Cargo carrying control method and device of carrying equipment and readable storage medium

Abstract

The invention discloses a cargo handling control method and device of handling equipment and a readable storage medium. The method comprises the steps that the working mode and equipment position information of the carrying equipment are obtained, the working mode at least comprises a loading mode and / or an unloading mode, and the equipment position information is used for indicating the position information of the carrying equipment; cargo position information is obtained, and the cargo position information is used for indicating the position information of the to-be-carried cargo; based on the working mode, the cargo position information and the equipment position information, determining a carrying route of carrying the to-be-carried cargo by the carrying equipment; and according to the carrying route, carrying equipment is controlled to carry the to-be-carried goods. The technical problem that the cargo carrying efficiency is low is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of cargo handling, and in particular to a control method, device, and readable storage medium for cargo handling by a handling device. Background Art

[0002] At present, in the environment of handling explosives, the importance of handling goods is self-evident. Any careless operation or negligence may lead to serious accidents, endangering the lives of people and property safety. Therefore, when handling explosives, it is necessary to strictly abide by the operating procedures and safety instructions to ensure the safe handling of goods.

[0003] In the related technologies, manual handling is mostly used. Since the objects being handled are dangerous and heavy, there is an urgent need to use handling robots to replace manual handling. This is expected to further improve the safety of the operation while ensuring the handling efficiency. At the same time, the function of the handling robots widely used in the market is only for loading, and cannot solve the problem of automatic unloading. Therefore, there is a technical problem of low handling efficiency of the goods being handled.

[0004] With respect to the above-mentioned technical problem of low efficiency in transporting goods, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a control method, device, and readable storage medium for a transporting device to transport goods, so as to at least solve the technical problem of low transport efficiency of the goods.

[0006] According to one aspect of an embodiment of the present invention, a control method for a handling device to carry goods is provided. The method may include: obtaining the working mode and device location information of the handling device, wherein the working mode includes at least a loading mode and / or an unloading mode, and the device location information is used to indicate the location information of the handling device; obtaining the cargo location information, wherein the cargo location information is used to indicate the location information of the cargo to be carried; determining the transportation route of the handling device to carry the cargo to be carried based on the working mode, the cargo location information and the device location information; and controlling the handling device to carry the cargo to be carried according to the transportation route.

[0007] Optionally, obtaining cargo location information includes: obtaining cargo warehouse image information, wherein the cargo warehouse image information is used to indicate image information of a cargo warehouse storing cargo to be transported; and extracting cargo location information from the cargo warehouse image information.

[0008] Optionally, based on the working mode, cargo location information and equipment location information, the transport route of the goods to be transported by the transport equipment is determined, including: in response to the working mode being the loading mode, obtaining the truck location information, wherein the truck location information is used to indicate the location information of the vehicle to be loaded; based on the truck location information, cargo location information and equipment location information, determining the transport route of the goods to be transported by the transport equipment.

[0009] Optionally, based on the truck location information, the cargo location information and the equipment location information, determining the transport route for the transport equipment to transport the cargo to be transported, including: extracting first cargo profile information from the cargo location information, wherein the first cargo profile information is used to indicate profile information of the cargo to be transported in the cargo warehouse; based on the first cargo profile information, the truck location information and the equipment location information, determining the transport route for the transport equipment to transport the cargo to be transported.

[0010] Optionally, based on the working mode, cargo location information and equipment location information, the transport route of the cargo to be transported by the transporting equipment is determined, including: in response to the working mode being the unloading mode, obtaining truck image information, wherein the truck image information is used to indicate image information of the interior of a compartment of the vehicle to be loaded; based on the truck image information, cargo location information and equipment location information, determining the transport route of the cargo to be transported by the transporting equipment.

[0011] Optionally, based on the truck image information, the cargo location information and the equipment location information, determining the transport route of the cargo to be transported by the transport equipment, including: extracting second cargo contour information from the truck image information, wherein the second cargo contour information is used to indicate contour information of the cargo to be transported in the vehicle to be loaded; based on the second cargo contour information, the cargo location information and the equipment location information, determining the transport route of the cargo to be transported by the transport equipment.

[0012] According to another aspect of an embodiment of the present invention, a control device for a handling device to carry goods is also provided. The device may include: a first acquisition unit, used to acquire the working mode and device location information of the handling device, wherein the working mode includes at least a loading mode and / or an unloading mode, and the device location information is used to indicate the location information of the handling device; a second acquisition unit, used to acquire the cargo location information, wherein the cargo location information is used to indicate the location information of the cargo to be carried; a determination unit, used to determine the transportation route of the cargo to be carried by the handling device based on the working mode, the cargo location information and the device location information; and a control unit, used to control the handling device to carry the cargo to be carried according to the transportation route.

[0013] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method for controlling the transport of goods by the transport equipment in the embodiment of the present invention.

[0014] According to another aspect of an embodiment of the present invention, a processor is further provided, wherein the processor is used to run a program, wherein when the program is run, the method for controlling the transport of goods by a transport device in an embodiment of the present invention is executed.

[0015] According to another aspect of the embodiment of the present invention, a computer program product is provided, which includes computer instructions, and when the computer instructions are executed by a processor, the control method for the handling equipment to handle goods in the embodiment of the present invention is implemented.

