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Substation inspection robot obstacle discrimination method and system

An inspection robot and a discrimination method technology, applied in neural learning methods, three-dimensional object recognition, instruments, etc., can solve the problems of low obstacle discrimination accuracy, failure of working mechanism, easy to be affected by light factors, etc., to improve inspection Accuracy and work efficiency, improving feature extraction capabilities, reducing labor costs and human errors

Active Publication Date: 2021-05-11
CHENGDU UNIV OF INFORMATION TECH
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AI Technical Summary

Problems solved by technology

[0004] One of the purposes of the present invention is to provide a method for identifying obstacles of a substation inspection robot, which can solve the problem that the visible light image recognition module carried by the existing substation inspection robot is easily affected by illumination factors during inspection, resulting in accurate obstacle identification The problem of low rate or failure of working mechanism

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  • Substation inspection robot obstacle discrimination method and system
  • Substation inspection robot obstacle discrimination method and system
  • Substation inspection robot obstacle discrimination method and system

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Embodiment 1

[0044] refer to figure 1 , which is a schematic structural diagram of an obstacle discrimination system for a substation inspection robot in this embodiment. Specifically, the system includes:

[0045]Obstacle discrimination model building module 1 is used to obtain the original 3D lidar point cloud data around the inspection robot in the substation scene, and extract part of the original point cloud data according to the ROI area, and then convert the three-dimensional original point cloud data into two-dimensional original points After the cloud bird's-eye view is input into the deep convolutional neural network, the stochastic gradient descent algorithm is used to train the deep convolutional neural network model to obtain the obstacle discrimination model;

[0046] In this embodiment, the obstacle discrimination model building module 1 also includes an SSD network optimization unit, which is used to add DenseNet dense blocks to the VGG-16 backbone network in the SSD networ...

Embodiment 1

[0057] Based on the system of Embodiment 1, this embodiment discloses an obstacle discrimination method for a substation inspection robot, refer to figure 2 , including the following steps:

[0058] S1: Obtain the original 3D lidar point cloud data around the inspection robot in the substation scene, and extract part of the original point cloud data according to the ROI area, and then convert the three-dimensional original point cloud data into a bird's-eye view of the original two-dimensional point cloud, and then input the deep convolution In the neural network, the stochastic gradient descent algorithm is used to train the deep convolutional neural network model to obtain the obstacle discrimination model;

[0059] Specifically, in this embodiment, the 3D lidar point cloud data of different scenes in the substation and the camera photos corresponding to each frame of point cloud are collected by the substation inspection robot, and the 3D original point cloud data is conve...

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Abstract

The present invention provides a method and system for discriminating obstacles of a substation inspection robot. The method includes the following steps: S1: Obtain 3D laser radar original point cloud data around the substation scene point inspection robot, and extract part of the original point cloud data according to the ROI area, Then convert the 3D original point cloud data into a bird's-eye view of the 2D original point cloud and input it into the deep convolutional neural network, use the stochastic gradient descent algorithm to train the deep convolutional neural network model, and obtain the obstacle discrimination model; S2: Real-time acquisition Point cloud data to be detected, and converting the point cloud data to be detected into a bird's-eye view of the point cloud to be detected; S3: Input the bird's-eye view of the point cloud to be detected after normalization processing into the obstacle discrimination model, and obtain The category information of the obstacle. This method is not limited by light conditions, and can realize the inspection robot to work at night, making it possible for the substation inspection robot to perform round-the-clock inspections.

Description

technical field [0001] The invention belongs to the technical field of power inspection equipment for substations, and in particular relates to an obstacle discrimination method and system for a substation inspection robot. Background technique [0002] Smart grid is the trend and direction of power grid development, and smart substation is the substation link of smart grid, which is an important foundation and support for a strong smart grid. Due to the large number of high-voltage equipment in the power place of the substation and the complex environment, regular inspections are required to ensure power safety. At present, most substations still use manual inspections. With the continuous development of robot technology, more and more substations have begun to use inspections. Robot inspection and automation technology replace traditional manual work, which can reduce labor costs. However, substation roads are narrow and there are often obstacles that affect robot inspect...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/647G06V20/00G06V10/25G06N3/045G06F18/241G06F18/253
Inventor 朱明张葛祥杨强王恒
Owner CHENGDU UNIV OF INFORMATION TECH
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