Safety control method and computer equipment for lift based on articulated boom truck

Abstract

The present application relates to the field of safety control of lifts based on articulated boom trucks, and specifically to a safety control method and computer equipment for lifts based on articulated boom trucks. A specific implementation of the method includes: controlling the articulated boom truck to travel to a target area according to an optimized travel route of the articulated boom truck; controlling a camera device provided on the articulated boom truck to capture a regional image of the target area; inputting a set of regional sub-images into a pre-trained ground area flat plane recognition model; determining the regional sub-image corresponding to the flat plane recognition result of each regional sub-image that meets the target condition as an alternative regional sub-image; controlling the articulated boom truck to travel to the area corresponding to the target regional sub-image; controlling the lift of the articulated boom truck to rise to the target position, and detecting the pressure data of each arm in real time, and detecting the current horizontal state information. This implementation can detect the pressure of each arm of the lift and the horizontal state of the articulated boom truck in real time to avoid safety hazards.

Description

Technical Field

[0001] The present application relates to the field of articulated boom lift safety control, and specifically to an articulated boom lift safety control method and computer equipment. Background Art

[0002] The articulated boom truck is a type of aerial work vehicle that can transport workers and staff to the site for aerial work. The articulated boom truck is easy to move, has a compact structure, uses new high-quality steel, has high strength and light weight, is directly connected to AC power or uses the vehicle's own power to start, has a fast erection speed, has a telescopic arm, and the workbench can be raised and extended, making it easy to cross obstacles to reach the working position. It is an ideal aerial work equipment.

[0003] When the articulated boom truck is performing construction, the blind spots in the field of vision and non-standard operation during manual operation may cause the articulated boom truck to collide with the equipment and facilities at the construction site in a complex environment, requiring multiple adjustments and easily creating safety hazards.

[0004] In addition, when the articulated boom truck is carrying out construction, the selection of the docking location is often done through manual screening, which requires multiple adjustments, and the horizontal state of the articulated boom truck cannot be monitored in real time, which can easily lead to safety hazards. Summary of the invention

[0005] The content of this application is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this application is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0006] Some embodiments of the present application propose a lift safety control method based on a boom truck, a computer device and a computer-readable storage medium to solve the technical problems mentioned in the above background technology section.

[0007] In a first aspect, some embodiments of the present application provide a method for controlling a safe lift based on an articulated boom truck, the method comprising: in response to the articulated boom truck receiving a task instruction corresponding to a target area, determining a starting position corresponding to the articulated boom truck and an end position of the target area; generating an initial articulated boom truck driving route based on the starting position and the end position; optimizing the initial articulated boom truck driving route to obtain an optimized articulated boom truck driving route; controlling the articulated boom truck to travel to the target area based on the optimized articulated boom truck driving route; in response to determining that the articulated boom truck has traveled to the target area, controlling a camera device provided on the articulated boom truck to capture an area image of the target area; performing area segmentation processing on the area image to obtain an area sub-image set; inputting the area sub-image set into a pre-trained ground area flattening plane recognition model to obtain an area sub-image flattening plane recognition result set, wherein one area sub-image corresponds to one area sub-image leveling plane recognition result; in response to determining that there is a regional sub-image leveling plane recognition result that meets the target condition in the above-mentioned regional sub-image leveling plane recognition result set, the regional sub-image corresponding to each regional sub-image leveling plane recognition result that meets the target condition is determined as a candidate regional sub-image, and a candidate regional sub-image group is obtained; the target regional sub-image is selected from the above-mentioned candidate regional sub-image group, and the above-mentioned articulated boom vehicle is controlled to travel to the area corresponding to the above-mentioned target regional sub-image; the lift of the above-mentioned articulated boom vehicle is controlled to rise to the target position, and the pressure sensors between the various arms of the lift are controlled in real time to detect the pressure data of each arm in real time, and the vehicle level of the above-mentioned articulated boom vehicle is controlled to detect the current horizontal status information; in response to determining that there is abnormal pressure data in the collected pressure data, and / or the horizontal status information meets the abnormal horizontal condition, the associated alarm device is controlled to issue an alarm prompt, and the lift of the above-mentioned articulated boom vehicle is controlled to fall back to the initial position.

[0008] In a second aspect, the present application also provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the method described in any implementation of the first aspect is implemented.

[0009] In a third aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the method described in any implementation of the first aspect is implemented.