[0016] In an embodiment of the present invention, the working mode and equipment location information of the handling equipment are obtained, wherein the working mode includes at least a loading mode and / or an unloading mode, and the equipment location information is used to indicate the location information of the handling equipment; the cargo location information is obtained, wherein the cargo location information is used to indicate the location information of the cargo to be handled; based on the working mode, the cargo location information and the equipment location information, the handling route of the cargo to be handled by the handling equipment is determined; and according to the handling route, the handling equipment is controlled to handle the cargo to be handled. In other words, the present invention automatically determines the handling route of the cargo to be handled by the handling equipment by processing the working mode, location information and cargo location information of the handling equipment, thereby controlling the handling equipment to handle the cargo to be handled, thereby solving the technical problem of low handling efficiency of the handled cargo and achieving the technical effect of improving the handling efficiency of the handled cargo. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 is a flow chart of a method for controlling a transport device to transport goods according to an embodiment of the present invention;

[0019] Figure 2 is a schematic diagram of an intelligent transport robot suitable for transporting explosives according to an embodiment of the present invention;

[0020] Figure 3 is a schematic diagram of the structure of a machine vision module of a handling robot according to an embodiment of the present invention;

[0021] Figure 4 is a schematic diagram of the structure of a navigation module of a transport robot according to an embodiment of the present invention;

[0022] Figure 5 2 is a schematic diagram of a control device for transporting goods by a transporting device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, functional component or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, functional components or devices.

[0025] According to an embodiment of the present invention, an embodiment of a control method for a handling device to transport goods is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] Figure 1 is a flow chart of a method for controlling a transport device to transport goods according to an embodiment of the present invention. Figure 1 As shown, the method may include the following steps:

[0027] Step S101, obtaining the working mode and equipment location information of the transport equipment.

[0028] In the technical solution provided in the above step S101 of the present invention, the working mode at least includes a loading mode and / or an unloading mode, and the equipment location information is used to indicate the location information of the transport equipment.

[0029] In this embodiment, the working mode and device location information of the transport device are obtained. For example, the device location information is obtained through the self-navigation positioning of the transport device. This is only an illustrative example and does not limit the specific method of obtaining the device location information.

[0030] Step S102, obtaining cargo location information.

[0031] In the technical solution provided in the above step S102 of the present invention, the cargo location information is used to indicate the location information of the cargo to be transported.

[0032] In this embodiment, after the working mode and device location information of the handling device are obtained in step S101, the cargo location information is obtained. For example, the cargo location information is collected by a depth vision unit. This is only an example and does not limit the specific method of obtaining the cargo location information.

[0033] For example, the warehouse image information is collected through the machine vision module, and then the warehouse image information is processed to determine the cargo location information.

[0034] Step S103, based on the working mode, the cargo location information and the equipment location information, determining a transport route for the transport equipment to transport the cargo to be transported.

[0035] In the technical solution provided in the above step S103 of the present invention, the transporting device may be a transporting robot.

[0036] In this embodiment, after the cargo location information is acquired in step S102, a transport route for the transport equipment to transport the cargo to be transported is determined according to the working mode, the cargo location information and the equipment location information.

[0037] Optionally, when the working mode is the loading mode, the navigation model is used to process the cargo location information and the equipment location information to determine a transportation route for the transportation equipment to transport the cargo to be transported, that is, a loading navigation route.

[0038] For example, when it is determined to be a loading task, the machine vision module is used to identify the outline of the truck, and the position of the truck is determined based on the outline of the truck. Then, the machine vision module is used to collect image information of the cargo warehouse, and the outline of the cargo pile is identified based on the image information. The navigation module formulates a loading navigation route based on the outline of the cargo pile, the outline of the truck and the equipment location information.

[0039] Optionally, when the working mode is the unloading mode, the navigation model is used to process the cargo position information and the equipment position information to determine a transport route for the transport equipment to transport the cargo to be transported, that is, the unloading navigation route.

[0040] For example, when it is determined to be an unloading task, the warehouse space is identified through the machine vision module, and the cargo stacking position is determined based on the warehouse space. Then, the image information inside the truck compartment is collected through the machine vision module, and the outline of the cargo pile is identified based on the image information inside the truck compartment. The navigation module formulates the loading navigation route based on the outline of the cargo pile, the cargo stacking position and the position of the handling robot.

[0041] Step S104, controlling the transport equipment to transport the goods to be transported according to the transport route.

[0042] In the technical solution provided in the above step S104 of the present invention, after the transport route is determined in step S103, the transport equipment is controlled to transport the goods to be transported according to the transport route.

[0043] In this embodiment, the transport device is controlled according to the transport route, for example, by a control unit on the transport device.

[0044] For example, the control unit includes at least a loading control unit, which controls the driving unit to drive the transport robot to a preset position at the cargo pile according to the loading navigation route, and then controls the manipulator to complete unstacking, pick up the goods and load them into the transport warehouse, and then controls the driving unit to move to the predetermined position of the truck compartment to complete the stacking operation.

[0045] To give another example, the control unit includes at least an unloading control unit, and the loading control unit controls the driving unit to drive the transport robot to the cargo pile position in the truck compartment according to the unloading navigation route, and then the unloading control unit controls the manipulator to pick up the cargo and load it into the transport warehouse, and then controls the driving unit to move to a predetermined position in the warehouse space.

[0046] It should be noted that the above embodiment can be implemented by a coal crushing and feeding control system.

