Lifting equipment detection method and apparatus, device, storage medium and vehicle

Abstract

A lifting equipment detection method and apparatus (50), a device (60), a storage medium, and a vehicle (103). The method comprises: acquiring target point cloud data of a target overhead crane device (101) (S201); when the target point cloud data satisfies a preset condition, generating target detection information (S202); and determining a target driving path on the basis of the target detection information (S203). The vehicle (103) automatically acquires target point cloud data of a target overhead crane device (101). When the target point cloud data satisfies the preset condition, it is determined that there is currently a critical scenario for the target overhead crane device (101). Target detection information can be generated, and subsequently, path planning and decision making can be performed on the basis of the target detection information, to determine a target driving path for the vehicle (103) to advance. The vehicle (103) can implement lifting equipment detection on the basis of the point cloud data of the overhead crane device (101), and perform path planning on the basis of the detection information, so that the safety risk of the vehicle (103) traveling during port operations can be reduced, and the occurrence of safety accidents can be avoided to a certain extent.

Description

Spreader detection method, device, equipment, storage medium and vehicle

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on January 22, 2024, with application number 202410088893.3 and application name “Spreader Detection Method, Device, Equipment, Storage Medium and Vehicle”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of autonomous driving technology, and in particular to a method, device, equipment, storage medium and vehicle for detecting a sling. Background Art

[0003] In actual scenarios such as ports, bridge crane equipment usually requires a crane to load and unload containers. Due to the complex on-site operating environment, bridge crane equipment may improperly grasp the container during the loading and unloading operation, causing the container to fall and causing safety accidents.

[0004] The scenario in which bridge crane equipment hangs containers on a crane is called heavy-closing. Due to the lack of detection and judgment of lifting equipment for heavy-closing and other scenarios in related technologies, the safety risk of vehicles traveling during port operations is high, which can easily lead to safety accidents. Summary of the Invention

[0005] The present application provides a sling detection method, device, equipment, storage medium and vehicle, which can reduce the safety risks of vehicle movement during port operations and avoid the occurrence of safety accidents to a certain extent.

[0006] In a first aspect, an embodiment of the present application provides a method for detecting a spreader, comprising:

[0007] Obtain target point cloud data of target bridge crane equipment;

[0008] When the target point cloud data meets the preset conditions, generating target detection information;

[0009] A target driving path is determined based on the target detection information.

[0010] In a possible implementation, obtaining target point cloud data of a target bridge crane device includes:

[0011] Determine the vehicle's driving area based on the vehicle's current driving path;

[0012] When a target crane exists in the vehicle driving area, target point cloud data corresponding to the target crane is acquired.

[0013] In one possible implementation, the method further includes:

[0014] Performing a point cloud search at a preset height to determine the target beam corresponding to the target bridge crane equipment;

[0015] Determining a target spatial range corresponding to the target beam within the vehicle driving area;

[0016] When a point cloud exists within the target space, it is determined that a target crane exists within the vehicle driving area.

[0017] In one possible implementation, the method further includes:

[0018] Determining the point cloud density corresponding to the target bridge crane equipment according to the target point cloud data;

[0019] When the point cloud density is greater than or equal to a preset threshold, it is determined that the target point cloud data meets the preset condition.

[0020] In one possible implementation, the method further includes:

[0021] When the target point cloud data does not meet the preset conditions, the vehicle is controlled to continue traveling based on the current driving path.

[0022] In a possible implementation, determining the target driving path based on the target detection information includes:

[0023] Re-plan the path based on the target detection information to obtain the target driving path; or

[0024] According to the target detection information, the vehicle is controlled to enter a waiting state.

[0025] In a second aspect, an embodiment of the present application provides a sling detection device, comprising:

[0026] An acquisition module is used to obtain target point cloud data of a target bridge crane device;

[0027] A generating module, configured to generate target detection information when the target point cloud data meets a preset condition;

[0028] A determination module is used to determine a target driving path based on the target detection information.

