Automatic docking and loading system and method for transport vehicle and truck, and computer storage medium

Abstract

The present invention relates to the field of vehicle driving, and provides an automatic docking and loading system, method and computer storage medium for a transport vehicle and a truck, wherein the system includes a parking guidance detection subsystem, a hoisting module positioning detection subsystem and a control subsystem for controlling a manipulator of the crane, wherein the parking guidance detection subsystem includes a monitoring camera, a processor, a display, a 16-line laser radar for collecting three-dimensional contour data of the transport vehicle body and a first near-infrared camera for acquiring an image of the transport vehicle; the hoisting module positioning detection subsystem includes a second near-infrared camera, a near-infrared light source, a laser ranging sensor, a hoisting module target and a vehicle target; the control subsystem controls the manipulator to load and unload the hoisting module according to the data of the parking guidance detection subsystem and the hoisting module positioning detection subsystem. The present invention can realize auxiliary parking guidance, hoisting module positioning detection and automatic operation control of a truck.

Description

Technical Field

[0001] The present invention relates to the field of vehicle driving, and in particular to an automatic docking and loading system and method for a transport vehicle and a truck, and a computer storage medium. Background Art

[0002] As labor costs continue to rise, vehicle logistics companies are in urgent need of strengthening innovation and reform in reducing operating costs, improving operating efficiency, and reducing labor intensity. However, the docking and loading of transport vehicles and trucks is generally done manually, which cannot achieve automated docking and loading and unloading of goods, resulting in high labor costs and high labor intensity. Summary of the invention

[0003] In view of the above problems, the present invention provides a system and method for automatic docking and loading of a transport vehicle and a truck, and a computer storage medium.

[0004] The purpose of the present invention is achieved by the following technical solutions:

[0005] The first aspect of the present invention provides an automatic docking and loading system for a transport vehicle and a truck, wherein both the transport vehicle and the truck are provided with a hoisting module, and the truck is also provided with a crane, wherein the system comprises a parking guidance detection subsystem, a hoisting module positioning detection subsystem, and a control subsystem for controlling a manipulator of the crane, wherein the parking guidance detection subsystem comprises a monitoring camera, a processor, a display, a 16-line laser radar for collecting three-dimensional contour data of the transport vehicle, and a first near-infrared camera for acquiring an image of the transport vehicle, wherein the 16-line laser radar, the first near-infrared camera, the monitoring camera, and the display are all connected to the processor;

[0006] The processor performs data fusion processing on the three-dimensional contour data of the vehicle body and the image of the transport vehicle captured by the first near-infrared camera to obtain real-time position and distance information of the transport vehicle relative to the cargo truck, and determines guidance data according to the real-time position and distance information, combines the guidance data with the real-time monitoring image captured by the monitoring camera, and sends the guidance data to the display for display, thereby guiding the transport vehicle to park within a specified range of the cargo truck;

[0007] The processor also acquires the current position and distance information of the transport vehicle relative to the truck according to the current three-dimensional contour data of the vehicle body and the current transport vehicle image when the transport vehicle is parked within the specified range of the truck, and sends the current position and distance information to the control subsystem;

[0008] The hoisting module positioning detection subsystem includes a second near-infrared camera, a near-infrared light source, a laser ranging sensor, a hoisting module target and a vehicle target, and the second near-infrared camera and the laser ranging sensor are both connected to the control subsystem;

[0009] The second near-infrared camera is used to photograph the hoisting module, the hoisting module target and the vehicle target to obtain photographed images;

[0010] The control subsystem calculates and analyzes the captured image to obtain the real-time position information of the hoisting module, and controls the manipulator to load and unload the hoisting module according to the current position and distance information, the sensing information of the laser ranging sensor, and the real-time position information.

[0011] According to an achievable method of the first aspect of the present invention, data fusion processing is performed on the three-dimensional contour data of the vehicle body and the image of the transport vehicle collected by the first near-infrared camera to obtain real-time position and distance information of the transport vehicle relative to the truck, specifically including:

[0012] Performing interference background filtering on the three-dimensional contour data of the vehicle body;

[0013] Extracting a region of interest of the transport vehicle image captured by the first near-infrared camera, and extracting three-dimensional point cloud data corresponding to the 16-line laser radar scan in the region of interest;

[0014] The three-dimensional point cloud data is fused with the three-dimensional contour data of the vehicle body.

