Obstacle detection method and device and storage medium

An obstacle detection and obstacle technology, applied in the field of obstacle detection, can solve the problem of low application deployment efficiency, achieve the effect of improving application deployment efficiency and avoiding the training of deep learning models

Active Publication Date: 2020-08-28
知行汽车科技(苏州)股份有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] This application provides an obstacle detection method, device and stora

Method used

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  • Obstacle detection method and device and storage medium
  • Obstacle detection method and device and storage medium
  • Obstacle detection method and device and storage medium

Examples

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[0046] The specific implementation of the present application will be described in further detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the application, but are not used to limit the scope of the application.

[0047] figure 1 Is a schematic structural diagram of an obstacle detection device 100 provided by an embodiment of the present application, such as figure 1 As shown, the device at least includes: a control component 110 and a laser detection component 120 communicatively connected with the control component 110.

[0048] The laser detection assembly 120 is installed on a mobile carrier. A mobile carrier refers to a carrier that moves on a moving plane at a certain speed. Optionally, the mobile carrier may be a vehicle or a cleaning robot, and this embodiment does not limit the implementation of the mobile carrier here.

[0049] Optionally, the laser detection component 120 may be a lidar, a stereo ...

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Abstract

The invention relates to an obstacle detection method and device and a storage medium, and belongs to the technical field of computers. The method comprises the steps: obtaining point cloud data collected by a laser detection module in a process that a moving carrier moves on a moving plane; wherein the point cloud data comprises three-dimensional coordinates of sampling points and reflection signal intensity; projecting the sampling points to a two-dimensional plane according to the three-dimensional coordinates by taking a height direction perpendicular to the moving plane as a projection direction to obtain a bird's-eye view; determining pixel information of each pixel point in the aerial view according to the point cloud data, wherein the pixel information of each pixel point comprisesa first pixel value, a second pixel value and a third pixel value; detecting obstacles in the collection range according to pixel information in the aerial view; the problem of low application deployment efficiency can be solved; by processing the point cloud data with huge data volume into the two-dimensional image data, a large amount of point cloud data does not need to be collected to train adeep learning model, and the application deployment efficiency is improved.

Description

technical field [0001] The present application relates to an obstacle detection method, device and storage medium, belonging to the field of computer technology. Background technique [0002] With the rapid development of automatic driving technology, during the process of automatic driving, the automatic driving system needs to obtain the information of surrounding obstacles in order to achieve the purpose of driving safely on the road. [0003] The existing obstacle detection method obtains the point cloud information of the surrounding environment through laser radar scanning ranging, and extracts the key points and features of the point cloud through calculation to obtain training samples; through BP neural network, SVM and other machine learning or deep learning Methods A model for identifying obstacles was built, and the types of obstacles around the vehicle were identified through the model. [0004] However, machine learning or deep learning models need to consume a...

Claims

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Application Information

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IPC IPC(8): G06K9/00G01S17/931G01S17/89
CPCG01S17/931G01S17/89G06V20/58
Inventor 王泽荔顾晨益王文爽陈伟
Owner 知行汽车科技(苏州)股份有限公司
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