[0029] In a possible implementation, the acquisition module is specifically configured to:

[0030] Determine the vehicle's driving area based on the vehicle's current driving path;

[0031] When a target crane exists in the vehicle driving area, target point cloud data corresponding to the target crane is acquired.

[0032] In one possible embodiment, the device is further used for:

[0033] Performing a point cloud search at a preset height to determine the target beam corresponding to the target bridge crane equipment;

[0034] Determining a target spatial range corresponding to the target beam within the vehicle driving area;

[0035] When a point cloud exists within the target space, it is determined that a target crane exists within the vehicle driving area.

[0036] In one possible embodiment, the device is further used for:

[0037] Determining the point cloud density corresponding to the target bridge crane equipment according to the target point cloud data;

[0038] When the point cloud density is greater than or equal to a preset threshold, it is determined that the target point cloud data meets the preset condition.

[0039] In one possible embodiment, the device is further used for:

[0040] When the target point cloud data does not meet the preset conditions, the vehicle is controlled to continue traveling based on the current driving path.

[0041] In a possible implementation, the determining module is specifically configured to:

[0042] Re-plan the path based on the target detection information to obtain the target driving path; or

[0043] According to the target detection information, the vehicle is controlled to enter a waiting state.

[0044] In a third aspect, an embodiment of the present application provides a spreader detection device, comprising: a processor, a memory;

[0045] The memory stores computer-executable instructions;

[0046] The processor executes the computer-executable instructions stored in the memory to implement the spreader detection method as described in any one of the first aspects.

[0047] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, which, when executed, are used to implement the sling detection method described in any one of the first aspects.

[0048] In a fifth aspect, an embodiment of the present application provides a vehicle comprising the sling detection device described in the third aspect.

[0049] The embodiments of the present application provide a method, apparatus, device, storage medium, and vehicle for detecting a sling, wherein the vehicle obtains target point cloud data of a target bridge crane device; generates target detection information when the target point cloud data meets preset conditions; and determines a target driving path based on the target detection information. In the present application, the vehicle automatically obtains target point cloud data of a target bridge crane device, and when the target point cloud data meets preset conditions, determines that a critical scene currently exists for the target bridge crane device, and can generate target detection information. Subsequently, path planning and decision-making can be performed based on the target detection information to determine the target driving path for the vehicle. In this way, the vehicle can detect the sling based on the point cloud data of the bridge crane device, and perform path planning based on the detection information, which can reduce the safety risks of vehicle travel during port operations and avoid the occurrence of safety accidents to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] FIG1 is a schematic diagram of an application scenario provided by an embodiment of the present application;

[0051] FIG2 is a schematic flow chart of a method for detecting a spreader provided in an embodiment of the present application;

[0052] FIG3 is a flow chart of another method for detecting a spreader provided in an embodiment of the present application;

[0053] FIG4 is a schematic diagram of execution logic of a spreader detection provided by an embodiment of the present application;

[0054] FIG5 is a schematic structural diagram of a spreader detection device provided in an embodiment of the present application;

[0055] FIG6 is a schematic structural diagram of a sling detection device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] To enable those skilled in the art to better understand the technical solution of the present application, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments and drawings described herein are only used to explain the present application and are not intended to limit the present application.

[0057] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0058] In related technologies, when loading and unloading containers at ports, there may be cases where the crane improperly grasps the container, causing it to fall and causing a safety accident. The scenario where a crane hangs a container on the vehicle's route is called a heavy check. To ensure production safety, the vehicle needs to change lanes or stop and wait when the crane is at a heavy check. In the scenario of autonomous driving of port vehicles, related technologies generally do not have crane detection and judgment for scenarios such as heavy checks, resulting in a high safety risk for vehicles traveling during port operations, which can easily lead to safety accidents.

