Improved method of RGB-D-based SLAM algorithm

An algorithm and motion technology, applied in the field of mobile robot research, can solve problems such as large errors and low efficiency

Inactive Publication Date: 2015-08-19
XIDIAN UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to provide an improved method of RGB-D-based SLAM algorithm that enhances feature mat

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  • Improved method of RGB-D-based SLAM algorithm
  • Improved method of RGB-D-based SLAM algorithm
  • Improved method of RGB-D-based SLAM algorithm

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Embodiment 1

[0136] In the embodiment of the present invention, the running hardware environment is a Lenovo notebook computer Lenovo ideapad Y471A, Inter Core i5-2410M CPU2.30GHz dual-core four-thread 2.3GHz processor, three-level cache is 3M and 6M, and 4G memory.

[0137] The operating system of the algorithm is Ubuntu 12.04, the kernel version is 3.5.0-54-generic, all the algorithms of the present invention are compiled by gcc 4.6.3, and the optimization level is three levels (-O3).

[0138] When evaluating the RGB-D SLAM algorithm, it can be considered from two aspects of efficiency and accuracy. If the optimized algorithm takes less time or has higher precision and smaller error than the original algorithm, the optimization is considered correct. In order to verify the proposed improved method, the present invention tests and compares the algorithms before and after improvement from the aspects of efficiency and precision, and evaluates the algorithms according to the comparison resu...

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Abstract

Disclosed in the invention is an improved method of a RGB-D-based simultaneously localization and mapping (SLAM) algorithm. The method comprises two parts: a front-end part and a rear-end part. The front-end part is as follows: feature detection and descriptor extraction, feature matching, motion conversion estimation, and motion conversion optimization. And the rear-end part is as follows: a 6-D motion conversion relation initialization pose graph obtained by the front-end part is used for carrying out closed-loop detection to add a closed-loop constraint condition; a non-linear error function optimization method is used for carrying out pose graph optimization to obtain a global optimal camera pose and a camera motion track; and three-dimensional environment reconstruction is carried out. According to the invention, the feature detection and descriptor extraction are carried out by using an ORB method and feature points with illegal depth information are filtered; bidirectional feature matching is carried out by using a FLANN-based KNN method and a matching result is optimized by using homography matrix conversion; a precise inliners matching point pair is obtained by using an improved RANSAC motion conversion estimation method; and the speed and precision of point cloud registration are improved by using a GICP-based motion conversion optimization method.

Description

technical field [0001] The invention relates to the field of mobile robot research, in particular to an improved method of an RGB-D-based SLAM algorithm. Background technique [0002] In order to navigate in an unknown environment, a mobile robot needs to build a map of the environment and locate itself in the map at the same time. The process of solving these two problems at the same time is called simultaneous localization and map construction (Simultaneously Localization And Mapping, SLAM) . When the robot is in an outdoor environment, this problem can be solved by high-precision GPS. However, when the robot is in an indoor environment, or when the GPS is not accurate enough to meet the high-precision requirements, or when the environment in which the robot is in a confidential environment, people must use other methods to accurately estimate the robot's position and build a map of the environment at the same time. The SLAM problem is proposed under such a demand backgr...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/20
CPCG06T7/246G06T7/55G06T2207/10021G06T2207/20081G06T2207/30244
Inventor 张亮沈沛意朱光明宋娟刘强强
Owner XIDIAN UNIV
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