Outdoor positioning and navigation algorithm of inspection robot dog based on multi-sensor fusion

Abstract

In the process of outdoor positioning and navigation of the patrol robot dog, the collected information was not fused, which led to the failure of accurate identification of obstacles. Therefore, an outdoor positioning and navigation algorithm based on multi-sensor fusion was proposed for the patrol robot dog. The information was collected by multi-sensor equipment such as 3D laser radar erected on the section plane of the patrol robot dog. The information was decomposed based on the wavelet packet energy spectrum strategy. After the robot dog patrol target was detected, the fusion results are input into the extended Kalman filter model through the Bayesian initial fusion data, and the robot dog positioning is realized according to the optimal variance estimation of the output parameters. Finally, the ant colony algorithm is improved by the clustering search strategy to search the optimal path to achieve navigation. The experimental results show that the method can effectively identify obstacles in complex environments and different scene execution speeds, and the recognition accuracy is high; It can accurately and quickly plan the best path of the fault area to ensure the stability of power system operation.