Method for carrying out pose optimization by utilizing Kalman filtering based on monocular SLAM algorithm

A Kalman filter, Kalman filter technology, applied in the field of computer vision

Active Publication Date: 2020-04-21
HARBIN INST OF TECH
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  • Abstract
  • Description
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Problems solved by technology

[0003]Because the map constructed by ORB-SLAM is sparse, and the sparse map can only be used for positioning, but only using ORB-SLAM to deal with positioning problems seems "overkill"

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  • Method for carrying out pose optimization by utilizing Kalman filtering based on monocular SLAM algorithm
  • Method for carrying out pose optimization by utilizing Kalman filtering based on monocular SLAM algorithm
  • Method for carrying out pose optimization by utilizing Kalman filtering based on monocular SLAM algorithm

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Embodiment Construction

[0030] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0031] figure 1 The overall block diagram of the monocular SLAM algorithm structure for the method described in the present invention, mainly follows the idea of ​​ORB-SLAM as a whole, and is divided into three threads: tracking, mapping and closed-loop. The present invention is mainly proposed for the pose optimization part of the monocular SLAM, with the purpose of reducing time-consuming and improving the overall real-time performance. For Kalm...

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Abstract

The invention provides a method for carrying out pose optimization by utilizing Kalman filtering based on a monocular SLAM algorithm. The method comprises the following steps: calculating update values of a rotation vector and a translation vector; and taking the update values of the rotation vector and the translation vector as optimized poses. According to the method, by modifying the pose optimization algorithm, a calculation amount and time consumption of ORB-SLAM are reduced, accurate and efficient positioning is provided for an upper-layer application, the calculation amount is reduced by replacing an original complex BA optimization method with a simple Kalman filtering method, and the time consumption of a pose optimization part is remarkably reduced. Compared with ORB-SLAM, the method provided by the invention has an advantage that real-time performance is improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a method for performing pose optimization based on a monocular SLAM algorithm and using a Kalman filter. Background technique [0002] Simultaneous Localization and Mapping (SLAM), proposed in 1988, has been a popular research direction in the field of mobile robots for more than 30 years. Today, SLAM algorithms are commonly used in mobile robot positioning in indoor scenes, and are also commonly used in small embedded systems. The ORB-SLAM proposed by Raul Mur-Artal et al. in 2015 is a SLAM algorithm based on the feature point method. The main body of ORB-SLAM inherits PTAM (Parallel Tracking and Mapping), which is used for monocular cameras. It is a peak of feature point SLAM. It has excellent loop detection and correction algorithms, and it is first proposed to use three parallel threads to complete SLAM, and The optimization algorithm is perfect, which m...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/20
CPCG01C21/20
Inventor 马琳吴婉晴王彬何晨光
Owner HARBIN INST OF TECH
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