[0059] In order to solve the above problems, the present application provides a hoist detection method, device, equipment, storage medium and vehicle. Unmanned container trucks and other autonomous driving vehicles can automatically obtain target point cloud data of target bridge crane equipment in scenarios such as bridge approach operations, and when the target point cloud data meets the preset conditions, it can be determined that the target bridge crane equipment currently has a critical scene, and target detection information can be generated. Subsequently, path planning and decision-making can be performed based on the target detection information to determine the target driving path of the vehicle.

[0060] Figure 1 is a schematic diagram of an application scenario provided by an embodiment of the present application. Please refer to Figure 1, which includes a bridge crane 101, a container 102, and a vehicle 103, wherein the bridge crane may include a crane 1011. As shown in Figure 1, in scenarios such as ports, the bridge crane 101 suspends the container 102 through the crane 1011 for loading and unloading operations, and the vehicle 103 is an autonomous driving vehicle that needs to travel through the bridge crane 101. The scenario in which the crane 1011 suspends the container 102 is a heavy-duty operation. The relevant technology lacks the detection and judgment of the sling for scenarios such as heavy-duty operations. If the vehicle 103 passes under the container 102 suspended in the air, it is easy for a safety accident caused by the container 102 falling off to occur, and the safety risk is relatively high.

[0061] In an embodiment of the present application, vehicle 102 obtains target point cloud data of the bridge crane device 101, and determines whether the bridge crane device 101 has a container 102 suspended based on the target point cloud data, that is, a sling detection is performed based on the target point cloud data. When a container 102 is suspended, vehicle 102 generates target detection information and replans the driving path according to the target detection information to avoid passing directly under the suspended container, thereby reducing safety risks.

[0062] The following is a detailed description of the solutions shown in this application through specific embodiments. It should be noted that the following embodiments can exist independently or in combination with each other, and the same or similar contents will not be repeated in different embodiments.

[0063] FIG2 is a flow chart of a method for detecting a spreader provided in an embodiment of the present application. Referring to FIG2 , the spreader detection method may include:

[0064] S201. Obtain target point cloud data of the target bridge crane equipment.

[0065] The execution subject of the embodiments of the present application can be a vehicle, specifically a control system in the vehicle (such as an unmanned driving system, a path planning system, etc.), or a spreader detection device provided in the vehicle. The spreader detection device can be implemented by software or by a combination of software and hardware. For ease of understanding, the following description will be made using a vehicle as an example. The vehicle can be an unmanned vehicle, specifically an unmanned container truck used for container transportation, loading and unloading in a port scenario.

[0066] In the embodiments of the present application, the target crane device may refer to a crane device found in a real-world scenario, such as a port. The crane device may include a crane and two parallel beams, with the crane being able to move between the two beams to grab containers for loading and unloading. The target point cloud data may refer to a point cloud corresponding to the target crane device. The target point cloud data may be used to represent the object shape of the target crane device in three-dimensional space and may be composed of a series of points, each of which has corresponding coordinate values ​​and other attribute values.

[0067] In this step, a laser radar can be installed on the roof of the unmanned vehicle. When the vehicle is moving, the laser radar can be used to scan and obtain the target point cloud data of the target bridge crane equipment. The target point cloud data can reflect the real-time status of the bridge crane equipment. Subsequently, it can be determined whether the bridge crane equipment is hanging a container based on the target point cloud data.

[0068] S202: When the target point cloud data meets preset conditions, generate target detection information.

[0069] In the embodiment of the present application, the preset condition may refer to a pre-set threshold condition, such as the point cloud density of the crane position of the target bridge crane equipment is greater than or equal to the preset threshold, etc. The point cloud density may refer to the number of points contained in a unit space. Since the number of point clouds of the crane itself is fixed, and the volume of the container is large, when the target bridge crane equipment is hanging a container, the point cloud density of the crane position will increase significantly. At this time, it can be determined whether the target bridge crane equipment is hanging a container based on the size relationship between the point cloud density of the crane position and the preset threshold. Of course, the preset condition can also be other judgment conditions, such as the number of point clouds, etc., which can be flexibly configured based on actual needs, and the embodiment of the present application does not limit this.

