Liao, Weiwen; Hou, Kang; Tang, Yonglian; Su, Bo; Xiang, Yu Source: 2023 3rd International Conference on Electronic Information Engineering and Computer Science, EIECS 2023, p 776-780, 2023, 2023 3rd International Conference on Electronic Information Engineering and Computer Science, EIECS 2023;

Abstract:

The paper presents adaptive untracked Kalman Filter and multi-sensor data fusion are used for visual positioning of the robot. Adaptive untracked Kalman Filter is used to fuse the data and obtain the positioning data with higher precision. In this way, the robot can effectively avoid the inaccuracy of the position data caused by some occlusion or violent shaking, and also minimize the impact of measurement error on positioning. Simulation results show that the proposed method can effectively improve the positioning accuracy.

© 2023 IEEE. (15 refs.)