A loopback detection method based on a convolutional neural network and ORB features

A convolutional neural network and detection method technology, applied in the field of intelligent mobile robots, can solve the problems of slow detection speed, low detection discrimination of bag-of-words method, and affect the real-time performance and accuracy of SLAM algorithm, so as to reduce false matching Probability, the effect of increasing speed and accuracy
CN109934857AActive Publication Date: 2019-06-25DALIAN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
DALIAN UNIV OF TECH
Publication Date
2019-06-25

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Abstract

The invention discloses a loopback detection method based on a convolutional neural network and ORB features. The method comprises the following steps: adding a new image i into an image sequence; Extracting feature vectors of the image i and other images in the image sequence by using a convolutional neural network, and calculating the similarity of other chords; Carrying out ORB feature extraction on the image i and the image j of which the similarity is greater than a threshold value; And carrying out feature matching on the image i and the image j, and if the correct logarithm of the finally matched feature points of the two images is greater than a set threshold value, considering that loop-back occurs. Due to the fact that the convolutional neural network is used for replacing a traditional word bag method, the speed and accuracy of loopback detection are improved. According to the invention, the convolutional neural network and ORB features are combined, so that the mismatchingprobability is reduced.
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Description

technical field

[0001] The invention belongs to the field of intelligent mobile robots, in particular to a loop detection method based on convolutional neural network and ORB features. Background technique

[0002] At this stage, autonomous driving technology is very hot, and people are looking forward to the arrival of the era of intelligent transportation. For the research of unmanned driving, the cost of direct real vehicle test is too high and the risk is relatively high. Therefore, major university-level scientific research institutions prefer to use low-cost wheeled mobile robots for scientific research, and then graft the research results to the real car. For an intelligent mobile robot, it mainly needs to have the following basic functions:

[0003] Positioning: The robot must be able to accurately determine its own position information by relying on the sensors it carries;

[0004] Navigation: The robot can smoothly reach the designated location from the starting...

Claims

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