Driving control method and system of unmanned forklift

Abstract

The invention provides a driving control method and system of an unmanned forklift, and relates to the technical field of unmanned forklifts.The method comprises the steps that image analysis is conducted on materials to be transported, target contour information is obtained, and the target contour information is used for indicating the projection contour of the materials to be transported vertically projected on the ground; a projection contour indicated by the target contour information and a virtual vehicle body contour of a first target forklift are spliced to obtain a target contour, and the first target forklift is an unmanned forklift used for transporting the to-be-transported material in an unmanned forklift cluster; and a target transportation route of the first target forklift is generated according to the target contour, and the first target forklift is controlled to transport the to-be-transported materials based on the target transportation route. Through the arrangement, a safer transportation route can be generated, so that the accident risk of the unmanned forklift in the material transportation process is lower, and the safety is higher.

Description

Technical Field

[0001] The present disclosure relates to the technical field of unmanned forklifts, and in particular to a driving control method and system for an unmanned forklift. Background Art

[0002] "Unmanned forklift", also known as "driverless forklift" or "forklift AGV", is an intelligent industrial vehicle robot. Compared with ordinary AGV, "unmanned forklift" can not only complete point-to-point material handling, but also realize logistics transportation connecting multiple production links.

[0003] It was found during application that the path planning method used by the related technology to control the unmanned forklift did not take the physical volume of the unmanned forklift into consideration. In addition, the actual volume of the logistics transported by the unmanned forklift is flexible and changeable, which makes it easy for the unmanned forklift to scratch and / or collide with materials in actual applications. In other words, the unmanned forklift driving control method provided by the related technology has poor safety. Summary of the invention

[0004] The purpose of the present disclosure is to provide a driving control method and system for an unmanned forklift, so as to solve the technical problem of poor safety of the driving control method for an unmanned forklift provided in the related art.

[0005] In a first aspect, an embodiment of the present application provides a driving control method for an unmanned forklift, the method comprising: Performing image analysis on the material to be transported to obtain target contour information, wherein the target contour information is used to indicate a projection contour of the material to be transported vertically projected onto the ground; splicing the projection contour indicated by the target contour information and the virtual body contour of the first target forklift to obtain a target contour, wherein the first target forklift is an unmanned forklift in the unmanned forklift cluster used to transport the material to be transported; A target transportation route of the first target forklift is generated according to the target profile, and the first target forklift is controlled to transport the material to be transported based on the target transportation route.

[0006] In a second aspect, an embodiment of the present application provides a driving control system for an unmanned forklift, the system comprising: An image analysis module is used to perform image analysis on the material to be transported to obtain target contour information, wherein the target contour information is used to indicate a projection contour of the material to be transported vertically projected onto the ground; a contour splicing module, configured to splice the projection contour indicated by the target contour information and the virtual body contour of a first target forklift to obtain a target contour, wherein the first target forklift is an unmanned forklift in an unmanned forklift cluster used for transporting the material to be transported; The forklift control module is used to generate a target transportation route of the first target forklift according to the target profile, and control the first target forklift to transport the material to be transported based on the target transportation route.

[0007] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect.

[0008] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0009] In a fifth aspect, an embodiment of the present application provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0010] In the present application, image analysis is performed on the material to be transported to obtain a projection outline of the material to be transported vertically projected onto the ground, and the projection outline is spliced ​​with the virtual body outline of the corresponding unmanned forklift to obtain a target outline, and a forklift transportation route is generated based on this and the forklift is controlled to transport the material. In the above setting, when planning the forklift path, the spliced ​​outline of the virtual body outline of the forklift and the ground projection outline of the material transported by the forklift is used to replace the fixed-size forklift outline used in the related technology during path planning, thereby generating a safer transportation route, which reduces the risk of accidents and increases safety for unmanned forklifts during material transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a flow chart of a driving control method of an unmanned forklift provided by an embodiment of the present disclosure; Figure 2 It is a structural schematic diagram of a driving control system of an unmanned forklift provided by an embodiment of the present disclosure; Figure 3 It is a schematic diagram of an electronic device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0012] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0013] See also Figure 1 , Figure 1 It is a flow chart of a driving control method of an unmanned forklift provided in an embodiment of the present application.

[0014] like Figure 1 As shown, the driving control method of the unmanned forklift includes: Step 101: Perform image analysis on the material to be transported to obtain target contour information.

[0015] The target contour information is used to indicate a projection contour of the material to be transported vertically projected onto the ground.

