Robot positioning method based on two-dimensional laser

Abstract

The invention relates to the technical field of mobile robot positioning and particularly discloses a robot positioning method based on two-dimensional laser. The robot positioning method based on two-dimensional laser comprises the steps that first motion data of a robot recorded by a speedometer on a two-dimensional plane is converted into an overall coordination system; a laser sensor carried by the robot constantly scans environment information to obtain a laser scanning point set; the laser scanning point set is processed to obtain second motion data; the second motion data is converted to the overall coordination system; the first motion data and the second motion data under the overall coordination system are fused through a Kalman algorithm to obtain fused data; the fused data is output; the positioning information of the robot is obtained according to the fused data. The positioning precision of robots is improved by adopting the robot positioning method based on two-dimensional laser.

Description

technical field [0001] The invention relates to the technical field of mobile robot positioning, in particular to a two-dimensional laser-based robot positioning method. Background technique [0002] In the application of mobile robots, navigation and positioning are the key functions of the robot system. Navigation means that the mobile robot obtains environmental information and its own position and posture state through sensors, and realizes autonomous movement to the destination in the environment of obstacles. The key and premise of navigation is positioning, which refers to determining the position and posture of the robot itself in the environment in real time. [0003] At present, most mobile robot positioning methods in unknown environments are based on the combination of track calculation and sensor acquisition of external information, that is to say, whenever the robot moves a small distance, it starts to build a local range map, through The sensor senses and de...

AI Technical Summary

Problems solved by technology

In an unknown environment, the incremental environmental mapping and self-localization of mobile robots is essentially a SLAM (Simultaneous Localization and Mapping, simultaneous localization and mapping) problem. The current mainstream method is a probability-based method, and its fundamental idea is to regard it as It is a Bayesian evaluation problem. Through the sensor observation data, motion and perception model, it uses the prediction-update repeated steps to estimate the pose s of the robot and the feature position λ of the robot's environment. It is a state reliability optimization problem. But this method is less accurate

Images