Automated Guided Vehicle (AGV) Driving System Using Vision Sensor and Color Code

Recently, the use of Automated Guided Vehicles (AGVs) at production sites has been increasing due to industrial development, such as the introduction of smart factories. AGVs utilizing the wired induction method, which is cheaper and faster than the wireless induction method, are mainly used at production sites. However, the wired guidance AGV operation system has the disadvantage of being limited to small-batch or collaboration-based production sites, since it is difficult to change the driving route. In this paper, we propose an AGV line-scan algorithm that can perform route recognition, driving commands, and operation through color-code recognition using an Arduino controller and a low-cost vision sensor, instead of the optical sensor conventionally used for these functions. When the proposed algorithm is applied to the AGV car, the CMUcam 5 Pixy2 camera identifies the driving path to follow by tracking a black line using the Otsu method. In addition, it can be confirmed that the driving command is executed using the proposed color code by applying the color recognition function of the CMUcam 5 Pixy2.

Automated summary

The use of AGVs has been increasing at production sites due to industrial development. Wired induction method is mainly used as it is cheaper and faster. However, the disadvantage of this method is a limited driving route. In this paper, an AGV line-scan algorithm is proposed to overcome this limitation by using an Arduino controller and a low-cost vision sensor for route recognition, driving commands, and operation through color-code recognition.