Research on Adaptive Monte Carlo Location Method Based on Fusion Posture Estimation

In the process of global positioning of robots, the errors of odometer caused by the abduction of robots and the errors of laser data matching results caused by ambient characteristics will lead to inaccurate Monte Carlo positioning. In this paper, an adaptive Monte Carlo localization algorithm based on position and attitude estimation is proposed. The real-time position and attitude are estimated by matching the scanning data of the laser sensor, and the real-time location is realized by combining the adaptive Monte Carlo algorithm. The results of simulation experiments on ROS show that the algorithm is superior to Monte Carlo algorithm in particle concentration and positioning accuracy, and has good robustness to the abduction problem of robots and the environment without obvious characteristics, which solves the positioning problem caused by the uncertainty of odometer.