Distance and course measurement method based on laser radar

Abstract

The invention relates to a distance and course measurement method based on a laser radar. According to the method, on the basis of 16-line laser radar, a distance between wall surfaces on the two sides of the robot in a long corridor environment and a yaw angle of the robot in the advancing direction are measured. The method comprises the following steps of 1) installing a laser radar sensor on a rotary holder of a robot, and scanning to obtain three-dimensional point cloud data of an environment; 2) extracting features required by measurement from the scanned three-dimensional point cloud data, wherein the specific operation comprises steps of performing straight-through filtering, statistical filtering, European clustering and random sampling consistency segmentation on the obtained three-dimensional point cloud, and calculating the centroid of the clustered point cloud cluster; and 3) according to the obtained centroid and plane parameters of the point cloud cluster, calculating a distance from the laser radar to the wall surfaces on the two sides of the corridor and the yaw angle of the robot. According to the method, requirements of the robot on the distance to the wall surfaces on the two sides and the yaw angle in autonomous navigation in the long corridor environment are met, and autonomous navigation of the robot in a specific scene is realized through provided data.

Description

technical field [0001] The present invention relates to the technical field of environment perception, in particular to the measurement of the distance between walls on both sides and the calculation of the yaw angle in a long corridor environment based on laser radar. Background technique [0002] As an active measurement sensor, lidar can accurately obtain the depth information of the scene, and has good anti-interference ability. It has great application value in the fields of robot navigation and engineering survey. In the long corridor environment, due to dim light and sparse environmental texture features, positioning methods based on vision or laser cannot extract effective environmental feature information, and positioning is prone to failure or large drift. [0003] Aiming at these environmental conditions, a lightweight distance and yaw angle measurement method is proposed to ensure the autonomous navigation of the robot by providing the distance from the robot to ...

AI Technical Summary

Problems solved by technology

In the long corridor environment, due to the dim light and sparse environmental texture features, the positioning method based on vision or laser cannot extract effective environmental feature information, and the positioning is prone to failure or large drift.

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