Bag of visual words-based closed-loop detection method for mobile robot maps

A mobile robot, closed-loop detection technology, applied in the field of map creation, can solve the problems of calculation accuracy, large data scale, wrong closed-loop detection results, etc., and achieve the effect of fast calculation speed and algorithm calculation speed.

Active Publication Date: 2018-04-06
HUNAN UNIV +1
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AI Technical Summary

Problems solved by technology

[0004] (1) SLAM generally operates in similar scenes, and similar scenes do not necessarily come from the same scene, which creates perceptual ambiguity, which will eventually lead to wrong closed-loop detection results
[0005] (2) When performing closed-loop detection, it is necessary to compare the current observation data with the processed and stored information to determine whether they are in the same scene, and the data that needs to be processed and stored increases with the increase in the running time o

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  • Bag of visual words-based closed-loop detection method for mobile robot maps
  • Bag of visual words-based closed-loop detection method for mobile robot maps
  • Bag of visual words-based closed-loop detection method for mobile robot maps

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Embodiment Construction

[0053] The present invention will be further described below in conjunction with accompanying drawing and embodiment

[0054] A method for detecting loop closures in a mobile robot map based on bag of visual words, comprising the following steps:

[0055] Step 1: Establishment of visual dictionary model;

[0056] Such as figure 1 As shown, the ORB feature points are first extracted from multiple images in the scene by offline training, and then trained into a tree-like visual dictionary, and the closed loop will be detected in real time during SLAM operation, and after obtaining the images currently observed by the robot, The corresponding dictionary vector is obtained by querying the established visual dictionary, and the dictionary vector corresponds to the scene description at the location of the image.

[0057] In the process of hierarchical quantification of image features, vocabulary generation is established on the basis of hierarchical K-Means clustering of features,...

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Abstract

The invention discloses a bag of visual words-based closed-loop detection method for mobile robot maps. The method comprises the following steps of: providing a visual dictionary-based image similarity detection algorithm, and taking the algorithm as a front end of closed-loop detection, namely, judging candidate closed-loop nodes through image similarity detection; and further determining the closed-loop nodes by adoption of a time constraint and space position verification method. A large number of experiments prove that the closed-loop detection method is capable of correctly detecting various different closed loops, is high in algorithm calculation speed, and is adaptive to relatively high instantaneity requirements, for the closed-loop detection part, of SLAM.

Description

technical field [0001] The invention belongs to the field of map creation, in particular to a method for detecting a closed loop of a mobile robot map based on a bag of visual words. Background technique [0002] In synchronous positioning and map creation SLAM, closed-loop detection refers to judging whether the robot is in a certain area visited before according to the information obtained by the sensor, or whether the current location of the robot is in the created map. corresponding description. In the SLAM method based on graph optimization, closed-loop detection is a very critical link. Correct closed-loop detection helps to correct the odometer error, so as to obtain a map with small error and consistent global information, but wrong closed-loop detection will increase Errors can even destroy the entire map. [0003] Loop closure detection is not only a focus of map creation in an unknown environment, but also a difficulty, mainly reflected in the following aspects:...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/28G06F18/22G06F18/23213
Inventor 余洪山孙健王磊刚谭磊孙炜朱江林鹏赖立海
Owner HUNAN UNIV
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