[0070] Target detection information may refer to detection information generated by the vehicle upon determining that a container is suspended from a target crane, and may be used to instruct the vehicle to subsequently re-route. In this step, after acquiring target point cloud data, the vehicle may further determine whether the target point cloud data meets preset conditions. If the target point cloud data meets the preset conditions, the vehicle may determine that a container is suspended from the target crane, generate target detection information, and subsequently re-route the vehicle based on this target detection information.

[0071] S203: Determine the target driving path based on the target detection information.

[0072] In the embodiments of the present application, the target driving path may refer to the driving path obtained after the vehicle re-plans and makes decisions. After generating target detection information, the vehicle can re-plan its path using a path planning system, etc., to obtain the target driving path and travel based on the target driving path, thereby avoiding passing directly under suspended containers and reducing safety risks.

[0073] The embodiment of the present application provides a method for detecting a sling, in which a vehicle obtains target point cloud data of a target bridge crane device; generates target detection information when the target point cloud data meets preset conditions; and determines a target driving path based on the target detection information. In the present application, the vehicle automatically obtains target point cloud data of a target bridge crane device, and when the target point cloud data meets preset conditions, determines that a critical scene currently exists in the target bridge crane device, and can generate target detection information. Subsequently, path planning and decision-making can be performed based on the target detection information to determine the target driving path of the vehicle. In this way, the vehicle can detect the sling based on the point cloud data of the bridge crane device, and perform path planning based on the detection information, which can reduce the safety risks of vehicle travel during port operations and avoid the occurrence of safety accidents to a certain extent.

[0074] Based on the above embodiment, FIG3 is a flow chart of another method for detecting a spreader provided in an embodiment of the present application. Referring to FIG3 , the method for detecting a spreader may include:

[0075] S301. Perform a point cloud search at a preset height to determine the target beam corresponding to the target bridge crane equipment.

[0076] In the embodiment of the present application, the preset height may refer to a pre-set height value, specifically 8 meters, 12 meters, 15 meters, etc., and may be specifically set based on the height of the bridge crane equipment in the actual port scene, and the embodiment of the present application does not limit this. The target beam may refer to the two parallel beams included in the target bridge crane equipment. While the vehicle is moving, it can use detection equipment such as laser radar to perform a point cloud search at a preset height to determine the target beam of the target bridge crane equipment. The actual position of the crane of the target bridge crane equipment can then be determined based on the target beam.

[0077] S302: Determine a vehicle driving area based on the vehicle's current driving path.

[0078] In the embodiment of the present application, the current driving path may refer to the current route of the vehicle. The vehicle driving area may refer to the area corresponding to the vehicle's route. Due to the large size of the container, the coverage area when the container falls off is also large. Based on the current driving path, the vehicle can determine the vehicle's driving area according to the preset area value. The preset area value may include an outward extension of 3 meters on both sides of the vehicle's current driving path. In this way, the vehicle can further improve the safety of the vehicle's movement by determining the vehicle's driving area based on the current driving path and subsequently detecting whether the sling has a heavy gate based on the vehicle's driving area.

[0079] S303: Determine a target spatial range corresponding to the target beam within the vehicle driving area.

[0080] In this embodiment of the present application, the target spatial range may refer to the three-dimensional spatial range corresponding to the target beam. This target spatial range may be determined based on the coordinate position of the target beam, which is not limited in this embodiment of the present application. After the vehicle determines the target beam of the target bridge crane through point cloud search, since the crane of the target bridge crane typically moves between the target beams, the vehicle may perform a point cloud search within the target spatial range corresponding to the target beam to determine whether the target bridge crane includes the crane.

[0081] S304: When a point cloud exists within the target space, determine that a target crane exists within the vehicle driving area.

