System and method for detecting boundary of working area based on vision, and machine equipment

A technology of working area and detection system, which is applied in the direction of instruments, computer components, two-dimensional position/channel control, etc., to achieve strong robustness

Pending Publication Date: 2019-06-07
BONGOS ROBOTICS SHANGHAI CO LTD
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AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems existing in the detection work area boundary scheme adopted by the existing autonomous working robots, a high-precision work area boundary detection scheme is needed

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  • System and method for detecting boundary of working area based on vision, and machine equipment
  • System and method for detecting boundary of working area based on vision, and machine equipment
  • System and method for detecting boundary of working area based on vision, and machine equipment

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Embodiment Construction

[0035] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific illustrations.

[0036] This solution is based on neural network technology to perform image semantic segmentation on the video images collected by the camera, so as to realize accurate perception of the environment and identify the boundaries of the working area.

[0037] According to this principle, this program builds a corresponding neural network model, and at the same time obtains real working scene pictures to form a corresponding training data set, and then uses the training data set to independently train and learn the formed neural network model, extracts and learns the corresponding The characteristics of the working area, thus obtaining the trained deep neural network model.

[0038] In application, the deep neural network model obtained by training ...

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Abstract

The invention discloses a vision-based working area boundary detection system and method, and machine equipment, and the method comprises the steps: carrying out the autonomous training learning of aconstructed neural network model based on a training data set, and extracting and learning corresponding working area features; and then carrying out real-time image semantic segmentation on the acquired video image by the neural network model subjected to training learning based on the working area characteristics extracted by the training learning, thereby perceiving the environment and identifying the boundary of the working area. According to the scheme provided by the invention, based on a neural network machine vision technology, the boundary of the working area can be efficiently identified by extracting and learning the characteristics of the working area in the earlier stage, and the robustness on the change of environments such as illumination and the like is relatively high.

Description

technical field [0001] The invention relates to machine vision technology, in particular to a machine vision-based work area boundary detection technology. Background technique [0002] With the development and popularization of machine vision, more and more autonomous working robots use machine vision to perceive the surrounding environment and working areas, such as plant protection drones, logistics storage robots, power inspection robots, factory security robots, gardens Lawn mowing robot, etc. When these autonomous robots are working, due to technical limitations, the robots often drive out of specific work areas, causing certain risks and safety hazards to other areas. The main reason is that the existing machine vision technology cannot accurately detect the boundary of the working area in real time. [0003] Currently, machine vision technology is used to detect the boundary of the working area, and the main methods are color matching and shape segmentation. In th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/13
CPCG05D1/02G06T2207/10016G06T2207/20081G06T2207/20084G06T7/11G06T2207/10024G06V20/56G06V10/82G06V20/70G06T7/12G06T7/90G06V20/41
Inventor 吴一飞张伟鲍鑫亮
Owner BONGOS ROBOTICS SHANGHAI CO LTD
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