[0016] The above-mentioned material to be transported can be understood as one of the multiple materials corresponding to the unmanned forklift transportation scene, wherein the unmanned forklift transportation scene can be a plane handling scene, a high-level storage and access scene, a production line docking scene, a product loading and unloading scene, etc.

[0017] Exemplarily, the material can be understood as a forklift transport frame on which products / boxes are placed (the lower part of the frame is provided with a fork opening for the fork of the forklift to extend into), or it can be understood as a component connected to a detachable supporting structure, wherein the detachable supporting structure is also provided with a fork opening for the fork of the forklift to extend into.

[0018] In the application, a camera installed on the material to be transported can be used to collect the material image at the transportation starting point, and a pre-trained image analysis model can be used to perform preprocessing, feature extraction, modeling, and post-processing on the material image in sequence, thereby obtaining an image analysis result (that is, target contour information) output by the image analysis model for the material image. The target contour information includes at least: the contour shape of the projection contour of the material to be transported vertically projected onto the ground, and the contour area of ​​the projection contour.

[0019] Step 102: splice the projection contour indicated by the target contour information and the virtual body contour of the first target forklift to obtain the target contour.

[0020] The first target forklift is an unmanned forklift in the unmanned forklift cluster that is used to transport the material to be transported.

[0021] The above-mentioned unmanned forklift cluster can be understood as a cluster composed of multiple unmanned forklifts corresponding to the unmanned forklift transportation scene.

[0022] Without loss of generality, multiple unmanned forklifts in an unmanned forklift cluster may correspond to the same virtual vehicle body contour.

[0023] In one example, multiple unmanned forklifts in an unmanned forklift cluster can also correspond to a virtual body contour respectively. At this time, each virtual body contour is mapped to a forklift number, and each unmanned forklift is also mapped to a forklift number. There is a corresponding relationship between the unmanned forklifts and the virtual body contours mapped to the same forklift number.

[0024] In one example, the projection contour includes a first splicing point, and the virtual body contour of the first target forklift includes a second splicing point. The process of splicing the projection contour indicated by the target contour information and the virtual body contour of the first target forklift can be understood as a process of translating and rotating the projection contour based on the virtual body contour of the first target forklift so that the first splicing point and the second splicing point overlap. Among them, the first splicing point can be understood as the center point of the two forks in the material to be transported in the two fork areas corresponding to the projection contour, and the second splicing point can be understood as the center point of the two forks of the first target forklift in the corresponding virtual body contour corresponding fork area.

[0025] The target profile may be understood as a vertical projection profile of the first target forklift loaded with the material to be transported on the ground.

[0026] Step 103: Generate a target transportation route of the first target forklift according to the target profile, and control the first target forklift to transport the material to be transported based on the target transportation route.

[0027] Specifically, a preset path planning algorithm is used, and the object indicated by the target contour is used as a navigation object to generate a target transportation route moving from the transportation starting point of the material to be transported to the transportation end point of the material to be transported.

[0028] In the present application, image analysis is performed on the material to be transported to obtain a projection contour of the material to be transported vertically projected onto the ground, and the projection contour is spliced ​​with the virtual body contour of the corresponding unmanned forklift to obtain a target contour, and a forklift transportation route is generated accordingly and the forklift is controlled to transport the material. In the above setting, when planning the forklift path, the spliced ​​contour of the virtual body contour of the forklift and the ground projection contour of the material transported by the forklift is used to replace the fixed-size forklift contour used in the path planning of the related technology, thereby generating a safer transportation route, which makes the accident risk of the unmanned forklift during the material transportation process (i.e., the probability of the unmanned forklift colliding or scratching the material) lower and the safety higher.

[0029] In one embodiment, performing image analysis on the material to be transported to obtain target contour information includes: Collecting a material image of the material to be transported at the transport starting point; Performing image analysis on the material image to obtain pixel contour information, where the pixel contour information is used to indicate the contour of a pixel area corresponding to the material to be transported in the material image; The pixel contour information is converted according to the spatial mapping information corresponding to the material image to obtain the target contour information, wherein the spatial mapping information is used to indicate a mapping relationship between the material image and a corresponding area in a three-dimensional space.

[0030] The pixel contour information at least includes: the contour shape of the pixel region corresponding to the material to be transported in the material image, and the contour area of ​​the pixel region.

