Method for detecting dangerous goods by explosive-handling robot based on self-adaptive spatial feature fusion

An EOD robot and spatial feature technology, applied in the field of visual inspection, can solve problems such as low detection accuracy and slow detection speed, achieve good robustness, reduce deployment requirements, and reduce the amount of memory

Pending Publication Date: 2021-11-16
SHANGHAI NORMAL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to overcome the defects that the existing deep learning algorithm used for the detection of dangerous objects in explosive robots has no dangerous object data sets available, the detection

Method used

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  • Method for detecting dangerous goods by explosive-handling robot based on self-adaptive spatial feature fusion
  • Method for detecting dangerous goods by explosive-handling robot based on self-adaptive spatial feature fusion
  • Method for detecting dangerous goods by explosive-handling robot based on self-adaptive spatial feature fusion

Examples

Experimental program
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Example Embodiment

[0036] Example 1

[0037] An explosion-proof robot-based dangerous product detection method based on adaptive spatial feature fusion, applied to electronic devices, including the following steps:

[0038] (1) Construct a dangerous product data set:

[0039] (1.1) Grab the data set from the Internet to obtain the initial dangerous data set, specifically: using the Python language SCRAPY framework to climb data on the Internet website by specifying the keyword, the initial danger data set;

[0040] (1.2) After cleaning the initial hazard data set, it will be labeled, specifically: After using the structural similarity index removal of the repetitive data in the initial danger data set, use the Labelimg visualization graphic labeling software, according to the data of Pasal VOC2007 Set of formats labels and store the generated XML file;

[0041] (1.3) Data sets of data sets to the label are highly dangerous, and the data sets are used to enhance the data sets of translation, mirror f...

Example Embodiment

[0055] Example 2

[0056] An electronic device comprising one or more processors, one or more memories, one or more programs, a data grab device for grabbing data from the Internet and an image acquisition device for obtaining a photo to be detected;

[0057] One or more programs are stored in the memory, and when one or more programs are executed by the processor, the electronic device performs an explosion-proof robot-based risk-proof robot based on adaptive spatial feature fusion as described in Example 1.

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Abstract

The invention discloses a method for detecting dangerous goods by an explosive-handling robot based on self-adaptive spatial feature fusion, and the method comprises the steps: capturing data from the Internet to obtain an initial hazardous article data set, cleaning the initial hazardous article data set, then marking the initial hazardous article data set, and finally carrying out the data enhancement of the marked data set, thereby obtaining a hazardous article data set; using a dangerous object data set to training a dangerous object detection model, wherein the training process is the process of taking an object image of a known category as input, taking the probability of the corresponding category of the object as theoretical output and continuously adjusting model parameters, wherein the training termination condition is that the upper limit of the training frequency is reached, and the dangerous goods detection model takes MobileNetV3 as a backbone extraction network; adopting a YOLOV4 model of an ASFF feature fusion strategy; and obtaining a picture of to-be-detected goods collected by the explosive ordnance disposal robot, and inputting the picture into the dangerous goods detection model to obtain the category of the to-be-detected goods. The method of the invention has the advantages of high accuracy and efficiency of detecting the dangerous goods and good robustness.

Description

technical field [0001] The invention belongs to the technical field of visual detection, and relates to a dangerous goods detection method of an explosion-proof robot based on adaptive spatial feature fusion and its application. Background technique [0002] In recent years, robot technology has advanced by leaps and bounds, and robots have been used in industrial production, rescue and disaster relief and other fields. EOD robots, as robots in the security field, have attracted a lot of attention. The EOD robots currently in use mainly rely on the video images returned by the robot's computer vision system, and then the EOD personnel remotely control the EOD robots through keyboards or remote controls to complete operations such as grasping, transferring, and detonating explosives. The efficiency and efficiency will be affected by factors such as the quality of the returned video image, the proficiency of the EOD personnel on the equipment, and the time error between the re...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/00G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/24G06F18/253G06F18/214
Inventor 安康李国承杜晓鹏方祖华方厚招
Owner SHANGHAI NORMAL UNIVERSITY
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