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Loading and unloading position detection method, device and system based on binocular depth camera
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A technology of depth camera and detection method, which is applied in computer components, character and pattern recognition, image data processing, etc., can solve the problem of increasing the cost of unmanned driving operations, the high price of laser scanning devices, and the great harm of red light to human eyes, etc. problems, to achieve the effect of improving the level of automation and work efficiency, avoiding large interference from human factors, and high reliability
Pending Publication Date: 2021-04-06
江苏智库智能科技有限公司
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In this mode, the driver of the unmanned vehicle needs to observe the visible red light falling on the unmanned vehicle with naked eyes. When the frame of the unmanned vehicle is higher than the driver's observation range, the driver needs to use the auxiliary platform to observe the scanning line. It brings inconvenience to the implementation of this mode; at the same time, it can be seen that the red light is more harmful to the human eye
In addition, since the laser scanning device is relatively expensive, the cost of unmanned operation is greatly increased.
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Embodiment 1
[0058] Such as figure 1 As shown, the present invention provides a method for detecting loading and unloading positions based on a binocular depth camera, comprising the following steps:
[0059] Step 1: Collect images and depths of the objects to be detected in the loading and unloading area, the objects to be detected include unmanned vehicles and goods;
[0060] Step 2: De-distorting the image based on the distortion parameters of the binocular depth camera;
[0061] Step 3: using the trained deep learning model to identify the image after de-distortion processing, and obtain the pixel coordinates of the center point of the object to be detected;
[0062] Step 4: Calculate the spatial three-dimensional coordinates of the object to be detected according to the distortion parameter, the collected depth, and the obtained pixel coordinates of the central point;
[0063] Step 5: Construct a coordinate error model of the object to be detected according to the real three-dimensi...
Embodiment 2
[0093] Such as image 3 As shown, the embodiment of the present invention provides a loading and unloading position detection device, including a binocular depth camera installed above the loading and unloading area, and the device includes the following modules:
[0094] The data collection module is used to collect images and depths of objects to be detected in the loading and unloading area;
[0095]A distortion processing module, configured to perform de-distortion processing on the image based on the distortion parameters of the binocular depth camera;
[0096] The center coordinate module is used to identify the image after de-distortion processing by using the trained deep learning model, and obtain the pixel coordinates of the center point of the object to be detected;
[0097] A coordinate calculation module, configured to calculate the spatial three-dimensional coordinates of the object to be detected according to the distortion parameter, the acquired depth, and th...
Embodiment 3
[0101] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, wherein, when the program is executed by a processor, the steps of the method described in the first embodiment are implemented.
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Abstract
The invention provides a loading and unloading position detection method based on a binocular depth camera, and belongs to the technical field of position detection, and the method comprises the following steps: collecting the image and depth of a to-be-detected object in a loading and unloading region; based on distortion parameters of a binocular depth camera, performing distortion removing processing on the image; utilizing a trained deep learning model to identify the image after distortioneliminationprocessing, and obtaining a central point pixel coordinate of the to-be-detected object; calculating spatial three-dimensional coordinates of the to-be-detected object according to the distortion parameters, the acquired depth and the acquired pixel coordinates of the central point; constructing a coordinate error model of the to-be-detected object according to the real space three-dimensional coordinates of the to-be-detected object, the calculated space three-dimensional coordinates and error terms influencing the coordinate precision; and according to the coordinate error model, obtaining an error-corrected spatial three-dimensional coordinate. According to the invention, the automation level, the working efficiency and the safety of loading and unloading position detection can be improved.
Description
technical field [0001] The invention relates to the technical field of unmanned vehicle loading and unloading position detection, in particular to a binocular depth camera-based loading and unloading position detection method, device and system. Background technique [0002] With the increasing development of automation technology, modern industry has put forward higher and higher demands on the efficiency and safety of driving. Crane has gradually evolved from a single handling tool to an important part of automated and flexible production. Fully automatic crane will become a necessary executive component in the modern production and manufacturing execution managementsystem. It uses advanced computer control technology to detect materials according to the received upper-level network operation instructions, and accurately locate the various mechanisms of the crane to complete unloading and loading. Materials, storage and other operations, to achieve fully automatic storag...
Claims
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