Abstract
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.
Cite
CITATION STYLE
Miao, Z., Zhang, X., & Huang, G. (2021). Research on dynamic obstacle avoidance path planning strategy of AGV. In Journal of Physics: Conference Series (Vol. 2006). IOP Publishing Ltd. https://doi.org/10.1088/1742-6596/2006/1/012067
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