[0047] In the above steps S101 to S104 of the present invention, the working mode and equipment location information of the handling equipment are obtained, wherein the working mode includes at least a loading mode and / or an unloading mode, and the equipment location information is used to indicate the location information of the handling equipment; the cargo location information is obtained, wherein the cargo location information is used to indicate the location information of the cargo to be handled; based on the working mode, the cargo location information and the equipment location information, the handling route of the cargo to be handled by the handling equipment is determined; and according to the handling route, the handling equipment is controlled to handle the cargo to be handled. In other words, the present invention automatically determines the handling route of the cargo to be handled by the handling equipment by processing the working mode, location information and cargo location information of the handling equipment, thereby controlling the handling equipment to handle the cargo to be handled, thereby solving the technical problem of low handling efficiency of the handled cargo and achieving the technical effect of improving the handling efficiency of the handled cargo.

[0048] The above method of this embodiment is further introduced below.

[0049] As an optional implementation manner, obtaining cargo location information includes: obtaining warehouse image information, wherein the warehouse image information is used to indicate image information of a warehouse storing cargo to be transported; and extracting cargo location information from the warehouse image information.

[0050] In this embodiment, the cargo warehouse image information is acquired, and the cargo location information is extracted from the cargo warehouse image information. For example, the cargo location information is detected and extracted from the cargo warehouse image using a detection algorithm.

[0051] For example, the warehouse space is identified through a machine vision module, and the cargo stacking position, that is, the cargo location information, is determined based on the warehouse space.

[0052] As an optional implementation method, based on the working mode, cargo location information and equipment location information, determining the transportation route of the transportation equipment for transporting the goods to be transported, including: in response to the working mode being the loading mode, obtaining the truck location information, wherein the truck location information is used to indicate the location information of the vehicle to be loaded; based on the truck location information, cargo location information and equipment location information, determining the transportation route of the transportation equipment for transporting the goods to be transported.

[0053] In this embodiment, when the working mode is the loading mode, it means that the goods in the warehouse need to be transported to the vehicle to be loaded. Based on this, the truck location information is obtained, and then the transportation route of the transportation equipment to transport the goods to be transported is determined according to the truck location information, the cargo location information and the equipment location information.

[0054] Optionally, by acquiring the truck location information, the optimal transportation route can be determined according to the truck location and the cargo location, thereby avoiding unnecessary repeated transportation and wasting time, thereby improving transportation efficiency.

[0055] As an optional implementation method, based on the truck location information, cargo location information and equipment location information, determining the transportation route of the cargo to be transported by the transportation equipment, including: extracting first cargo profile information from the cargo location information, wherein the first cargo profile information is used to indicate the profile information of the cargo to be transported in the cargo warehouse; based on the first cargo profile information, the truck location information and the equipment location information, determining the transportation route of the cargo to be transported by the transportation equipment.

[0056] In this embodiment, the first cargo contour information is extracted from the cargo position information, for example, by performing edge recognition through an edge detection algorithm or edge detection.

[0057] For example, the edge of an object is determined by detecting the change in brightness in an image. Common edge detection algorithms include Sobel operator, Canny edge detection, etc. Further, take Canny edge detection as an example. The acquired image is grayed to convert the color image into a grayscale image. This step is to simplify the complexity of image processing and make the subsequent edge detection algorithm easier to operate. The grayed image is smoothed to reduce the noise in the image. Smoothing filters include Gaussian filters, median filters, etc. The gradient value and direction of each pixel in the image are calculated by applying a gradient operator. Gradient operators include Prewitt operator, Roberts operator, etc. In the gradient image, non-maximum suppression is performed on each pixel to retain the fine lines in the image while suppressing the response of other areas. This step helps to refine the edge. According to the set threshold, the pixels in the image are divided into three categories: strong edge, weak edge and non-edge. Two thresholds are usually selected, a lower threshold is used to detect possible edges, and a higher threshold is used to screen real edges. The edge tracking algorithm based on the gradient direction or the edge pixel neighbor relationship forms a continuous edge contour by connecting the strong edge pixels in the image. The edge contour is refined to make the edge more accurate and clear. This step usually includes operations such as eliminating unnecessary pixels and connecting broken edge segments.

[0058] As an optional implementation method, based on the working mode, cargo location information and equipment location information, the transport route of the cargo to be transported by the transport equipment is determined, including: in response to the working mode being the unloading mode, obtaining truck image information, wherein the truck image information is used to indicate image information of the interior of the compartment of the vehicle to be loaded; based on the truck image information, cargo location information and equipment location information, determining the transport route of the cargo to be transported by the transport equipment.

[0059] In this embodiment, when the working mode is the unloading mode, it means that the goods in the vehicle to be unloaded need to be moved to the cargo warehouse. Based on this, the truck image information is obtained, wherein the truck image information is used to indicate the image information inside the compartment of the vehicle to be loaded.

[0060] Optionally, after obtaining the truck image information, the transport route of the cargo to be transported by the transport equipment is determined based on the truck image information, cargo location information and equipment location information. For example, the truck image information, cargo location information and equipment location information are processed using a navigation module to determine the transport route of the cargo to be transported by the transport equipment.