[0031] In this embodiment, after determining the contour shape of the pixel area corresponding to the material to be transported in the material image, and the contour area of ​​the pixel area, a spatial mapping conversion is performed to convert the contour area of ​​the pixel area into an actual area in three-dimensional space, thereby forming the target contour information, thereby ensuring the accuracy of the obtained target contour information.

[0032] Exemplarily, the spatial mapping information is used to indicate: the actual length / width corresponding to the length / width of a unit pixel block in the material image in the three-dimensional space, and / or the actual area corresponding to the area of ​​a unit pixel block in the material image in the three-dimensional space.

[0033] In one embodiment, performing image analysis on the material image to obtain pixel contour information includes: Correcting the material image to obtain a corrected image, wherein the corrected image is used to represent a top view of the material to be transported at the transport starting point; Performing image analysis on the corrected image to obtain the pixel contour information.

[0034] In this embodiment, in view of the situation that the image acquisition device (such as a camera) for taking material images is unable to achieve vertical shooting of the material to be transported during actual application, image correction is used to ensure that a top view of the material to be transported at the starting point of the transportation can be obtained, and image analysis is performed based on this, which can avoid contour calculation deviation caused by image shooting angle deviation, so that the obtained target contour information is more accurate and reliable.

[0035] In the present application, the correction operation performed on the material image can be understood as an operation of adjusting the material image for geometric correction.

[0036] In one embodiment, generating a target transportation route of the first target forklift according to the target profile includes: Generate an initial transportation route according to the target profile, the transportation starting point and the transportation end point of the material to be transported; Performing a turn detection on a plurality of transport turning points in the initial transport route to obtain a first detection result, wherein the transport turning point is used to indicate a location point where a turn occurs in the initial transport route; In the case where the first detection result indicates that the multiple transport inflection points include at least one risk inflection point, a route correction is performed on each risk inflection point in the initial transport route to obtain a first transport route, wherein the risk inflection point is a transport inflection point whose corresponding turning angle is greater than or equal to an angle threshold among the multiple transport inflection points, the turning angle corresponding to the inflection point section after the route correction is less than the angle threshold, and the total length of the first transport route is greater than the total length of the initial transport route; The target transportation route is determined according to the first transportation route.

[0037] In this embodiment, risk detection is performed on the turning sections in the initial transport route, and route correction is performed on the turning sections with excessively large steering angles, so that the steering angle of each turning section in the first transport route after route correction is within a controllable range (i.e., less than the angle threshold) while appropriately increasing the turning radius, thereby avoiding the problem of body skewing, material position displacement or tipping caused by excessive steering angles of the unmanned forklift, which can further enhance the safety of the unmanned forklift during material transportation.

[0038] The turning point section after route correction can be understood as a section of a set length in the first transport route with the risk turning point as the center of the section. For example, the set length can be 3 meters, 5 meters, 10 meters, etc., and the angle threshold can be 50 degrees, 70 degrees, 90 degrees, 110 degrees, etc.

[0039] In some embodiments, the forklift driving speed of each turning point section in the first transport route can be set lower than the first speed threshold, and the forklift driving speed of the non-turning point section in the first transport route can be set between the first speed threshold and the second speed threshold (the second speed threshold is greater than the first speed threshold). By setting measures to slow down the unmanned forklift during the turning process, combined with the aforementioned solution of appropriately increasing the turning radius, the risk of the unmanned forklift body skewing, material position displacement or dumping due to over-rapid turning can be further reduced, so that the safety of the unmanned forklift during material transportation is further improved.

[0040] Among them, the steering angle corresponding to the turning point section after route correction can be understood as the maximum steering angle among the multiple steering angles corresponding to the multiple position points included in the turning point section, among which the steering angle corresponding to a position point in the turning point section can be understood as the angle corresponding to the slope of the position point in the turning point section.

[0041] In some embodiments, the generated transport routes corresponding to other unmanned forklifts can be obtained first, and in the corresponding transport map, the route portion of the generated transport route during the corresponding transport period can be adjusted to a prohibited state, and then in the adjusted transport map, an initial transport route is generated according to the target profile, the transport starting point and the transport end point of the material to be transported, so as to avoid route conflicts between the initial transport route and the generated transport route.

[0042] It should be understood that, when the first detection result indicates that the multiple transportation inflection points do not include the risk inflection point, the target transportation route is determined based on the initial transportation route.

