Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)

Agent-based Eight Wheel-legged Hybrid Wheelchair Control System

Authors
Dongxing Cao, Shanshan Liu, Chao Wang, Minfei Li
Corresponding Author
Dongxing Cao
Available Online November 2016.
DOI
10.2991/aiie-16.2016.83How to use a DOI?
Keywords
multi-agent system; climbing wheelchair; robot mechanism; port-agent; control strategy
Abstract

Eight wheel-legged hybrid wheelvhair robot motion is the process of multi-agent system collaborating work, in which each module can be viewed as an agent, such as frontal leg mechanism, latter leg mechanism, and seat position and orientation mechanism. Agent has the ability of sensing the environment, and at any time responds to the environment. The paper builds a new robot wheelchair. The user operates the handle to implement the communication of multi-agent, and changes the position and orientation of frontal leg, latter leg, and seat in the light sensing the environment. It can not only work on the ground, but also climb stairs and obstacles.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
Series
Advances in Intelligent Systems Research
Publication Date
November 2016
ISBN
10.2991/aiie-16.2016.83
ISSN
1951-6851
DOI
10.2991/aiie-16.2016.83How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Dongxing Cao
AU  - Shanshan Liu
AU  - Chao Wang
AU  - Minfei Li
PY  - 2016/11
DA  - 2016/11
TI  - Agent-based Eight Wheel-legged Hybrid Wheelchair Control System
BT  - Proceedings of the 2016 2nd International Conference on Artificial Intelligence and Industrial Engineering (AIIE 2016)
PB  - Atlantis Press
SP  - 362
EP  - 365
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-16.2016.83
DO  - 10.2991/aiie-16.2016.83
ID  - Cao2016/11
ER  -