Inspection robot positioning method based on multi-sensor fusion

Abstract

The invention discloses an inspection robot positioning method based on multi-sensor fusion, and the method comprises the following steps: S1, collecting the data of multiple sensors, including the absolute positioning information of a positioning system, the data of an encoder in an inspection robot, and the data of an inertial measurement unit; s2, EKF fusion of multi-sensor data: carrying out primary EKF data fusion on the data of the encoder and the measurement quantity of the inertial measurement unit; carrying out secondary EKF data fusion on the fused data and absolute positioning information of the positioning system to obtain a secondary fusion pose; and S3, performing Monte Carlo positioning in combination with a 3D prior map according to the fusion pose. According to the invention, based on the EKF fusion algorithm, a pose solution with no accumulative error and high reliability and stability can be given in real time; and the MCL positioning algorithm is combined, so that the positioning precision requirement in some shielding environments is ensured.

Description

technical field [0001] The invention relates to the technical field of electric inspection robots, in particular to a positioning method for inspection robots based on multi-sensor fusion. Background technique [0002] There are many disadvantages in the operation mode of manual power inspection. For example, the manual method determines its degree of automation and efficiency is low, and the cost is high; and the manual cannot guarantee the timely intercommunication and uploading of the entered data to the cloud, resulting in information lag and backup difficulties; There is also no guarantee of full coverage and round-the-clock inspection of the entire station. Relying on powerful and reliable positioning, navigation and intelligent recognition technology, inspection robots have gradually replaced manpower as the main force in power inspections. [0003] At this stage, the mainstream positioning scheme of the inspection robot is Lidar-scan, which is to calculate the real-...

AI Technical Summary

Problems solved by technology

[0004] The laser registration algorithm can give the optimal pose estimation when the surrounding environment features are rich, but the laser registration algorithm still has its disadvantages, such as the large turning angle, fast driving speed, interference of moving objects and transparent objects during the driving process. The resulting mismatch and other situations, or in an open environment with few surrounding environment features, will directly lead to an error in estimating the pose, and the environment of the substation is complex, and its single laser positioning solution cannot meet its actual application requirements.

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