[0010] The above-mentioned embodiments of the present application have the following beneficial effects: the articulated boom truck can automatically drive to the target area for operation through the optimal driving path, without the need for supervisors to implement supervision, and without the need for manual control of the driving of the articulated boom truck, which not only reduces the cost of the articulated boom truck in complex construction scenes, but also improves safety. In addition, a relatively flat parking area can be selected in the target area through image recognition to ensure the horizontal stability of the articulated boom truck. In addition, the pressure of each arm of the elevator and the horizontal state of the articulated boom truck can be detected in real time through the pressure sensor and the vehicle level to avoid safety hazards. First, in response to the articulated boom truck receiving the task instruction corresponding to the target area, the starting position corresponding to the articulated boom truck and the end position of the target area are determined; according to the starting position and the end position, the initial articulated boom truck driving route is generated; the initial articulated boom truck driving route is optimized to obtain the optimized articulated boom truck driving route. Thus, the initial driving route can be determined to determine each feasible route node, so as to avoid the high time complexity and low efficiency of generating routes caused by the insertion method under the uncertainty of each feasible route node. Secondly, according to the above-mentioned optimized driving route of the articulated boom, the above-mentioned articulated boom is controlled to travel to the above-mentioned target area; in response to determining that the above-mentioned articulated boom travels to the above-mentioned target area, the camera device set on the above-mentioned articulated boom is controlled to capture the regional image of the above-mentioned target area; the above-mentioned regional image is subjected to regional segmentation processing to obtain a set of regional sub-images; the above-mentioned set of regional sub-images is input into a pre-trained ground area flat plane recognition model to obtain a set of regional sub-image flat plane recognition results, wherein one regional sub-image corresponds to one regional sub-image flat plane recognition result. In this way, a flat area that can be docked in the working area can be identified. In response to determining that there is a regional sub-image flat plane recognition result that meets the target condition in the above-mentioned regional sub-image flat plane recognition result set, the regional sub-image corresponding to each regional sub-image flat plane recognition result that meets the target condition is determined as an alternative regional sub-image to obtain an alternative regional sub-image group; the target regional sub-image is selected from the above-mentioned alternative regional sub-image group, and the above-mentioned articulated boom is controlled to travel to the area corresponding to the above-mentioned target regional sub-image. Thus, a relatively flat parking area can be selected in the target area through image recognition, so as to ensure the horizontal stability of the articulated boom truck. Finally, the lift of the articulated boom truck is controlled to rise to the target position, and the pressure sensors between the arms of the lift are controlled in real time to detect the pressure data of each arm in real time, and the vehicle level of the articulated boom truck is controlled to detect the current horizontal state information; in response to determining that there is abnormal pressure data in the collected pressure data, and / or the horizontal state information meets the abnormal horizontal condition, the associated alarm device is controlled to issue an alarm prompt, and the lift of the articulated boom truck is controlled to fall back to the initial position.Therefore, through the pressure sensor and the vehicle level meter, the pressure of each arm of the lift and the horizontal state of the articulated boom truck can be detected in real time to avoid safety hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other features, advantages and aspects of the embodiments of the present application will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar figure labels represent the same or similar elements. It should be understood that the drawings are schematic and that the components and elements are not necessarily drawn to scale.

[0012] Figure 1 is a flow chart of some embodiments of a lift safety control method based on a boom truck according to the present application;

[0013] Figure 2 It is a schematic diagram of the structure of a computer device suitable for implementing some embodiments of the present application. DETAILED DESCRIPTION

[0014] Embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0015] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0016] It should be noted that the concepts such as "first" and "second" mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0017] It should be noted that the modifications of "one" and "plurality" mentioned in the present application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0018] The names of the messages or information exchanged between multiple devices in the embodiments of the present application are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0019] The present application will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0020] Figure 11 is a flowchart of some embodiments of the articulated boom lift safety control method according to the present application. 100 of some embodiments of the articulated boom lift safety control method according to the present application is shown. The articulated boom lift safety control method comprises the following steps:

[0021] Step 101, in response to a boom truck receiving a task instruction corresponding to a target area, determining a starting position corresponding to the boom truck and an end position of the target area.

[0022] In some embodiments, the execution subject (e.g., computer device) of the articulated boom lift safety control method may determine the starting position corresponding to the articulated boom lift and the end position of the target area in response to the articulated boom lift receiving a task instruction corresponding to the target area. The target area may refer to an area to be constructed (e.g., an infrastructure site). The task instruction may be an instruction to instruct the articulated boom lift to perform a lifting task in the target area. The starting position may refer to the current position of the articulated boom lift.

[0023] Step 102: Generate an initial articulated boom truck driving route based on the above starting point and end point.

[0024] In some embodiments, the execution subject may generate an initial articulated boom driving route according to the starting position and the end position. For example, the initial articulated boom driving route between the starting position and the end position may be found by a preset heuristic search algorithm. For example, the heuristic search algorithm may be an A* (A Star) algorithm.

[0025] Step 103, optimizing the initial articulated boom driving route to obtain an optimized articulated boom driving route.

[0026] In some embodiments, the execution entity may optimize the initial articulated boom truck driving route to obtain an optimized articulated boom truck driving route.