[0082] In the embodiment of the present application, the target crane may refer to the crane part of the target bridge crane equipment. Since there may be a large number of bridge crane equipment in scenes such as ports, some bridge crane equipment may not be put into use, and there may be situations where the bridge crane equipment has no crane operation. On this basis, the vehicle can perform a point cloud search within the target space range corresponding to the target beam. If a point cloud exists, the vehicle can determine that there is a target crane in the vehicle's driving area, and then the target point cloud data corresponding to the target crane can be collected to detect whether there is a re-closing of the hoist. If there is no point cloud, the vehicle can determine that there is no target crane in the vehicle's driving area. At this time, the vehicle can determine that there is no re-closing situation at present, and the vehicle can move along the original path.

[0083] S305 : When there is a target crane in the vehicle driving area, obtain target point cloud data corresponding to the target crane.

[0084] In an embodiment of the present application, when the vehicle searches for a point cloud within the target space range, the vehicle can determine that there is a target crane in the vehicle's driving area. At this time, the target point cloud data corresponding to the target crane can be obtained, and subsequently it can be determined whether the target crane includes a container based on the target point cloud data.

[0085] S306: When the target point cloud data meets the preset conditions, generate target detection information.

[0086] In a possible implementation, whether the target point cloud data meets the preset conditions can be determined in the following manner:

[0087] According to the target point cloud data, the point cloud density corresponding to the target bridge crane equipment is determined; when the point cloud density is greater than or equal to the preset threshold, it is determined that the target point cloud data meets the preset conditions.

[0088] In the embodiment of the present application, the preset threshold may refer to a pre-set point cloud density threshold, which may be set based on the type of LiDAR, and is not limited in the embodiment of the present application. After acquiring the target point cloud data, the vehicle may further determine the point cloud density corresponding to the target crane of the target bridge crane. If the point cloud density is greater than or equal to the preset threshold, the vehicle may determine that the target point cloud data meets the preset condition, and the target bridge crane is currently suspending a container within the vehicle's travel area.

[0089] S307: re-plan the path based on the target detection information to obtain the target driving path; or, control the vehicle to enter a waiting state based on the target detection information.

[0090] In this embodiment of the present application, after generating target detection information, the vehicle can re-plan its path. Based on the path planning decision, the vehicle can execute a lane change to obtain a target driving path to avoid the suspended container. The vehicle can also control the vehicle to enter a waiting state based on the target detection information to avoid passing directly under the suspended container. During the waiting process, the vehicle can periodically obtain target point cloud data of the target bridge crane device and continue to move when the target point cloud data does not meet the preset conditions, that is, when the target bridge crane device is not suspended by a container.

[0091] S308 : When the target point cloud data does not meet the preset conditions, control the vehicle to continue traveling based on the current driving path.

[0092] In an embodiment of the present application, when the target point cloud data does not meet the preset conditions, the vehicle can determine that the target bridge crane equipment does not suspend a container, and the vehicle can continue to move based on the current driving path.

[0093] It should be noted that in the various embodiments of the present application, the size of the serial number of each step does not mean the order of execution. The order of execution of each step should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0094] Based on the above embodiments, Figure 4 is a schematic diagram of the execution logic of a sling detection provided by an embodiment of the present application. As shown in Figure 4, the vehicle uses a laser radar to perform a point cloud search at a preset height to determine the target beam of the target bridge crane equipment; after determining the position of the target beam, since the crane moves between the beams, the vehicle can perform a point cloud search within the target space corresponding to the target beam, and at the same time, it can determine the vehicle driving area based on the vehicle's current driving path, and then determine whether there is a target crane within the vehicle driving area. If there is no point cloud within the target space, the vehicle can determine that there is no crane in the target bridge crane equipment, and there is no double-closing situation at this time.