[0015] According to an achievable method of the first aspect of the present invention, the second near-infrared camera, the near-infrared light source, and the laser ranging sensor are arranged at the end of the crane in the form of an integral module, and the module for controlling the manipulator to load and unload the hoisting module includes:

[0016] Control the manipulator to take the hoisting module on the transport vehicle;

[0017] Controlling the manipulator to place the lifting module on the transport vehicle onto the truck;

[0018] Control the manipulator to take the lifting module on the truck;

[0019] The manipulator is controlled to place the lifting module on the truck onto the transport vehicle.

[0020] According to an achievable manner of the first aspect of the present invention, the controlling the manipulator to take the hoisting module on the transport vehicle specifically performs:

[0021] Calculate the coordinates of the position where the hoisting module is positioned and photographed on the transport vehicle according to the current position and distance information, and control the crane to move to a position corresponding to the coordinates of the position where the hoisting module is positioned and photographed;

[0022] Control the second near-infrared camera to take pictures and acquire images, and obtain the actual position of the hoisting module on the transport vehicle through image processing and calculation;

[0023] Control the crane to move to the actual position, receive the relative distance information of each point on the lifting module on the transport vehicle measured by the laser ranging sensor, calculate the inclination angle of the lifting module on the transport vehicle according to the plane relative position of each point, and position and dock the manipulator with the lifting module on the transport vehicle according to the inclination angle.

[0024] According to an achievable manner of the first aspect of the present invention, the controlling the manipulator to take the hoisting module on the transport vehicle further specifically executes: after positioning and docking, controlling the display to display a prompt message for prompting that automatic positioning of the hoisting module is completed.

[0025] According to an achievable manner of the first aspect of the present invention, both the first near-infrared camera and the second near-infrared camera are near-infrared cameras with a spectrum of 850 nm.

[0026] The second aspect of the present invention provides an automatic docking and loading method for a transport vehicle and a truck, wherein both the transport vehicle and the truck are provided with a hoisting module, and the truck is also provided with a crane, and a second near-infrared camera, a near-infrared light source, a laser ranging sensor, a hoisting module target and a vehicle target are installed at the end of the crane.

[0027] The method comprises the following steps:

[0028] The control subsystem receives the current position and distance information sent by the processor, wherein the processor receives the three-dimensional contour data of the transport vehicle collected by the 16-line laser radar and the image data of the transport vehicle acquired by the first near-infrared camera; the processor performs data fusion processing on the three-dimensional contour data of the vehicle body and the image data of the transport vehicle to obtain the real-time position and distance information of the transport vehicle relative to the truck; the processor determines the guidance data according to the real-time position and distance information, combines the guidance data with the real-time monitoring image collected by the monitoring camera, and sends it to the display for display; when the current real-time position and distance information is consistent with the real-time position and distance information obtained last time, the processor sends the current position and distance information to the control subsystem;

[0029] The control subsystem calculates the position coordinates of the hoisting module on the transport vehicle for positioning and photographing according to the current position and distance information, and controls the crane to move to a position corresponding to the position coordinates of the hoisting module for positioning and photographing;

[0030] The control subsystem controls the second near-infrared camera to photograph the hoisting module, the hoisting module target and the vehicle target, obtains the photographed images, and obtains the actual position of the hoisting module on the transport vehicle through image processing calculation;

[0031] The control subsystem controls the crane to move to the actual position, receives the relative distance information of each point on the lifting module on the transport vehicle measured by the laser ranging sensor, calculates the inclination angle of the lifting module on the transport vehicle according to the plane relative position of each point, and controls the manipulator to position and dock with the lifting module on the transport vehicle according to the inclination angle.

[0032] According to an achievable manner of the second aspect of the present invention, the processor performs data fusion processing on the vehicle body three-dimensional contour data and the transport vehicle image data, specifically including:

[0033] The processor performs interference background filtering on the three-dimensional contour data of the vehicle body;

[0034] The processor extracts a region of interest of the transport vehicle image captured by the first near-infrared camera, and extracts three-dimensional point cloud data corresponding to the 16-line laser radar scan in the region of interest;

[0035] The processor performs data fusion processing on the three-dimensional point cloud data and the three-dimensional contour data of the vehicle body.

