A multi-sensor fusion positioning approach for indoor mobile robot using factor graph

•Considering different sensor characteristics of the indoor mobile robot, sensor measurement models of IMU, Odometer and LiDAR are constructed.•The factor graph positioning model fuses asynchronous nonlinear sensor information and optimizes incremental robot state estimation using an iterative approach.•Dynamic adaptation function detects sensor anomaly information in real time to improve the robustness of multi-sensor fusion positioning system.•The proposed algorithm reduces mean location errors by about 40% compared to conventional positioning methods under normal and abnormal sensor conditions.