|---|---|
1996 | 10.1016/S0893-6080(96)00043-3 | Neural Networks |
Keywords | Field | DocType |
teaching by showing,task-level learning,bi-directional theory,dynamic optimization,motion capture | Motion capture,Kinematics,Human arm,Simulation,Computer science,Control variable,Artificial intelligence,Artificial neural network,Robot,Machine learning,Robotics,Trajectory | Journal |
Volume | Issue | ISSN |
9 | 8 | Neural Networks |
Citations | PageRank | References |
55 | 11.87 | 9 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroyuki Miyamoto | 1 | 216 | 90.54 |
| Stefan Schaal | 2 | 6081 | 530.10 |
| Francesca Gandolfo | 3 | 74 | 15.23 |
| Hiroaki Gomi | 4 | 385 | 119.46 |
| Yasuharu Koike | 5 | 357 | 62.78 |
| Rieko Osu | 6 | 121 | 20.42 |
| Eri Nakano | 7 | 95 | 17.10 |
| Yasuhiro Wada | 8 | 225 | 62.58 |
| Mitsuo Kawato | 9 | 2306 | 447.03 |