[0036] According to an achievable manner of the second aspect of the present invention, the method further comprises the following steps:

[0037] The control subsystem controls the crane with the lifting module to move above the truck;

[0038] The control subsystem uses the second near-infrared camera to capture the vehicle target image of the truck, and calculates the plane positioning position of the hoisting module using the mutual relationship of the targets;

[0039] The control subsystem controls the crane to move above the plane positioning position of the lifting module;

[0040] The control subsystem controls the manipulator of the crane to place the lifting module to the plane positioning position of the lifting module.

[0041] A third aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the automatic docking and loading method of a transport vehicle and a truck is performed as described above.

[0042] The beneficial effects of the present invention are as follows: the present invention comprises a parking guidance detection subsystem, a hoisting module positioning detection subsystem and a control subsystem for controlling the manipulator of the crane to form a docking and loading system for a transport vehicle and a truck, which can realize auxiliary parking guidance, hoisting module positioning detection and automatic operation control of the truck. The docking and loading system and method for a transport vehicle and a truck of the present invention have the advantages of all-weather operation, rapid positioning, high-precision detection and automatic docking. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0044] Figure 1 It is a schematic diagram of the structural connection of an automatic docking and loading system between a transport vehicle and a truck according to an exemplary embodiment of the present invention;

[0045] Figure 2 is a schematic diagram of the installation position of a parking guidance detection subsystem according to an exemplary embodiment of the present invention;

[0046] Figure 3 is a schematic diagram of a detection range of a parking guidance detection subsystem according to an exemplary embodiment of the present invention;

[0047] Figure 4 is a schematic diagram of the installation position of a hoisting module positioning detection subsystem according to an exemplary embodiment of the present invention;

[0048] Figure 5 It is a flow chart of an automatic docking and loading method between a transport vehicle and a truck according to an exemplary embodiment of the present invention.

[0049] Reference numerals:

[0050] Parking guidance detection subsystem 1, lifting module positioning detection subsystem 2, control subsystem 3. DETAILED DESCRIPTION

[0051] The present invention is further described in conjunction with the following examples.

[0052] See also Figures 1 to 4 The first aspect of the present invention provides an automatic docking and loading system for a transport vehicle and a truck, wherein both the transport vehicle and the truck are provided with a lifting module, and the truck is also provided with a crane. According to the lifting radius of the crane, the length, width, and height of the transport vehicle, and the length, width, and height of the truck, two lifting modules are symmetrically installed on both sides of the rear of the transport vehicle, and the crane is installed at the rear of the truck.

[0053] The system includes a parking guidance detection subsystem 1, a hoisting module positioning detection subsystem 2, and a control subsystem 3 for controlling the manipulator of the crane. The parking guidance detection subsystem 1 includes a monitoring camera, a processor, a display, a 16-line laser radar for collecting the three-dimensional contour data of the transport vehicle, and a first near-infrared camera for acquiring an image of the transport vehicle. The 16-line laser radar, the first near-infrared camera, the monitoring camera, and the display are all connected to the processor;

[0054] The processor performs data fusion processing on the three-dimensional contour data of the vehicle body and the image of the transport vehicle captured by the first near-infrared camera to obtain real-time position and distance information of the transport vehicle relative to the cargo truck, and determines guidance data according to the real-time position and distance information, combines the guidance data with the real-time monitoring image captured by the monitoring camera, and sends the guidance data to the display for display, thereby guiding the transport vehicle to park within a specified range of the cargo truck;

[0055] The processor also obtains the current position and distance information of the transport vehicle relative to the truck according to the current three-dimensional contour data of the vehicle body and the current transport vehicle image when the transport vehicle is parked within the specified range of the truck, and sends the current position and distance information to the control subsystem 3;

[0056] The hoisting module positioning detection subsystem 2 includes a second near-infrared camera, a near-infrared light source, a laser ranging sensor, a hoisting module target and a vehicle target, and the second near-infrared camera and the laser ranging sensor are both connected to the control subsystem 3;

[0057] The second near-infrared camera is used to photograph the hoisting module, the hoisting module target and the vehicle target to obtain photographed images;

[0058] The control subsystem 3 obtains the real-time position information of the hoisting module based on the calculated analysis of the captured image, and controls the manipulator to load and unload the hoisting module based on the current position and distance information, the sensing information of the laser ranging sensor, and the real-time position information.