[0061] As an optional implementation method, based on the truck image information, the cargo location information and the equipment location information, determining the transportation route of the cargo to be transported by the transportation equipment, including: extracting second cargo contour information from the truck image information, wherein the second cargo contour information is used to indicate the contour information of the cargo to be transported in the vehicle to be loaded; based on the second cargo contour information, the cargo location information and the equipment location information, determining the transportation route of the cargo to be transported by the transportation equipment.

[0062] In this embodiment, the second cargo contour information is extracted from the truck image information, for example, by implementing contour detection through a segmentation algorithm.

[0063] For example, objects in an image are segmented into different regions or pixels to achieve contour recognition, such as threshold-based segmentation, region growing method, edge segmentation method, etc.

[0064] It should be noted that the above embodiment can be implemented by a coal crushing and feeding control system.

[0065] In this embodiment, the working mode and equipment location information of the handling equipment are obtained, wherein the working mode includes at least a loading mode and / or an unloading mode, and the equipment location information is used to indicate the location information of the handling equipment; the cargo location information is obtained, wherein the cargo location information is used to indicate the location information of the cargo to be handled; based on the working mode, the cargo location information and the equipment location information, the handling route of the cargo to be handled by the handling equipment is determined; and according to the handling route, the handling equipment is controlled to handle the cargo to be handled. In other words, the present invention automatically determines the handling route of the cargo to be handled by the handling equipment by processing the working mode, location information and cargo location information of the handling equipment, thereby controlling the handling equipment to handle the cargo to be handled, thereby solving the technical problem of low handling efficiency of the handled cargo and achieving the technical effect of improving the handling efficiency of the handled cargo.

[0066] The technical solution of the embodiment of the present invention is illustrated below in conjunction with preferred implementation modes.

[0067] At present, in the environment of handling explosives, the importance of handling goods is self-evident. Any careless operation or negligence may lead to serious accidents, endangering the lives of people and property safety. Therefore, when handling explosives, it is necessary to strictly abide by the operating procedures and safety instructions to ensure the safe handling of goods.

[0068] In the related technologies, manual handling operations are mostly used. Since the objects being handled are dangerous and heavy, there is an urgent need to use handling robots to replace manual handling operations. This is expected to further improve the safety of operations while ensuring handling efficiency. At the same time, the function of a large number of handling robots used in the market is only for loading, and cannot solve the problem of automatic unloading. Therefore, there is a technical problem of low handling efficiency of the goods being handled. At present, no effective solution has been proposed for the above-mentioned technical problem of low handling efficiency of the goods being handled.

[0069] However, an embodiment of the present invention proposes a method suitable for handling explosives, by determining that the current working state is a loading task or an unloading task, and when it is determined to be a loading task, locating the position of the handling robot itself; identifying the outline of the truck, determining the position of the truck based on the outline of the truck, and then collecting cargo warehouse image information through a machine vision module, and identifying the outline of the cargo pile based on the image information; the navigation module formulates a loading navigation route based on the outline of the cargo pile and the outline of the truck, thereby solving the technical problem of low handling efficiency of handling goods and achieving the technical effect of improving the handling efficiency of handling goods.

[0070] The embodiments of the present invention are further described below.

[0071] Figure 2 is a schematic diagram of an intelligent transport robot suitable for transporting explosives according to an embodiment of the present invention, such as Figure 2 As shown, the intelligent transport robot 200 may include: a motion chassis 201 , a machine vision module 202 , a transport warehouse 203 and a manipulator 204 .

[0072] The motion chassis 201 is a customized 600kg load motion component. It has the characteristics of high load, high sensitivity, high mobility, strong obstacle crossing ability, etc. The kit includes a telecontrol drive unit 2011, a battery assembly 2012, a navigation module 2016, a communication unit 2015, a control unit 2014 and a task acquisition unit 2017.

[0073] Optionally, the driving unit 2011 is used to drive the moving chassis to move; in addition to providing power to the above components, the battery assembly 2013 also provides power to the manipulator 204 and the cargo hold adjustment unit 2031.

[0074] Optionally, the performance parameters of the drive assembly may be exemplified as follows: Load capacity: 600kg body load. Traveling capacity: 300mm non-slip rubber drive wheel. Endurance of the drive assembly: 48V DC drive motor. Climbing: 6° rough ground differential steering structure, strong ability to pass twisted ground. Passability: 20mm gap, 10mm threshold can be passed.

[0075] Optionally, in the present invention, multiple handling robots can be deployed at the same time, and the multiple handling robots are communicatively connected to the intelligent warehouse management platform. The intelligent warehouse management platform is connected to the existing warehouse data system and the robot intelligent central control platform to comprehensively coordinate the task issuance of the handling robots and the visual display of work data.

[0076] Optionally, in order to ensure explosion-proof safety and realize unmanned warehouse-style transportation in an explosive handling environment, and solve the problems of loading and unloading at the same time, the task acquisition unit 2017 can determine whether the current working state is a loading task or an unloading task.

[0077] Optionally, when it is determined to be a loading task, the self-position is located, the outline of the truck is identified through the machine vision module, the position of the truck is determined based on the outline of the truck, and then the cargo warehouse image information is collected through the machine vision module, the outline of the cargo pile is identified based on the image information, and the navigation module formulates a loading navigation route based on the outline of the cargo pile and the outline of the truck. The control unit includes at least a loading control unit, which controls the driving unit to drive the transport robot to a preset position at the cargo pile according to the loading navigation route, and then the loading control unit controls the manipulator to complete the unstacking, pick up the goods and load them into the transport cargo warehouse, and then controls the driving unit to move to the predetermined position of the truck compartment to complete the stacking operation.

