Journal article 948 views 422 downloads
Visual Servoing of Humanoid Dual-Arm Robot with Neural Learning Enhanced Skill Transferring Control
Chenguang Yang,
Junshen Chen,
Zhaojie Ju,
Andy S. K. Annamalai
International Journal of Humanoid Robotics, Start page: 1750023
Swansea University Author: Chenguang Yang
-
PDF | Accepted Manuscript
Download (3.43MB)
DOI (Published version): 10.1142/S0219843617500232
Abstract
This paper presents a novel combination of visual servoing (VS) control and neural network (NN) learning on humanoid dual-arm robot. A VS control system is built by using stereo vision to obtain the 3D point cloud of a target object. A least square-based method is proposed to reduce the stochastic e...
| Published in: | International Journal of Humanoid Robotics |
|---|---|
| ISSN: | 0219-8436 1793-6942 |
| Published: |
2017
|
| Online Access: |
Check full text
|
| URI: | https://cronfa.swan.ac.uk/Record/cronfa34937 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract: |
This paper presents a novel combination of visual servoing (VS) control and neural network (NN) learning on humanoid dual-arm robot. A VS control system is built by using stereo vision to obtain the 3D point cloud of a target object. A least square-based method is proposed to reduce the stochastic error in workspace calibration. An NN controller is designed to compensate for the effect of uncertainties in payload and other parameters (both internal and external) during the tracking control. In contrast to the conventional NN controller, a deterministic learning technique is utilized in this work, to enable the learned neural knowledge to be reused before current dynamics changes. A skill transfer mechanism is also developed to apply the neural learned knowledge from one arm to the other, to increase the neural learning efficiency. Tracked trajectory of object is used to provide target position to the coordinated dual arms of a Baxter robot in the experimental study. Robotic implementations has demonstrated the efficiency of the developed VS control system and has verified the effectiveness of the proposed NN controller with knowledge-reuse and skill transfer features. |
|---|---|
| Keywords: |
Neural networks; deterministic learning; visual servoing; stereo vision |
| College: |
Faculty of Science and Engineering |
| Start Page: |
1750023 |