[0059] In this embodiment, since the rear of the transport vehicle is uneven and its volume is relatively large, the external feature information of the transport vehicle may change over time. In order to ensure that the automatic docking and loading system continues to operate stably without being disturbed by the external environment and to reduce hardware costs, the parking guidance detection subsystem 1 in this embodiment is combined with a 16-line laser radar, a first near-infrared camera and a surveillance camera, which can meet the requirements of working in all weather conditions and when the vehicle body may change.

[0060] In this embodiment, both the transport vehicle and the truck have lifting modules, wherein the lifting module of the transport vehicle has no cargo, while the lifting module of the truck has cargo. Since the lifting modules have a certain height difference, the heights taken by the near-infrared camera will be different. Therefore, it is necessary to shoot and identify the lifting modules, vehicle targets, and lifting module targets on the transport vehicle and the truck, and calculate the position parameters of the lifting modules in the manipulator coordinate system through the image recognition algorithm.

[0061] In one achievable manner, the three-dimensional contour data of the vehicle body and the image of the transport vehicle captured by the first near-infrared camera are subjected to data fusion processing to obtain real-time position and distance information of the transport vehicle relative to the truck, specifically including:

[0062] Performing interference background filtering on the three-dimensional contour data of the vehicle body;

[0063] Extracting a region of interest of the transport vehicle image captured by the first near-infrared camera, and extracting three-dimensional point cloud data corresponding to the 16-line laser radar scan in the region of interest;

[0064] The three-dimensional point cloud data is fused with the three-dimensional contour data of the vehicle body.

[0065] Among them, the three-dimensional data contour of the vehicle body obtained by the 16-line laser radar and the image of the transport vehicle collected by the near-infrared camera are used for data fusion. First, the near-infrared camera needs to be calibrated, and then the 16-line laser radar calibration and the near-infrared camera are calibrated jointly to obtain the calibration parameters and relative position relationship of the two, and then the data collected by the two are fused.

[0066] In one achievable manner, such as Figure 4 As shown, the second near-infrared camera, the near-infrared light source, and the laser ranging sensor are arranged at the end of the crane in the form of an integral module, and the module for controlling the manipulator to load and unload the crane includes:

[0067] Control the manipulator to take the hoisting module on the transport vehicle;

[0068] Controlling the manipulator to place the lifting module on the transport vehicle onto the truck;

[0069] Control the manipulator to take the lifting module on the truck;

[0070] The manipulator is controlled to place the lifting module on the truck onto the transport vehicle.

[0071] The controlling of the manipulator to take the hoisting module on the transport vehicle is specifically performed as follows:

[0072] Calculate the coordinates of the position where the hoisting module is positioned and photographed on the transport vehicle according to the current position and distance information, and control the crane to move to a position corresponding to the coordinates of the position where the hoisting module is positioned and photographed;

[0073] Control the second near-infrared camera to take pictures and acquire images, and obtain the actual position of the hoisting module on the transport vehicle through image processing and calculation;

[0074] Control the crane to move to the actual position, receive the relative distance information of each point on the lifting module on the transport vehicle measured by the laser ranging sensor, calculate the inclination angle of the lifting module on the transport vehicle according to the plane relative position of each point, and position and dock the manipulator with the lifting module on the transport vehicle according to the inclination angle.

[0075] Furthermore, the controlling the manipulator to take the hoisting module on the transport vehicle is further specifically performed by: after positioning and docking, controlling the display to display a prompt message for prompting that the automatic positioning of the hoisting module is completed.