[0078] Optionally, when it is determined to be an unloading task, the position of the handling robot itself is first located, and then the warehouse space is identified through the machine vision module, and the cargo stacking position is determined according to the warehouse space, and then the image information in the truck compartment is collected through the machine vision module, and the cargo pile contour is identified according to the image information in the truck compartment. The navigation module formulates an unloading navigation route according to the cargo pile contour and the cargo stacking position, and the control unit includes at least an unloading control unit, and the loading control unit controls the driving unit to drive the handling robot to the cargo pile position in the truck compartment according to the unloading navigation route, and then the unloading control unit controls the manipulator to pick up the cargo and load it into the handling warehouse, and then controls the driving unit to move to a predetermined position in the warehouse space.

[0079] The machine vision module 202 is used to automatically realize loading and unloading. Figure 3 Schematic diagram of the structure of a machine vision module of a handling robot according to an embodiment of the present invention. Figure 3 As shown, the machine vision module 202 includes a depth vision unit 2021 and a video acquisition unit 2022.

[0080] Optionally, the depth vision unit 2021 is mainly used to collect spatial data in multiple channels of visible light, and restore the workspace and cargo location information through visual algorithm calculation. Specifically, in the loading process, the truck outline can be obtained through the depth vision unit, and the truck position can be determined based on the truck outline. Then, the cargo warehouse image information is collected through the machine vision module, and the cargo pile outline is identified based on the image information. When implementing truck outline detection, loading and unloading remain consistent at the algorithm level, which can be exemplified as: edge recognition is performed through edge detection algorithm or edge detection, which determines the edge of the object by detecting light and dark changes in the image. Commonly used edge detection algorithms include Sobel operator, Canny edge detection, etc.

[0081] Optionally, taking canny edge detection as an example, the acquired image is grayed to convert the color image into a gray image. This step is to simplify the complexity of image processing so that the subsequent edge detection algorithm is easier to operate. The grayed image is smoothed to reduce the noise in the image. Smoothing filters include Gaussian filters, median filters, etc. The gradient value and direction of each pixel in the image are calculated by applying a gradient operator. Gradient operators include Prewitt operators, Roberts operators, etc. In the gradient image, non-maximum suppression is performed on each pixel to retain the fine lines in the image while suppressing the response of other areas. This step helps to refine the edge. According to the set threshold, the pixels in the image are divided into three categories: strong edge, weak edge and non-edge. Two thresholds are usually selected, a lower threshold is used to detect possible edges, and a higher threshold is used to screen real edges. The edge tracking algorithm based on the gradient direction or the edge tracking algorithm based on the adjacent relationship of edge pixels forms a continuous edge contour by connecting the strong edge pixels in the image. The edge contour is refined to make the edge more accurate and clear. This step usually includes operations such as eliminating unnecessary pixels and connecting broken edge segments.

[0082] Optionally, in addition to the above-mentioned edge detection algorithm, in the present invention, a segmentation algorithm can also be used to realize contour detection, which is a method of dividing an object in an image into different regions or pixels, thereby realizing contour recognition. In the present invention, exemplary segmentation algorithms include threshold-based segmentation, region growing method, edge segmentation method, etc.

[0083] Optionally, the performance parameters of the depth vision unit 202 are as follows: sensor specifications: monocular TOF sensor camera; weather resistance parameters: IP65; explosion-proof performance parameters: EX IIIC; the robot carries a camera to collect the physical outline of the warehouse, perform pattern recognition on the shape, and determine its spatial position and quantity.

[0084] Optionally, the robot visually identifies the boundaries of objects, calculates the spatial dimensions, automatically determines the dimensions of packaging boxes, and automatically collects label information of cargo packaging boxes.

[0085] Optionally, in the machine vision module 202 of the present invention, there may be further a video acquisition unit 2022, and the video acquisition unit 2022 is configured to complete video data acquisition of the working surface.

[0086] Optionally, the navigation module 2016 mainly functions to guide the transport robot to complete loading or unloading operations according to the loading navigation route or the unloading navigation route, because during the entire loading or unloading operation, the transport robot needs to shuttle between trucks, transition platforms, transition sections and complex warehouse ground environments.

[0087] Optionally, in the present invention, it is actually necessary to use multiple navigation units in combination. For example, it can exemplarily include at least two or more combination judgment scenarios of the following navigation units.

[0088] Optionally, Figure 4 is a schematic diagram of the structure of a navigation module of a transport robot according to an embodiment of the present invention, such as Figure 4 As shown, the navigation module 2016 includes: an inertial navigation unit 20161 (Inertial Navigation System, referred to as INS), a grayscale navigation unit 20162, a magnetic navigation unit 20163, a QR code navigation unit 20164 and an auxiliary navigation unit 20165.

[0089] Optionally, the inertial navigation unit 20161 uses an inertial navigation unit for navigation in areas without navigation marks; the inertial navigation unit is a system for determining the position, direction and speed of a moving object in three-dimensional space. It uses inertial measurement devices, such as accelerometers and gyroscopes, to measure the acceleration and angular velocity of an object, and then estimates the position and direction of the object by integrating these measurements.

