Name
Title | ||
|---|---|---|
On the use of forward kinematic models in visually guided hand position control - analysis based on ISLES model |
Abstract | ||
|---|---|---|
The human nervous system is equipped with a forward kinematics model, which calculates the hand positions using proprioceptive information. Since significant evidence suggests that the forward dynamics model is used for general motion control, the forward kinematics model also seems to be used for the control of visually guided reaching. However, we believe that the forward kinematics model plays no role, or only a supplemental role, in the final stages of visually guided hand position control. Instead, we propose that this is mainly handled by the inverse kinematics model. To explain the relatively large errors of the internal models in the human nervous system, Maeda et at. (Proceedings of the 1993 International Joint Conference on Neural Networks (IJCNN'93 Nagoya), 1993, pp, 1317-1320) proposed a neural network architecture called independent scalar learning elements summations (ISLES) model. We will provide evidence based on experimental results and a mathematical analysis using the ISLES model to support our hypothesis. (C) 2002 Published by Elsevier Science B.V. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1016/S0925-2312(02)00498-8 | NEUROCOMPUTING |
Keywords | Field | DocType |
forward kinematics model,inverse kinematics model,visually guided reaching,ISLES model | Kinematics,Inverse kinematics,General motion control,Scalar (physics),Neural network architecture,Forward kinematics,Artificial intelligence,Artificial neural network,Mathematics | Journal |
Volume | Issue | ISSN |
44 | 1-4 | 0925-2312 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eimei Oyama | 1 | 120 | 20.45 |
| Taro Maeda | 2 | 434 | 80.83 |
| Susumu Tachi | 3 | 1294 | 221.20 |
| Karl F. MacDorman | 4 | 805 | 54.92 |
| Arvin Agah | 5 | 397 | 54.11 |