[0076] Among them, the operation of placing the lifting module on the truck is as follows: first, obtain the lifting position of the lifting module. The position of the lifting module on the truck is fixed. Which lifting module is taken away and which lifting module is left is known, so the lifting position of the lifting module is obtained from the control subsystem 3. The lifting module on the transport vehicle is taken away, and the positioning position of the lifting module can be obtained, and then the control subsystem 3 is notified to execute the crane motion control to move the crane with the lifting module above the truck. Then, the vehicle target image is captured by the near-infrared camera under the crane, and the plane positioning position of the lifting module is calculated using the relationship between the targets. If the calculation accuracy is not satisfied, repeat the movement of the crane position, and then shoot the calculation with the camera. Until the accuracy meets the requirements, the automatic positioning of the lifting module is output on the display control interface, and manual confirmation is required for accuracy of the alignment. After confirming the accurate alignment, the automatic lifting module placement action is performed.

[0077] The lifting module of the truck has items that need to be carried out. The positioning operation of the lifting module on the truck is similar to the operation of taking the lifting module on the transport vehicle, except that the position data of the lifting module is obtained differently. First, the position data of the lifting module of the truck is obtained, and the coordinates of the position for positioning and photographing the lifting module are calculated based on the data, and the control subsystem 3 is notified to control the crane to move to the corresponding shooting position. Then, a near-infrared camera is used to take pictures to obtain images, and the precise position of the lifting module is calculated through image processing. The control subsystem 3 is notified again to control the crane to move to the corresponding position, which is also the working position of the laser ranging sensor. The relative distance information of each point on the lifting module is measured by the laser ranging sensor. According to the relative position of each point in the plane, the inclination angle of the lifting module is calculated, and the control subsystem 3 is notified again to control the crane to move to the corresponding position. At this time, the entire automatic docking process is completed, and the automatic positioning of the lifting module is output on the display and control interface. It is necessary to manually confirm whether the alignment is accurate. After confirming the accurate alignment, the automatic lifting module placement action is performed.

[0078] The operation of controlling the manipulator to place the lifting module on the truck to the transport vehicle is similar to the operation of placing the lifting module on the truck. The difference is that the data sources for obtaining the lifting position of the lifting module are different. Due to the placement position restriction of the lifting module on the transport vehicle, an avoidance position compensation operation is required. First, the material picking lifting position of the lifting module is obtained. The lifting module is taken away during the process of picking up the lifting module on the transport vehicle, and the inclination position of the material picking lifting can be obtained. The inclination position is used to guide the adjustment of the camera's posture so that the camera is level with the photographed surface to ensure the position accuracy obtained by the camera image processing. Due to the placement position restriction of the lifting module on the transport vehicle, the target is arranged below the lifting module. When the alignment action of the physical installation is completed, the lifting module will block the target. Therefore, in order to avoid this problem in actual processing, the software-assisted offset positioning method is adopted. First, align to the set offset position, and finally complete the alignment of the lifting module when it is placed by compensating the offset value.

[0079] In one achievable manner, the first near-infrared camera and the second near-infrared camera are both near-infrared cameras with a spectrum of 850 nm, and the near-infrared light source uses 850 nm near-infrared band fill light.

[0080] Since visible light cameras require visible light sources at night, the light sources of multiple transport vehicles will cause confusion. Infrared cameras use infrared imaging to identify at night, and the imaging accuracy of the transport vehicles is not high, the image contours are unclear, and they cannot be accurately positioned. The imaging quality accuracy of low-light imaging cameras is not high, and they cannot work and accurately position in completely dark scenes. This embodiment uses a near-infrared camera with a spectrum of 850nm, which can not only produce clear images under visible light, but also at night, through the near-infrared light source 850nm near-infrared band fill light, it can also produce clear images. This configuration can be used to capture images during the day and at night.

[0081] Among them, the 16-meter laser radar adopts the TOF full waveform solution, which can scan and detect the surrounding environment 360 degrees. When selecting the model of the 16-meter laser radar, according to the vehicle parking positioning measurement accuracy, the technical indicators to be considered include: scanning angle, scanning radius, measurement accuracy, angular resolution, measurement frequency and communication method.

[0082] Among them, the 16-line laser radar, the first near-infrared camera, and the monitoring camera are installed on the rear side of the truck. The installation direction is horizontal and the head-up view direction can capture the rear view image. The parking guidance detection subsystem 1 is installed at the following position: Figure 2 As shown. The 16-line laser radar, near-infrared camera, and surveillance camera are all required to be able to capture the entire transport vehicle and work within the field of view at all times.