[0090] Optionally, the grayscale navigation unit 20162: in the area with color difference dedicated navigation mark, the bottom color difference grayscale camera navigation is used; in this method, the camera installed at the bottom of the moving chassis is used to capture the image on the ground, and usually uses color difference or grayscale information to identify specific marks, lines or patterns on the ground. These marks, lines or patterns can be pre-designed or generated in real time.

[0091] Optionally, the magnetic navigation unit 20163: in the area with magnetic navigation markers, a Hall sensor is used for navigation; in this method, magnetic markers or magnetic strips can be installed on the navigation path. These markers usually contain magnetic materials and generate magnetic fields to indicate navigation paths, turning points or target locations. A Hall sensor is installed at the bottom of the moving chassis to detect the strength and direction of the surrounding magnetic field. The Hall sensor can detect changes in the magnetic field and convert them into electrical signals for output. The position and direction of the navigation device relative to the magnetic navigation marker can then be determined by analyzing the electrical signal output by the Hall sensor. Based on this information, functions such as navigation path tracking, turning control and target navigation can be realized. It is worth noting that the technical means for navigation by the magnetic navigation unit can be further optimized and improved. Specifically, the Hall sensor can be calibrated before using the Hall sensor for navigation to ensure accurate detection of the strength and direction of the magnetic field. The calibration process includes determining parameters such as the sensitivity, offset and direction of the sensor.

[0092] Optionally, the QR code navigation unit 20164: in the area with a dedicated QR code navigation mark, a bottom wide-angle camera is used for navigation; when using this method for navigation, the QR code navigation mark can be arranged on the predetermined route in advance. These QR codes usually contain information such as position, direction, and target, which can be recognized by the navigation system. A wide-angle camera is arranged at the bottom of the moving chassis, and the wide-angle camera captures the QR code image on the ground. After capturing the ground QR code image, the navigation system uses image processing technology to pre-process the image, and uses a QR code recognition algorithm to detect and decode the QR code in the image. Once the QR code is recognized, the navigation system decodes the information therein and calculates the position and posture of the navigation device relative to the QR code based on the position and direction of the QR code. Based on the recognized QR code information, the navigation system performs path planning and adjusts the motion control of the navigation device to move along the predetermined path or to the target position.

[0093] Optionally, an auxiliary navigation unit 20165 may be further added, wherein the auxiliary navigation unit 20165 may be a Beidou navigation module. When other systems need to call the robot's location information, the system can provide relevant geographic coordinate information.

[0094] Optionally, the above navigation units can be used in combination of two or more, depending on the actual operating environment. However, it should be noted that in the present invention, at least two navigation units should be used in combination.

[0095] Optionally, in the present invention, the navigation module 2016 adopts multiple navigation methods because the transport robot needs to be able to adapt to the first section from the truck to the transition platform, the second section from the transition platform to the warehouse door, and the third section from the warehouse door to the stacking area. The working conditions of each section are different, so different navigation methods are suitable and intelligent judgment is required. When judging the scene, the method of the present invention is as follows.

[0096] Optionally, first, Bluetooth beacons are set at truck stops, transition platforms, warehouse entrances and stacking areas, and the UUIDs of the Bluetooth beacons are recorded. Each Bluetooth beacon periodically sends Bluetooth signals to the surrounding areas. A Bluetooth receiver is set on the handling robot. The Bluetooth receiver periodically scans the Bluetooth signals emitted by the surrounding Bluetooth beacons. For each received Bluetooth signal, the UUID and signal strength (RSSI, Received Signal Strength Indication) of the Bluetooth beacon are recorded.

[0097] Optionally, the distance between the mobile device and each Bluetooth beacon is estimated based on the received signal strength. In the present invention, a logarithmic attenuation model is used for specific estimation. The specific algorithm is:

[0098] RSSI = A-10 n log 10 (d)+∈

[0099] Where RSSI is the received signal strength in decibels (dBm). d is the distance between the mobile device and the beacon in meters. A is the reference signal strength (RSSI) at a specific distance (usually 1 meter). n is the path loss exponent, which indicates the rate at which the signal decays. Generally, the value of n is between 2 and 4, depending on the complexity of the environment and the propagation medium. ∈ is a random error term, which represents noise or interference caused by other factors.

[0100] Optionally, the parameters A and n of the logarithmic attenuation model can be determined by field measurements and model fitting. Generally, some experimental measurements are required to collect RSSI values ​​at different distances and use a fitting algorithm (such as the least squares method) to estimate the parameters of the model.

[0101] Optionally, the process of fitting the model is generally as follows: collect a series of sampling points with different distances and measure the RSSI value at each sampling point. Input the distance of the sampling point and the corresponding RSSI value into the fitting algorithm. Use the fitting algorithm to fit the parameters A and n of the logarithmic decay model. Verify the accuracy of the fitting model and adjust and optimize it as needed. Once the parameters of the logarithmic decay model are determined, the model can be used to estimate the distance between the mobile device and the beacon. By reverse calculation, the distance is estimated based on the received RSSI value and the model parameters. 3) Using the received beacon information (UUID) and the distance estimate, use the positioning algorithm to calculate the position of the mobile device. Positioning algorithms include triangulation or weighted average.

