Open AccessResearch on Dynamic Obstacle Avoidance Path Planning Strategy of AGV
Author(s) -
Zhenteng Miao,
Xiaolei Zhang,
Guojue Huang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2006/1/012067
Subject(s) - obstacle avoidance , obstacle , robustness (evolution) , collision avoidance , computer science , motion planning , fuzzy logic , control engineering , robot , mobile robot , engineering , control theory (sociology) , simulation , collision , artificial intelligence , control (management) , biochemistry , chemistry , computer security , political science , law , gene
As a highly intelligent robot, AGV has many applications in automatic production, AGV needs to ensure its own safety when it works in a complex environment. If there are irregularly moving obstacles within the working range of AGV, collision accidents are easy to occur. This paper establish a obstacle avoidance fuzzy controller based on fuzzy control algorithm, this controller can obtain the operation data of obstacle avoidance, AGV adaptive neuro-fuzzy network system is further established to train these operation data for a certain number of times, so that this system can provide correct behavior decision for AGV dynamic obstacle avoidance. This paper builds a simulation environment to test this system. It is proved that this system has good robustness and reliability.