Abstract
Automatic guided vehicle (AGV) is a robot with automatic transportation capability, which is the key equipment to achieve efficient and intelligent logistics. And thus, AGV localization has gradually become a research hotspot in this field, especially in the indoor environment. In this paper, the localization strategy which an inertial navigation system (INS) and ultra wide band (UWB) integrated is proposed. Based on the INS/UWB integrated model, an interactive multiple model (IMM) algorithm is proposed to reduce the impact of positioning in line-of-sight (LOS) and non-line-of-sight (NLOS) states. To the UWB localization system, we set up two Kalman filters (KF) in LOS/NLOS states according to different distance error characteristics, then, the Markov chain is used to transform the state of the two models. The weighted fusion of the filtering results is employed to provide the distance estimation. In the integrated localization stage, the final position estimation of the integrated localization is computed by the difference between the UWB solution and the INS solution. Test experiments show that the IMM-based UWB localization approach can reduce the influence of LOS/NLOS environment on positioning accuracy, and the INS/UWB integrated localization can achieve accurate position information.
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