[0043] In one embodiment, determining the target transportation route according to the first transportation route includes: Determine at least one meeting section in the first transport route, wherein the meeting section is used to indicate a section in the first transport route where the first target forklift and a second target forklift meet in the opposite direction, and the second target forklift is an unmanned forklift in the unmanned forklift cluster that is different from the first target forklift; performing collision detection on each of the at least one oncoming road section according to the target contour and the virtual contour of the second target forklift corresponding to each oncoming road section to obtain a second detection result; In the case where the second detection result indicates that the at least one oncoming road section includes a risky road section, a route correction is performed on each of the risky roads sections in the first transport route to obtain a second transport route, wherein the risky road section is a oncoming road section in the at least one oncoming road section, in which the lateral distance between the corresponding second target forklift and the first target forklift is less than or equal to a distance threshold, and the lateral distance between the corresponding second target forklift and the first target forklift in the risky road section after the route correction is greater than the distance threshold; The target transportation route is determined according to the second transportation route.

[0044] In this embodiment, when the route is corrected based on the turning detection, collision detection is performed on the sections of the corrected route where there is a possibility of meeting, so as to identify the sections with high collision risk (i.e., the lateral distance between the first target forklift and the second target forklift is too close when meeting), and the route is corrected again, thereby reducing the probability of collision between multiple unmanned forklifts during the staggered driving process, so that the safety of unmanned forklifts in the material transportation process is further improved.

[0045] The second target forklift corresponding to the risky road section may be understood as other unmanned forklifts that may meet the first target forklift in the opposite direction in the risky road section.

[0046] The lateral distance between the second target forklift and the first target forklift can be understood as: when the first target forklift and the second target forklift meet each other, the shortest distance between the first target forklift and the second target forklift in a direction perpendicular to the travel direction of the forklift.

[0047] It should be understood that, different from the route correction measures made for risky turning points (increasing the turning radius, appropriately extending the turning distance, and thus reducing the steering angle), the route correction measures made for risky sections are specifically as follows: before meeting on the risky section, deflect a set distance (e.g., 0.5 meters, 1 meter, etc.) in the direction away from the second target forklift (e.g., when the second target forklift is located on the left side of the first target forklift, the first target forklift needs to deflect to the right); after the meeting on the risky section is over, deflect again a set distance in the direction of the second target forklift (e.g., when the second target forklift is located on the left side of the first target forklift, the first target forklift needs to deflect to the left) to return to the correct route.

[0048] In some embodiments, the forklift driving speed in each meeting section in the second transport route can be set to be lower than the first speed threshold, while the forklift driving speed in the non-meeting section in the first transport route can be set to be between the first speed threshold and the second speed threshold, so as to reduce the severity of the accident after the collision between the forklifts as much as possible by setting measures to slow down the unmanned forklift during the meeting process.

[0049] In one example, the second transportation route may be directly determined as the target transportation route.

[0050] It should be noted that, when the second detection result indicates that the at least one oncoming road section does not include a risky road section, the target transportation route is determined according to the first transportation route.

[0051] In one embodiment, determining at least one meeting road segment in the first transport route includes: determining a planned transportation time of the first target forklift according to the first transportation route; Determine, among a plurality of planned transport routes corresponding to the unmanned forklift cluster, a reference transport route having a time overlap with the planned transport time; At least one meeting section is determined in the first transport route according to the reference transport route.

[0052] In this embodiment, by screening out the transport routes that overlap with the planned transport time of the first target forklift from the planned routes, the amount of data and the computational complexity of subsequent processing are reduced, thereby improving the efficiency of oncoming vehicle detection.

[0053] For example, the start time of the first target forklift arriving at the transportation starting point can be predicted based on the distance between the current position of the first target forklift and the transportation starting point of the material to be transported and the set driving speed, and the set loading time (used to represent the time taken by the first target forklift to load the material to be transported) is added to the start time as the transportation start time, and then the transportation time is determined based on the first transportation route and the aforementioned set driving speed, and finally the planned transportation time of the first target forklift is calculated based on the transportation start time and the transportation time; The set driving speed may be preset or dynamically determined based on an average of actual driving speeds of multiple unmanned forklifts in the unmanned forklift cluster in a most recent speed measurement cycle.

[0054] The present application also provides a driving control system for an unmanned forklift. Figure 2 As shown, the driving control system 700 of the unmanned forklift includes: An image analysis module 701 is used to perform image analysis on the material to be transported to obtain target contour information, where the target contour information is used to indicate a projection contour of the material to be transported vertically projected onto the ground; A contour splicing module 702 is used to splice the projection contour indicated by the target contour information and the virtual body contour of the first target forklift to obtain a target contour, wherein the first target forklift is an unmanned forklift in the unmanned forklift cluster used to transport the material to be transported; The forklift control module 703 is used to generate a target transportation route of the first target forklift according to the target profile, and control the first target forklift to transport the material to be transported based on the target transportation route.

