RGB-D visual odometry taking ground constraint into consideration in indoor environment

Abstract

The invention belongs to the field self-localization of a mobile robot, and particularly relates to RGB-D visual odometry taking ground constraint into consideration in an indoor environment. The method comprises: (1) in an indoor environment, collecting color image information and depth image information in the environment during a motion process of an RGB-D camera loaded on a mobile platform and marking adjacent frame images as Is and It; (2) performing solution through a reverse projection function [pi]-1 according to the depth image information to obtain three dimensional point cloud data Vs and Vt of the environment; and (3) extracting and matching ORB characteristics including extracting and matching characteristic points of RGB-D images through an ORB algorithm. Image pre-treatment including characteristic extraction and matching is completed through an ORB algorithm. Compared with SIFT and SURF algorithms, the ORB algorithm is accelerated by one order of magnitude. The point cloud ground is obtained through use of depth image detection and point set alignment is improved through use of ground information, thereby improving the estimation precision of motion transformation.

Description

technical field [0001] The invention belongs to the field of autonomous positioning of mobile robots, in particular to an RGB-D visual odometer method considering ground constraints in an indoor environment. Background technique [0002] In a navigation system, odometry is a method that uses sensor movement data to estimate the amount of change in robot position over time, and is often used in wheeled mobile robots. Traditional odometers use compass or encoders to achieve positioning by measuring the number of rotations of the wheels of a mobile robot. However, when the tires slip, there will be a large deviation that is difficult to eliminate, and due to the accumulation of errors over time, the odometer readings will become increasingly unreliable, which cannot meet the application scenarios that require high precision. Visual Odometry (VO, Visual Odometry) technology is a method of estimating the moving distance of the robot by using continuous image sequences. It can ob...

AI Technical Summary

Problems solved by technology

[0004] The RGB-D sensor is used to realize the visual odometry. Feature extraction and matching as the preprocessing steps of data association have a great impact on the solution speed of the system. Traditional algorithms usually use SIFT and SURF algorithms, which are slow and difficult to meet the real-time output of the odometer. Requirements; Since the traditional algorithm uses the corresponding feature point set obtained through matching to directly solve the motion transformation matrix, without adding environmental structural feature geometric constraints, the accuracy of the algorithm needs to be further improved

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