Research on Visual Rid and Path Planning of Industrial Robot

DOI

10.2991/emcs-16.2016.490How to use a DOI?

Keywords

Friction coefficient; ANSYS; Contact analysis; Neural network; Genetic algorithm

Abstract

Traditional path planning algorithm for multi-objective circumstances, primarily on a single multi-information fusion Select avoidance path, in the scale of sludge entangled region vulnerable to blind, unable to robot path sludge entangled environment for accurate planning. This paper presents an improved robot vision route planning method to get rid of, improve the ability of the robot's environment entangled in the mud of the robot around obstacles. To this end, an improved robot path planning method to get rid of visual entangled, with the robot vision instrument collection features sludge entangled with a normalization method to integrate visual information into the programming model to choose the best path, the robot get rid of sludge entanglement and the shortest route requires integration into a fitness function, get the best robot rid of paths through the genetic algorithm search. Experimental results show that the method of sludge entanglement under ambient robot path planning to get rid of lengths and efficiency are superior to the traditional model, with high robustness.

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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TY  - CONF
AU  - Jingyun Zhao
AU  - Pengfei Wang
PY  - 2016/01
DA  - 2016/01
TI  - Research on Visual Rid and Path Planning of Industrial Robot
BT  - Proceedings of the 2016 International Conference on Education, Management, Computer and Society
PB  - Atlantis Press
SP  - 1950
EP  - 1953
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-16.2016.490
DO  - 10.2991/emcs-16.2016.490
ID  - Zhao2016/01
ER  -