[0102] Optionally, the obtained position estimation result usually needs to be error corrected and optimized, and the positioning accuracy can be improved by taking an average value through multiple measurements or using filtering technology (such as Kalman filtering).

[0103] Optionally, the position coordinates of the handling robot device relative to the Bluetooth beacon are output and projected into a two-dimensional coordinate system.

[0104] Optionally, based on the preset coordinate value range in the two-dimensional coordinate system, it is determined whether the handling robot is in the first section, the second section or the third section, and when it is in the first section, the inertial navigation unit and the grayscale navigation unit are enabled; when it is in the second section, the magnetic navigation unit is enabled, and at this time, a navigation magnetic strip or magnetic nail is pre-buried on the fixed section between the transition platform and the warehouse door. When it is determined to be in the third section, it is already in the warehouse. At this time, according to the two-dimensional code navigation mark sprayed on the ground in the warehouse, the navigation mark covers the location information of multiple different stacking areas. The handling robot can go to the stacking areas with different numbers corresponding to the handling task according to the information given by the two-dimensional code.

[0105] Optionally, the manipulator 204 is used to achieve loading and unloading, and the following rectangular coordinate manipulator is selected. More specifically, the manipulator should have a 6-axis drive structure including 3D coordinate control, tilt control, horizontal delivery control, and folding guide suction cup structure. It can flexibly adapt to the pick-up and placement of various cargo specifications.

[0106] Optionally, exemplary manipulator performance parameters: load capacity: 40kg; arm span and working space: 0.9*1.5 meters; power supply specification: 48v; DC weather resistance parameter: IP65; explosion-proof performance parameter: EX IIIC.

[0107] Optionally, the communication unit 2015 accesses the customer network through the secure access point provided by the customer (the construction party needs to set up the corresponding gateway according to the access location, including physical isolation such as network gates and firewalls), builds its own communication network, and the main data uses 5G private network and WIFI communication methods, and has 4G or 5G public network communication functions. The project construction party lays all the cables and other equipment and facilities that meet the system operation to ensure the safe, stable and high-quality operation of the system.

[0108] Optionally, the normal working mode of the robot is an unmanned working mode with fully automatic path planning. "Remote intervention" opens the "start and stop" authority of the robot system. Due to the complexity of path planning and the limitation of remote field of view, for the safety of robot operation, remote intervention of the robot's motion planning and navigation operation is not supported. "On-site control" refers to the method in which a dedicated person uses a dedicated handle to control movement on-site, which is mostly used in system debugging or fault rescue situations.

[0109] In this embodiment, by determining whether the current working state is a loading task or an unloading task, when it is determined to be a loading task, the position of the handling robot itself is located; the outline of the truck is identified, and the position of the truck is determined based on the outline of the truck, and then the image information of the cargo warehouse is collected through the machine vision module, and the outline of the cargo pile is identified based on the image information; the navigation module formulates a loading navigation route based on the outline of the cargo pile and the outline of the truck, which solves the technical problem of low handling efficiency of handling goods and achieves the technical effect of improving the handling efficiency of handling goods.

[0110] According to an embodiment of the present invention, a control device for a transporting device to transport goods is also provided. It should be noted that the control device for a transporting device to transport goods can be used to execute a control method for a transporting device to transport goods in a method embodiment.

[0111] Figure 5 Schematic diagram of a control device for transporting goods using a transport device according to an embodiment of the present invention. Figure 5 As shown, the control device 500 for transporting goods by the transport equipment may include: a first acquisition unit 501 , a second acquisition unit 502 , a determination unit 503 and a control unit 504 .

[0112] The first acquisition unit 501 is used to acquire the working mode and device location information of the transport device, wherein the working mode at least includes a loading mode and / or an unloading mode, and the device location information is used to indicate the location information of the transport device.

[0113] The second acquiring unit 502 is used to acquire cargo location information, wherein the cargo location information is used to indicate location information of the cargo to be transported.

[0114] The determination unit 503 is used to determine a transport route for the transport equipment to transport the goods to be transported based on the working mode, the goods location information and the equipment location information.

[0115] The control unit 504 is used to control the transport equipment to transport the goods to be transported according to the transport route.

[0116] Optionally, the second acquisition unit 502 may include: a first acquisition module, used to acquire warehouse image information, wherein the warehouse image information is used to indicate image information of a warehouse storing goods to be transported; and a first extraction module, used to extract cargo location information from the warehouse image information.

[0117] Optionally, the determination unit 503 may include: a second acquisition module, used to obtain truck location information in response to the working mode being a loading mode, wherein the truck location information is used to indicate location information of a vehicle to be loaded; and a first determination module, used to determine a transport route for the transport equipment to transport the goods to be transported based on the truck location information, the cargo location information and the equipment location information.

[0118] Optionally, the first determination module may include: a first extraction submodule, used to extract first cargo profile information from the cargo location information, wherein the first cargo profile information is used to indicate profile information of the cargo to be transported in the cargo warehouse; a first determination submodule, used to determine a transport route for the transport equipment to transport the cargo to be transported based on the first cargo profile information, the truck location information and the equipment location information.

[0119] Optionally, the determination unit 503 may include: a third acquisition module, used to acquire truck image information in response to the working mode being the unloading mode, wherein the truck image information is used to indicate image information of the interior of the compartment of the vehicle to be loaded; and a second determination module, used to determine a transport route for the transport equipment to transport the goods to be transported based on the truck image information, the cargo location information and the equipment location information.

