High-fidelity positioning and tracking of AGVs based on Kalman filter

Automated guided vehicles are widely used in industry, agriculture and service industry. To achieve the precise positioning of the vehicle, this paper designed and modeled a UWB-based automated guided vehicle positioning system, and proposed a positioning method based on trilateration characteristics and Kalman filtering. The base stations measure the distance to the tag on the vehicle, and then the coordinates of the automated guided vehicle are initially calculated through trilateration. To reduce the influence of noise signals and hardware errors on positioning accuracy, Kalman filtering is used to optimize the positioning system. The indoor positioning experiments show that the positioning ranges of the automated guided vehicle in uniform linear motion and uniform random motion are (-0.0307m, 0.0552m) and (-0.0531m, 0.0670m), respectively, and the standard deviations are 0.0242m and 0.0379m, respectively. The method proposed in this paper has good accuracy and practicability, and can meet the positioning needs of automated guided vehicles.