[0083] Furthermore, the various parts of the parking guidance detection subsystem 1 can be assembled into a component, and a protective shell is installed on the outside to reduce the interference caused by the ambient temperature, sewage, and impurities during the driving of the truck, and improve the environmental adaptability of the parking guidance detection subsystem 1. In order to ensure that the 16-line laser radar and near-infrared camera can work normally in a low-temperature environment, a local heating module can be arranged in the parking guidance detection subsystem 1 to increase the ambient temperature inside the parking guidance detection subsystem 1.

[0084] In one possible implementation, the surveillance camera uses a day and night full-color surveillance camera, so that color surveillance can be performed 24 hours a day, even in dim light environments, and can automatically fill in the light in insufficient or no light conditions, so as to achieve real-time shooting of color surveillance dynamic images. The model of the day and night full-color surveillance camera can be selected according to color classification, clarity, effective distance, lens size, and focal length.

[0085] Among them, the hoisting module target refers to the target set on the hoisting module, and the vehicle target refers to the target set on the transport vehicle and the truck. In one feasible method, the target adopts a circular pattern, black and red are cycled at 90° intervals, and the diameter is 2cm to ensure sufficient recognition rate and recognition accuracy. The target is fixedly installed on the hoisting module, truck and transport vehicle by printing. In order to ensure its positioning accuracy, two targets are arranged on one side of each hoisting module. The position of the target on the truck and the transport vehicle is based on the installation hole of the hoisting module and is arranged on the same side as the target point on the hoisting module.

[0086] like Figure 5 As shown, the second embodiment of the present invention provides a method for automatic docking and loading between a transport vehicle and a truck, and the method relies on the above-mentioned automatic docking and loading system between a transport vehicle and a truck.

[0087] The transport vehicle and the truck are both provided with a hoisting module, and the truck is also provided with a crane, at the end of which a second near-infrared camera, a near-infrared light source, a laser ranging sensor, a hoisting module target and a vehicle target are installed.

[0088] The method comprises the following steps:

[0089] S1 control subsystem receives current position and distance information sent by processor, wherein the processor receives three-dimensional contour data of the transport vehicle collected by 16-line laser radar and image data of the transport vehicle acquired by the first near-infrared camera; the processor performs data fusion processing on the three-dimensional contour data of the vehicle body and the image data of the transport vehicle to obtain real-time position and distance information of the transport vehicle relative to the truck; the processor determines guidance data according to the real-time position and distance information, combines the guidance data with the real-time monitoring image collected by the monitoring camera, and sends it to the display for display; when the current real-time position and distance information is consistent with the real-time position and distance information obtained last time, the processor sends the current position and distance information to the control subsystem;

[0090] S2: the control subsystem calculates the position coordinates of the hoisting module on the transport vehicle for positioning and photographing according to the current position and distance information, and controls the crane to move to a position corresponding to the position coordinates of the hoisting module for positioning and photographing;

[0091] S3: the control subsystem controls the second near-infrared camera to photograph the hoisting module, the hoisting module target and the vehicle target, obtains the photographed images, and obtains the actual position of the hoisting module on the transport vehicle through image processing and calculation;

[0092] S4 The control subsystem controls the crane to move to the actual position, receives the relative distance information of each point on the lifting module on the transport vehicle measured by the laser ranging sensor, calculates the inclination angle of the lifting module on the transport vehicle according to the plane relative position of each point, and controls the manipulator to position and dock with the lifting module on the transport vehicle according to the inclination angle.

[0093] In one achievable manner, the processor performs data fusion processing on the vehicle body three-dimensional contour data and the transport vehicle image data, specifically including:

[0094] The processor performs interference background filtering on the three-dimensional contour data of the vehicle body;

[0095] The processor extracts a region of interest of the transport vehicle image captured by the first near-infrared camera, and extracts three-dimensional point cloud data corresponding to the 16-line laser radar scan in the region of interest;

[0096] The processor performs data fusion processing on the three-dimensional point cloud data and the three-dimensional contour data of the vehicle body.