[0120] Optionally, the second determination module may include: an extraction submodule, used to extract second cargo contour information from the truck image information, wherein the second cargo contour information is used to indicate contour information of the cargo to be transported in the vehicle to be loaded; a second determination submodule, used to determine a transport route for the transport equipment to transport the cargo to be transported based on the second cargo contour information, the cargo location information and the equipment location information.

[0121] In this embodiment, the working mode and equipment location information of the handling equipment are obtained, wherein the working mode includes at least a loading mode and / or an unloading mode, and the equipment location information is used to indicate the location information of the handling equipment; the cargo location information is obtained, wherein the cargo location information is used to indicate the location information of the cargo to be handled; based on the working mode, the cargo location information and the equipment location information, the handling route of the cargo to be handled by the handling equipment is determined; and according to the handling route, the handling equipment is controlled to handle the cargo to be handled. In other words, the present invention automatically determines the handling route of the cargo to be handled by the handling equipment by processing the working mode, location information and cargo location information of the handling equipment, thereby controlling the handling equipment to handle the cargo to be handled, thereby solving the technical problem of low handling efficiency of the handled cargo and achieving the technical effect of improving the handling efficiency of the handled cargo.

[0122] According to an embodiment of the present invention, there is further provided a computer-readable storage medium, the storage medium comprising a stored program, wherein the program executes the method for controlling the transport of goods by a transporting device in an embodiment of the method.

[0123] According to an embodiment of the present invention, a processor is further provided. The processor is used to run a program, wherein the program executes the method for controlling the transport of goods by a transporting device in the method embodiment when running.

[0124] According to an embodiment of the present invention, a computer program product is further provided. The computer program product includes computer instructions. When the computer instructions are executed by a processor, the method for controlling the transporting of goods by a transporting device in the method embodiment is implemented.

[0125] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0126] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0127] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0128] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0129] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0130] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent functional component, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software functional component, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc., which can store program codes.

[0131] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for controlling a transport device to transport goods, characterized in that: include: Acquire the working mode and device location information of the transport equipment, wherein the working mode at least includes a loading mode and / or an unloading mode, and the device location information is used to indicate the location information of the transport equipment; Acquiring cargo location information, wherein the cargo location information is used to indicate location information of the cargo to be transported; Determining a transport route for the transport equipment to transport the cargo to be transported based on the working mode, the cargo location information and the equipment location information; According to the transport route, the transport equipment is controlled to transport the goods to be transported.

2. The method according to claim 1, characterized in that Obtain cargo location information, including: Acquire warehouse image information, wherein the warehouse image information is used to indicate image information of a warehouse storing the goods to be transported; The cargo location information is extracted from the cargo warehouse image information.

3. The method according to claim 1, characterized in that Determining a transport route for the transport equipment to transport the cargo to be transported based on the working mode, the cargo location information, and the equipment location information, includes: In response to the working mode being the loading mode, obtaining truck position information, wherein the truck position information is used to indicate position information of a vehicle to be loaded; The transport route for the transport equipment to transport the cargo to be transported is determined based on the truck position information, the cargo position information and the equipment position information.

4. The method according to claim 3, characterized in that Determining the transport route of the cargo to be transported by the transport equipment based on the truck location information, the cargo location information and the equipment location information includes: Extracting first cargo profile information from the cargo position information, wherein the first cargo profile information is used to indicate profile information of the cargo to be transported in the cargo warehouse; The transport route for the transport equipment to transport the cargo to be transported is determined based on the first cargo profile information, the truck position information and the equipment position information.

5. The method according to claim 1, characterized in that Determining a transport route for the transport equipment to transport the cargo to be transported based on the working mode, the cargo location information, and the equipment location information, includes: In response to the working mode being the unloading mode, acquiring truck image information, wherein the truck image information is used to indicate image information of the interior of a compartment of a vehicle to be loaded; The transport route for the transport equipment to transport the cargo to be transported is determined based on the truck image information, the cargo position information and the equipment position information.

6. The method according to claim 5, characterized in that Determining the transport route of the cargo to be transported by the transport equipment based on the truck image information, the cargo location information and the equipment location information includes: Extracting second cargo contour information from the truck image information, wherein the second cargo contour information is used to indicate contour information of the cargo to be transported in the vehicle to be loaded; The transport route for the transport equipment to transport the cargo to be transported is determined based on the second cargo profile information, the cargo location information and the equipment location information.

7. A control device for transporting goods by a transporting device, characterized in that: include: A first acquisition unit is used to acquire the working mode and device location information of the transport device, wherein the working mode at least includes a loading mode and / or an unloading mode, and the device location information is used to indicate the location information of the transport device; A second acquiring unit is used to acquire cargo location information, wherein the cargo location information is used to indicate location information of the cargo to be transported; a determination unit, configured to determine a transport route for the transport equipment to transport the cargo to be transported based on the working mode, the cargo location information and the equipment location information; A control unit is used to control the transport equipment to transport the goods to be transported according to the transport route.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 6.

9. A processor, characterized in that: The processor is used to run a program, wherein the program executes the method according to any one of claims 1 to 6 when running.

10. A computer program product, characterized in that The computer program product comprises computer instructions, which implement the method according to any one of claims 1 to 6 when executed by a processor.

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