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A ground classification method and system for field robots based on a small number of annotations

A classification method and robot technology, applied in the computer field, can solve problems such as misclassification and insufficient utilization of spatial smoothness

Active Publication Date: 2020-12-25
合肥中科立恒智能科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, existing semi-supervised learning methods do not fully exploit spatial smoothness, especially in robotic ground classification, resulting in a large number of misclassifications

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  • A ground classification method and system for field robots based on a small number of annotations
  • A ground classification method and system for field robots based on a small number of annotations
  • A ground classification method and system for field robots based on a small number of annotations

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Embodiment Construction

[0054] In order to further illustrate the features of the present invention, please refer to the following detailed description and accompanying drawings of the present invention. The accompanying drawings are for reference and description only, and are not intended to limit the protection scope of the present invention.

[0055] Such as figure 1 As shown, this embodiment discloses a field robot ground classification method based on a small number of annotations. A vibration sensor and an image acquisition device are installed on the robot body, including the following steps S1 to S7:

[0056] S1. Obtain the vibration signal collected by the vibration sensor and the ground image signal collected by the image acquisition device, and obtain the vibration frame set and the ground image signal set;

[0057] It should be noted that the vibration sensor is used to detect vibration signals perpendicular to the ground. The image acquisition device can use a camera with the camera len...

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Abstract

The invention discloses a field robot ground classification method and system based on a small number of labels, belonging to the field of computer technology, by corresponding the vibration signal collected by a vibration sensor with the ground image signal collected by an image collection device, and manually identifying the ground image signal. The corresponding real ground type is used to label the vibration signal, and the labeled samples and unlabeled samples are obtained to train the support vector machine to prevent certain types of samples from lacking labels, and at the same time make better use of the spatial smoothness assumption to improve classification accuracy Spend. The sample classification of the invention well reflects the actual situation of data classification, and the model is trained by using the classified data, which improves the accuracy of semi-supervised classification.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a field robot ground classification method and system based on a small number of labels. Background technique [0002] How to utilize massive amounts of data is an important task facing current machine learning. The traditional support vector machine is a supervised learning method that requires a large number of labeled samples for training. However, in practical applications, since most of the sample data that can be used is unlabeled, and there are fewer labeled sample points, if only these few labeled samples are used, it will result in information that exists in a large number of location-labeled samples. was lost. Therefore, some scholars have proposed a method of semi-supervised learning, which is to use both unlabeled sample data knowledge and a small amount of labeled sample data knowledge in the semi-supervised learning process. However, existing semi-supervised lea...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/10G06F2218/12G06F18/2411G06F18/10G06F18/214
Inventor 吕文君康宇李泽瑞昌吉
Owner 合肥中科立恒智能科技有限公司