[0095] If there is a point cloud within the target space, the vehicle can determine that there is a target crane within the vehicle's driving area. The vehicle can obtain the target point cloud data corresponding to the target crane and further determine whether the target point cloud data meets the preset conditions. If the target point cloud data does not meet the preset conditions, the vehicle can determine that there is no double-checking situation and can continue to move along the current driving path. If the target point cloud data meets the preset conditions, the vehicle can determine that the target bridge crane equipment is suspended with a container and there is a double-checking situation. The vehicle can generate target detection information and report the target detection information to the path planning system. The path planning system re-plans the path, makes decisions, and determines the target driving path to avoid safety risks of the vehicle.

[0096] In the embodiments of the present application, autonomous vehicles such as unmanned container trucks can use detection equipment such as laser radar to obtain target point cloud data of target bridge crane equipment during bridge approach operations, and perform real-time detection of whether the spreader is heavy or not based on the target point cloud data. This can ensure the safety of the vehicle's movement and avoid safety accidents caused by container detachment. In this way, during the autonomous driving process, due to the presence of crane equipment in special scenarios such as ports, the vehicle can not only detect ground targets, but also perform spreader detection such as heavy or not on suspended targets such as cranes and containers, thus ensuring the safety of vehicle passage.

[0097] The spreader detection method in the embodiments of this application can be implemented through the vehicle's unmanned driving system and path planning system. Specifically, the spreader detection method can be deployed in the embedded platform of the vehicle's unmanned driving system. The unmanned driving system automatically performs spreader detection during operation and uploads the target detection information to the path planning system, which then makes path decisions and determines the target driving path. In this way, the vehicle can effectively perform spreader detection on the bridge crane with a high detection success rate, which can meet the needs of actual production and ensure the safety of the operation system.

[0098] FIG5 is a schematic diagram of the structure of a spreader detection device provided in an embodiment of the present application. Referring to FIG5 , the spreader detection device 50 may include:

[0099] An acquisition module 51 is used to acquire target point cloud data of a target bridge crane device;

[0100] A generating module 52 is used to generate target detection information when the target point cloud data meets the preset conditions;

[0101] The determination module 53 is configured to determine the target driving path based on the target detection information.

[0102] In a possible implementation, the acquisition module 51 is specifically configured to:

[0103] Determine the vehicle's driving area based on the vehicle's current driving path;

[0104] When there is a target crane in the vehicle driving area, target point cloud data corresponding to the target crane is obtained.

[0105] In one possible implementation, the device 50 is further configured to:

[0106] Perform point cloud search at a preset height to determine the target beam corresponding to the target bridge crane equipment;

[0107] Determine the target spatial range corresponding to the target beam within the vehicle driving area;

[0108] When a point cloud exists within the target space, it is determined that a target crane exists within the vehicle driving area.

[0109] In one possible implementation, the device 50 is further configured to:

[0110] According to the target point cloud data, determine the point cloud density corresponding to the target bridge crane equipment;

[0111] When the point cloud density is greater than or equal to a preset threshold, it is determined that the target point cloud data meets the preset condition.

[0112] In one possible implementation, the device 50 is further configured to:

[0113] If the target point cloud data does not meet the preset conditions, the vehicle is controlled to continue driving based on the current driving path.

[0114] In a possible implementation, the determination module 53 is specifically configured to:

[0115] Based on the target detection information, re-plan the path and obtain the target driving path; or

[0116] According to the target detection information, the vehicle is controlled to enter the waiting state.

[0117] The sling detection device 50 provided in the embodiment of the present application can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar and will not be repeated here.

[0118] FIG6 is a schematic diagram of the structure of a spreader detection device provided in an embodiment of the present application. Referring to FIG6 , the spreader detection device 60 may include: a memory 61 and a processor 62. Exemplarily, the memory 61 and the processor 62 are interconnected via a bus 63.

[0119] The memory 61 is used to store program instructions;

[0120] The processor 62 is configured to execute program instructions stored in the memory to implement the spreader detection method shown in the above embodiment.

[0121] The spreader detection device 60 shown in FIG6 can implement the technical solution shown in the above method embodiment, and its implementation principle and beneficial effects are similar, which will not be described in detail here.