[0055] In one embodiment, the forklift control module 703 includes: A route planning unit, used for generating an initial transport route according to the target profile, the transport starting point and the transport end point of the material to be transported; a turning detection unit, configured to perform a turning detection on a plurality of transport turning points in the initial transport route to obtain a first detection result, and, if the first detection result indicates that the plurality of transport turning points include at least one risk turning point, perform a route correction on each of the risk turning points in the initial transport route to obtain a first transport route, wherein the risk turning point is a transport turning point among the plurality of transport turning points whose corresponding turning angle is greater than or equal to an angle threshold, the turning angle corresponding to the turning point section after the route correction is less than the angle threshold, and the total length of the first transport route is greater than the total length of the initial transport route, and the transport turning point is used to indicate a location point where a turn occurs in the initial transport route; A route determination unit is used to determine the target transportation route according to the first transportation route.

[0056] In one embodiment, the route determination unit is specifically configured to: Determine at least one meeting section in the first transport route, wherein the meeting section is used to indicate a section in the first transport route where the first target forklift and a second target forklift meet in the opposite direction, and the second target forklift is an unmanned forklift in the unmanned forklift cluster that is different from the first target forklift; performing collision detection on each of the at least one oncoming road section according to the target contour and the virtual contour of the second target forklift corresponding to each oncoming road section to obtain a second detection result; In the case where the second detection result indicates that the at least one oncoming road section includes a risky road section, a route correction is performed on each of the risky roads sections in the first transport route to obtain a second transport route, wherein the risky road section is a oncoming road section in the at least one oncoming road section, in which the lateral distance between the corresponding second target forklift and the first target forklift is less than or equal to a distance threshold, and the lateral distance between the corresponding second target forklift and the first target forklift in the risky road section after the route correction is greater than the distance threshold; The target transportation route is determined according to the second transportation route.

[0057] In one embodiment, determining at least one meeting road segment in the first transport route includes: determining a planned transportation time of the first target forklift according to the first transportation route; Determine, among a plurality of planned transport routes corresponding to the unmanned forklift cluster, a reference transport route having a time overlap with the planned transport time; At least one meeting section is determined in the first transport route according to the reference transport route.

[0058] In one embodiment, the image analysis module 701 includes: An image acquisition unit, used to acquire a material image of the material to be transported at the transport starting point; An image processing unit, used for performing image analysis on the material image to obtain pixel contour information, wherein the pixel contour information is used for indicating the contour of the pixel area corresponding to the material to be transported in the material image; An information conversion unit is used to convert the pixel contour information according to the spatial mapping information corresponding to the material image to obtain the target contour information, wherein the spatial mapping information is used to indicate the mapping relationship between the material image and the corresponding area in the three-dimensional space.

[0059] In one embodiment, the image processing unit is specifically used to: Correcting the material image to obtain a corrected image, wherein the corrected image is used to represent a top view of the material to be transported at the transport starting point; Performing image analysis on the corrected image to obtain the pixel contour information.

[0060] The driving control system 200 of an unmanned forklift provided in the embodiment of the present application can implement each process in the driving control method embodiment of the unmanned forklift described above, and will not be described again here to avoid repetition.

[0061] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement an embodiment of the present application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0062] like Figure 3As shown, the device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 to a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0063] A number of components in the device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0064] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSP), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as the driving control method of the unmanned forklift. For example, in some embodiments, the driving control method of the unmanned forklift may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the driving control method of the unmanned forklift described above may be executed. Alternatively, in other embodiments, the computing unit 301 may be configured to execute the driving control method of the unmanned forklift in any other appropriate manner (for example, by means of firmware).

[0065] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0066] The program code for implementing the method of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, implements the functions / operations specified in the flow chart and / or block diagram. The program code can be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0067] In the context of the present application, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0068] As used herein, the term "machine-readable medium" refers to any computer program product, apparatus, and / or device (e.g., disk, optical disk, memory, programmable logic device (PLD)) for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal for providing machine instructions and / or data to a programmable processor.

[0069] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0070] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0071] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0072] The present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above Figure 1 The various processes of the method embodiment shown can achieve the same technical effect, and will not be described again here to avoid repetition.

