Proceedings of the 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)

The Virtual Assembly Technology Based on Natural Gesture

Authors
Yanjiao Chen, Guanglong Du, Ping Zhang
Corresponding Author
Yanjiao Chen
Available Online June 2017.
DOI
https://doi.org/10.2991/caai-17.2017.3How to use a DOI?
Keywords
virtual assembly; kalman filtering; leap motion; force feedback.
Abstract
The purpose of this paper is to present a method called virtual assembly technology based on natural gesture. In the proposed method, five Leap Motions are fixed on the table to measure the position of the hands. Due to the tracking errors and the noise of equipment, the measurement errors will increase over time. Therefore, we use Kalman Filter and Particle Filter to evaluate the position and orientation of our hands. Then we use 3D Max to build the joint model of our hands, and OSG (OpenSceneGraph) to refactor the model of the hand. We use k-DOPs collision detection algorithm to detect collisions between hands model and human model. Then we use noncontact force feedback to make the operator experience the drag force like in a real environment, so that the operator can use natural gesture to do various assembly operation on the parts of the products in an interactive virtual assembly environment.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2017
ISBN
978-94-6252-360-9
ISSN
1951-6851
DOI
https://doi.org/10.2991/caai-17.2017.3How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yanjiao Chen
AU  - Guanglong Du
AU  - Ping Zhang
PY  - 2017/06
DA  - 2017/06
TI  - The Virtual Assembly Technology Based on Natural Gesture
BT  - 2017 2nd International Conference on Control, Automation and Artificial Intelligence (CAAI 2017)
PB  - Atlantis Press
SP  - 9
EP  - 13
SN  - 1951-6851
UR  - https://doi.org/10.2991/caai-17.2017.3
DO  - https://doi.org/10.2991/caai-17.2017.3
ID  - Chen2017/06
ER  -