[0122] An embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above-mentioned spreader detection method.

[0123] The embodiment of the present application may also provide a sling detection vehicle, including the above-mentioned sling detection device, which can implement the above-mentioned sling detection method.

[0124] It should be noted that the processor mentioned in the embodiments of the present application may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0125] It should be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DR RAM). It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, the memory (storage module) is integrated into the processor. It should be noted that the memory described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0126] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0127] The present application embodiment is described with reference to the flow chart and / or block diagram according to the method, device (system) and computer program product of the embodiment of the present application.It should be understood that each flow process and / or box in the flow chart and / or block diagram and the combination of the flow process and / or box in the flow chart and / or block diagram can be realized by computer program instructions.These computer program instructions can be provided to the processing unit of general-purpose computer, special-purpose computer, embedded processing machine or other programmable data processing equipment to produce a machine, so that the instruction executed by the processing unit of computer or other programmable data processing equipment produces the device for realizing the function specified in one flow chart flow chart or multiple flow charts and / or one block or multiple blocks of block diagram.

[0128] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0129] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0130] Regarding the various modules / units contained in the various devices and products described in the above embodiments, they can be software modules / units, hardware modules / units, or partly software modules / units and partly hardware modules / units. Each device and product can be applied to or integrated into a chip, a chip module or a terminal device. For example, for each device and product applied to or integrated into a chip, the various modules / chips contained therein can be all implemented in the form of hardware such as circuits, or at least part of the modules / units can be implemented in the form of software programs, which run on a processor integrated inside the chip, and the remaining modules / units can be implemented in the form of hardware such as circuits.

[0131] In this application, the term "include" and its variations may refer to non-restrictive inclusion; the term "or" and its variations may refer to "and / or". In this application, the terms "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. In this application, "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship.

[0132] The above are only some embodiments of the present application. 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 application. These improvements and modifications should also be regarded as within the scope of protection of the present application.

Claims

1. A sling detection method, characterized in that, Including: Obtaining target point cloud data of a target gantry crane device; Generating target detection information when the target point cloud data meets a preset condition; Determining a target driving path based on the target detection information.

2. The method according to claim 1, wherein The obtaining of the target point cloud data of the target gantry crane device includes: Determining a vehicle driving area according to the current driving path of the vehicle; When there is a target crane in the vehicle driving area, obtaining the target point cloud data corresponding to the target crane.

3. The method according to claim 2, wherein The method further includes: Performing point cloud search at a preset height to determine a target crossbeam corresponding to the target gantry crane device; Determining a target space range corresponding to the target crossbeam within the vehicle driving area; When there is point cloud within the target space range, determining that there is a target crane within the vehicle driving area.

4. The method according to claim 1, characterized in that, The method further includes: Determining a point cloud density corresponding to the target gantry crane device according to the target point cloud data; When the point cloud density is greater than or equal to a preset threshold, determining that the target point cloud data meets the preset condition.

5. The method according to claim 1, wherein The method further includes: When the target point cloud data does not meet the preset condition, controlling the vehicle to continue driving based on the current driving path.

6. The method according to claim 1, wherein The determining of the target driving path based on the target detection information includes: According to the target detection information, re-making a path planning decision to obtain the target driving path; or, According to the target detection information, controlling the vehicle to enter a waiting state.

7. A sling detection device, characterized in that, Including: An obtaining module, configured to obtain target point cloud data of a target gantry crane device; A generating module, configured to generate target detection information when the target point cloud data meets a preset condition; A determining module, configured to determine a target driving path based on the target detection information.

8. A sling detection device, characterized in that, Including: A processor and a memory; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the spreader detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, Computer execution instructions are stored in the computer-readable storage medium, and when the computer execution instructions are executed, they are used to implement the spreader detection method according to any one of claims 1 to 6.

10. A sling detection vehicle, characterized in that, Including the spreader detection device according to claim 8.

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