[0073] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution disclosed in this application can be achieved, and this document is not limited here.

[0074] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A driving control method for an unmanned forklift, characterized in that: The method comprises: Performing image analysis on the material to be transported to obtain target contour information, wherein the target contour information is used to indicate a projection contour of the material to be transported vertically projected onto the ground; splicing the projection contour indicated by the target contour information and the virtual body contour of the first target forklift to obtain a target contour, wherein the first target forklift is an unmanned forklift in the unmanned forklift cluster used to transport the material to be transported; A target transportation route of the first target forklift is generated according to the target profile, and the first target forklift is controlled to transport the material to be transported based on the target transportation route.

2. The method according to claim 1, characterized in that Generating a target transportation route of the first target forklift according to the target profile includes: Generate an initial transportation route according to the target profile, the transportation starting point and the transportation end point of the material to be transported; Performing a turn detection on a plurality of transport turning points in the initial transport route to obtain a first detection result, wherein the transport turning point is used to indicate a location point where a turn occurs in the initial transport route; In the case where the first detection result indicates that the multiple transport inflection points include at least one risk inflection point, a route correction is performed on each risk inflection point in the initial transport route to obtain a first transport route, wherein the risk inflection point is a transport inflection point whose corresponding turning angle is greater than or equal to an angle threshold among the multiple transport inflection points, the turning angle corresponding to the inflection point section after the route correction is less than the angle threshold, and the total length of the first transport route is greater than the total length of the initial transport route; The target transportation route is determined according to the first transportation route.

3. The method according to claim 2, characterized in that The determining the target transportation route according to the first transportation route comprises: Determine at least one meeting section in the first transport route, wherein the meeting section is used to indicate a section in the first transport route where the first target forklift and a second target forklift meet in the opposite direction, and the second target forklift is an unmanned forklift in the unmanned forklift cluster that is different from the first target forklift; performing collision detection on each of the at least one oncoming road section according to the target contour and the virtual contour of the second target forklift corresponding to each oncoming road section to obtain a second detection result; In the case where the second detection result indicates that the at least one oncoming road section includes a risky road section, a route correction is performed on each of the risky roads sections in the first transport route to obtain a second transport route, wherein the risky road section is a oncoming road section in the at least one oncoming road section, in which the lateral distance between the corresponding second target forklift and the first target forklift is less than or equal to a distance threshold, and the lateral distance between the corresponding second target forklift and the first target forklift in the risky road section after the route correction is greater than the distance threshold; The target transportation route is determined according to the second transportation route.

4. The method according to claim 3, characterized in that The determining at least one meeting road section in the first transport route comprises: determining a planned transportation time of the first target forklift according to the first transportation route; Determine, among a plurality of planned transport routes corresponding to the unmanned forklift cluster, a reference transport route having a time overlap with the planned transport time; At least one meeting section is determined in the first transport route according to the reference transport route.

5. The method according to claim 1, characterized in that The image analysis of the material to be transported is performed to obtain target contour information, including: Collecting a material image of the material to be transported at the transport starting point; Performing image analysis on the material image to obtain pixel contour information, where the pixel contour information is used to indicate the contour of a pixel area corresponding to the material to be transported in the material image; The pixel contour information is converted according to the spatial mapping information corresponding to the material image to obtain the target contour information, wherein the spatial mapping information is used to indicate a mapping relationship between the material image and a corresponding area in a three-dimensional space.

6. The method according to claim 5, characterized in that The performing image analysis on the material image to obtain pixel contour information includes: Correcting the material image to obtain a corrected image, wherein the corrected image is used to represent a top view of the material to be transported at the transport starting point; Performing image analysis on the corrected image to obtain the pixel contour information.

7. A driving control system for an unmanned forklift, characterized in that: The system comprises: An image analysis module is used to perform image analysis on the material to be transported to obtain target contour information, wherein the target contour information is used to indicate a projection contour of the material to be transported vertically projected onto the ground; a contour splicing module, configured to splice the projection contour indicated by the target contour information and the virtual body contour of a first target forklift to obtain a target contour, wherein the first target forklift is an unmanned forklift in an unmanned forklift cluster used for transporting the material to be transported; The forklift control module is used to generate a target transportation route of the first target forklift according to the target profile, and control the first target forklift to transport the material to be transported based on the target transportation route.

8. An electronic device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the steps of the method according to any one of claims 1 to 6 when executed by the processor.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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

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