[0097] Furthermore, the method further comprises the following steps:

[0098] The control subsystem controls the crane with the lifting module to move above the truck;

[0099] The control subsystem uses the second near-infrared camera to capture the vehicle target image of the truck, and calculates the plane positioning position of the hoisting module using the mutual relationship of the targets;

[0100] The control subsystem controls the crane to move above the plane positioning position of the lifting module;

[0101] The control subsystem controls the manipulator of the crane to place the lifting module to the plane positioning position of the lifting module.

[0102] A third aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the automatic docking and loading method of a transport vehicle and a truck is performed as described above.

[0103] The present invention comprises a parking guidance detection subsystem, a hoisting module positioning detection subsystem and a control subsystem for controlling the manipulator of the crane to form a docking and loading system for a transport vehicle and a truck, which can realize auxiliary parking guidance, hoisting module positioning detection and automatic operation control of the truck. The transport vehicle and truck docking and loading system and method of the present invention have the advantages of all-weather operation, rapid positioning, high-precision detection and automatic docking.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the essence and scope of the technical solution of the present invention.

Claims

1. An automatic docking and loading system for a transport vehicle and a truck, wherein both the transport vehicle and the truck are provided with a hoisting module, and the truck is also provided with a crane, wherein: The system includes a parking guidance detection subsystem, a hoisting module positioning detection subsystem, and a control subsystem for controlling the manipulator of the crane. The parking guidance detection subsystem includes a monitoring camera, a processor, a display, a 16-line laser radar for collecting three-dimensional contour data of the transport vehicle, and a first near-infrared camera for acquiring an image of the transport vehicle. The 16-line laser radar, the first near-infrared camera, the monitoring camera, and the display are all connected to the processor; The processor performs data fusion processing on the three-dimensional contour data of the vehicle body and the image of the transport vehicle captured by the first near-infrared camera to obtain real-time position and distance information of the transport vehicle relative to the cargo truck, and determines guidance data according to the real-time position and distance information, combines the guidance data with the real-time monitoring image captured by the monitoring camera, and sends the guidance data to the display for display, thereby guiding the transport vehicle to park within a specified range of the cargo truck; The processor also acquires the current position and distance information of the transport vehicle relative to the truck according to the current three-dimensional contour data of the vehicle body and the current transport vehicle image when the transport vehicle is parked within the specified range of the truck, and sends the current position and distance information to the control subsystem; The hoisting module positioning detection subsystem includes a second near-infrared camera, a near-infrared light source, a laser ranging sensor, a hoisting module target and a vehicle target, and the second near-infrared camera and the laser ranging sensor are both connected to the control subsystem; The second near-infrared camera is used to photograph the hoisting module, the hoisting module target and the vehicle target to obtain photographed images; The control subsystem calculates and analyzes the captured image to obtain the real-time position information of the hoisting module, and controls the manipulator to load and unload the hoisting module according to the current position and distance information, the sensing information of the laser ranging sensor, and the real-time position information; The three-dimensional contour data of the vehicle body and the image of the transport vehicle collected by the first near-infrared camera are subjected to data fusion processing to obtain the real-time position and distance information of the transport vehicle relative to the truck, specifically including: Performing interference background filtering on the three-dimensional contour data of the vehicle body; Extracting a region of interest of the transport vehicle image captured by the first near-infrared camera, and extracting three-dimensional point cloud data corresponding to the 16-line laser radar scan in the region of interest; The three-dimensional point cloud data is fused with the three-dimensional contour data of the vehicle body.

2. The automatic docking and loading system for a transport vehicle and a truck according to claim 1 is characterized in that: The second near-infrared camera, the near-infrared light source, and the laser ranging sensor are arranged at the end of the crane in the form of an integral module. The module for controlling the loading and unloading of the manipulator includes: Control the manipulator to take the hoisting module on the transport vehicle; Controlling the manipulator to place the lifting module on the transport vehicle onto the truck; Control the manipulator to take the lifting module on the truck; The manipulator is controlled to place the lifting module on the truck onto the transport vehicle.

