Autonomous positioning method and device and mobile robot

Abstract

The embodiment of the invention provides an autonomous positioning method and device and a mobile robot. The method comprises the steps that after the mobile robot moves, obstacle detection is conducted through a laser range finder on the mobile robot; a pre-estimated pose of the mobile robot is calculated after the mobile robot moves; a cost gradient of the detected obstacle in a corresponding region grid is searched in a preset gradient map; wherein the gradient map comprises a plurality of grids in a scene where the mobile robot is located and the cost of the plurality of grids, the cost ofthe grids is used for representing the confidence that the grids are obstacle grids, and the cost gradient of the grids is used for representing the direction in which the cost of the grids is increased fastest; and movement compensation is performed on the estimated pose according to the cost gradient of the detected obstacle corresponding to the grid in a preset gradient map to obtain an optimized pose of the mobile robot after movement. The laser end point is matched with the gradient map, the optimized pose is obtained through one-time matching, and resource consumption in the autonomouspositioning process is effectively reduced.

Description

technical field [0001] The invention relates to the technical field of autonomous positioning of robots, in particular to an autonomous positioning method, device and mobile robot. Background technique [0002] The mobile robot can move in the scene and perform corresponding tasks. The mobile robot needs to obtain its own pose when performing some tasks. The pose includes the position and orientation angle of the mobile robot. After the mobile robot moves, it can estimate the pose of the mobile robot after it moves based on the readings of the built-in odometer and based on the motion model of the mobile robot. However, there is a certain error in the reading of the odometer, and the error will accumulate as the moving distance of the mobile robot increases, so the pose estimated based on the odometer reading needs to be corrected. [0003] In the prior art, the mobile robot can be a scene map of the scene established by SLAM (simultaneous localization and mapping, timely p...

AI Technical Summary

Problems solved by technology

[0004] However, in order to make the difference between the resampling result and the actual pose of the mobile robot smaller, it may be necessary to set a larger number of particles so that these particles can better reflect the possible distribution of the pose of the mobile robot, while the number of particles The increase will increase the number of matching between the range data and the scene map, resulting in an increase in the complexity of the algorithm, and the mobile robot may spend more system resources in the process of autonomous positioning

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