Research on UWB/QR Sensor Fusion Location Algorithm based on UKF and FIS

Demanding for precision and flexibility of Automatic Guided Vehicle is critical with the rapid development of logistics automation and factory automation, a low-cost sensor fusion positioning method is proposed in this paper. The sensors used in this paper are Ultra Wide Band (UWB), a Gyroscope, Encoders, and the Camera (QR), and a more accurate pose can be obtained by the unscented Kalman filter (UKF). At the same time, the fuzzy inference system (FIS) is used to output the noise of UKF. To demonstrate the performance of the proposed method, we use the simulated sensor data signal and carry out several simulations under different working conditions. Finally, the simulation demonstrates that the proposed method can effectively overcome the low positioning accuracy of a single sensor and the UWB/QR sensor fusion location algorithm can achieve accurate positioning information.