3. The automatic docking and loading system for a transport vehicle and a truck according to claim 2 is characterized in that: The controlling the manipulator to take the hoisting module on the transport vehicle is specifically performed as follows: Calculate the coordinates of the position where the hoisting module is positioned and photographed on the transport vehicle according to the current position and distance information, and control the crane to move to a position corresponding to the coordinates of the position where the hoisting module is positioned and photographed; Control the second near-infrared camera to take pictures and acquire images, and obtain the actual position of the hoisting module on the transport vehicle through image processing and calculation; Control the crane to move to the actual position, receive the relative distance information of each point on the lifting module on the transport vehicle measured by the laser ranging sensor, calculate the inclination angle of the lifting module on the transport vehicle according to the plane relative position of each point, and position and dock the manipulator with the lifting module on the transport vehicle according to the inclination angle.

4. The automatic docking and loading system for a transport vehicle and a truck according to claim 3 is characterized in that: The controlling the manipulator to take the hoisting module on the transport vehicle further specifically executes: after positioning and docking, controlling the display to display a prompt message for prompting that the automatic positioning of the hoisting module is completed.

5. The automatic docking and loading system for a transport vehicle and a truck according to claim 1 is characterized in that: The first near-infrared camera and the second near-infrared camera both use near-infrared cameras with a spectrum of 850nm.

6. A method for automatically docking and loading a transport vehicle and a truck, wherein both the transport vehicle and the truck are provided with a hoisting module, and the truck is also provided with a crane, wherein: The end of the crane is equipped with a second near-infrared camera, a near-infrared light source, a laser ranging sensor, a hoisting module target and a vehicle target. The method comprises the following steps: The control subsystem receives the current position and distance information sent by the processor, wherein the processor receives the three-dimensional contour data of the transport vehicle collected by the 16-line laser radar and the image data of the transport vehicle acquired by the first near-infrared camera; the processor performs data fusion processing on the three-dimensional contour data of the vehicle body and the image data of the transport vehicle to obtain the real-time position and distance information of the transport vehicle relative to the truck; the processor determines the guidance data according to the real-time position and distance information, combines the guidance data with the real-time monitoring image collected by the monitoring camera, and sends it to the display for display; when the current real-time position and distance information are consistent with the real-time position and distance information obtained last time, the processor sends the current position and distance information to the control subsystem; The control subsystem calculates the position coordinates of the hoisting module on the transport vehicle for positioning and photographing according to the current position and distance information, and controls the crane to move to a position corresponding to the position coordinates of the hoisting module for positioning and photographing; The control subsystem controls the second near-infrared camera to photograph the hoisting module, the hoisting module target and the vehicle target, obtains the photographed images, and obtains the actual position of the hoisting module on the transport vehicle through image processing calculation; The control subsystem controls the crane to move to the actual position, receives the relative distance information of each point on the lifting module on the transport vehicle measured by the laser ranging sensor, calculates the inclination angle of the lifting module on the transport vehicle according to the plane relative position of each point, and controls the manipulator to position and dock with the lifting module on the transport vehicle according to the inclination angle.

7. The automatic docking and loading method of a transport vehicle and a truck according to claim 6, characterized in that: The processor performs data fusion processing on the vehicle body three-dimensional contour data and the transport vehicle image data, specifically including: The processor performs interference background filtering on the three-dimensional contour data of the vehicle body; The processor extracts a region of interest of the transport vehicle image captured by the first near-infrared camera, and extracts three-dimensional point cloud data corresponding to the 16-line laser radar scan in the region of interest; The processor performs data fusion processing on the three-dimensional point cloud data and the three-dimensional contour data of the vehicle body.

8. The automatic docking and loading method of a transport vehicle and a truck according to claim 6, characterized in that: The method further comprises the following steps: The control subsystem controls the crane with the lifting module to move above the truck; The control subsystem uses the second near-infrared camera to capture the vehicle target image of the truck, and calculates the plane positioning position of the hoisting module using the mutual relationship of the targets; The control subsystem controls the crane to move above the plane positioning position of the lifting module; The control subsystem controls the manipulator of the crane to place the lifting module to the plane positioning position of the lifting module.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the automatic docking and loading method between the transport vehicle and the truck is performed as described in any one of claims 6 to 8.

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