Abstract
The automated guided vehicle (AGV) with sensor recognition method is having shortcomings such as high cost and noise. In this regard, the flower pollination algorithm (FPA) is applied in the path detection system of an AGV, in combination with computer vision. The path detection system starts with image acquisition using an onboard camera. The captured image is then preprocessed to obtain simple contrast of the path. Subsequently, the FPA is used to find a set of solution points fall inside the path zone. A regression model is formed as path guidance for AGV to travel accordingly. The performance of FPA is analyzed via simulation and real-world experiment using a robotic platform and tested on commonly seen line patterns in the industrial environment. The effectiveness of FPA in path detection is also compared with particle swarm optimization. The obtained results demonstrate the promising feasibility of the proposed FPA-based path detection system.
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