[0027] In an actual application scenario, the execution entity can optimize the initial articulated boom vehicle driving route through the following steps:

[0028] In the first step, the distance matrix and the route matrix corresponding to the above-mentioned starting position and the above-mentioned end position are determined by using the interpolation method. The interpolation method can be the Floyd-Warshall algorithm. Among them, the distance matrix can represent the node distance between each route node between the starting position and the end position. The route matrix can represent the route information between each route node between the starting position and the end position. Each route node can be each pre-set landmark route node, or each route node set according to the driving time or driving distance.

[0029] In the second step, based on the distance matrix and the route matrix, the node routes between the route nodes in the initial articulated boom truck driving route are optimized to obtain the optimized articulated boom truck driving route.

[0030] The execution subject may optimize the node routes between the route nodes in the initial articulated boom vehicle driving route by the following steps:

[0031] Step 1: determine the route node sequence corresponding to the initial articulated boom vehicle driving route. The route node sequence may include: a starting point, an end point, and each route node. Each route node in the route node sequence is arranged in the driving order.

[0032] Step 2: divide each route node in the above route node sequence to obtain a route node subsequence set.

[0033] Step 3: For each route node subsequence in the above route node subsequence set, perform the following processing steps:

[0034] 1. Based on the above distance matrix and the above route matrix, determine the first node distance and the first node route corresponding to the above route node subsequence. The first node distance can represent the node distance between each route node in the driving node subsequence. The first node route can represent the node connection path between each route node in the route node subsequence. Each driving node in the route node subsequence is adjacent. The above execution entity can filter out the node distance corresponding to the route node subsequence from the distance matrix as the first node distance, and filter out the node route corresponding to the route node subsequence from the route matrix as the first node route.

[0035] 2. Determine the second node route corresponding to the route node subsequence in the initial articulated boom driving route, and determine the second node distance corresponding to the second node route. The second node distance can represent the node distance between each route node in the initial articulated boom driving route. The second node route can represent the node connection route between each route node in the initial articulated boom driving route. The execution subject can select the node distance corresponding to the route node subsequence from the distance matrix as the second node distance, and select the node route corresponding to the route node subsequence from the route matrix as the second node route.

[0036] 3. In response to determining that the first node distance is less than or equal to the second node distance, determining the first node route as a candidate node route.

[0037] 4. In response to determining that the first node distance is greater than the second node distance, determining the second node route as a candidate node route.

[0038] Step 4: determine the determined candidate node route sequence as the optimized boom truck driving route.

[0039] Step 104: Control the articulated boom truck to travel to the target area according to the optimized driving route of the articulated boom truck.

[0040] In some embodiments, the execution entity may control the articulated boom truck to travel to the target area according to the optimized travel route of the articulated boom truck.

[0041] In an actual application scenario, the execution subject can control the articulated boom truck to travel to the target area through the following steps:

[0042] The first step is to determine at least one dynamic obstacle information currently corresponding to the above-mentioned articulated boom truck. The dynamic obstacle information may be obstacle information of a movable dynamic obstacle. For example, a dynamic obstacle may be a moving vehicle / animal / pedestrian. The at least one dynamic obstacle corresponding to the at least one dynamic obstacle information may be each dynamic obstacle traveling on the same road as the articulated boom truck. The at least one dynamic obstacle information may be at least one obstacle traveling on the same road as the articulated boom truck, the corresponding vehicle distance of which is less than a predetermined distance. The obstacle information may characterize the identification information of the obstacle. For example, the obstacle information may indicate whether the obstacle is a vehicle, a pedestrian, or an animal. For example, the dynamic obstacle may be identified by the current on-board radar of the articulated boom truck.

[0043] In the second step, for each dynamic obstacle information in the at least one dynamic obstacle information, the movement position of the obstacle corresponding to the dynamic obstacle information at each future time node is determined as the obstacle movement position, and an obstacle movement position sequence is obtained. Among them, each future time node can be pre-set for the current time node. The movement position can be the driving position of the dynamic obstacle on the road. One obstacle movement position corresponds to one future time node.

[0044] In the third step, in response to determining that at least one predicted motion route conflicts with the optimized driving route of the articulated boom truck, the drivable area information corresponding to the articulated boom truck and at least one route node change position sequence are determined based on the obtained at least one obstacle motion position sequence. The at least one predicted motion route corresponds to the at least one obstacle motion position sequence. The drivable area information may be the area information of the road area where the articulated boom truck can travel. The route node change position may be the position after the articulated boom truck movement position is adjusted at a future time node. The route node change position is the position where the corresponding articulated boom truck movement original position is changed.

[0045] The third step may include the following sub-steps:

[0046] In the first sub-step, for each future time node in the future time node sequence, the following processing steps are performed:

[0047] 1. Determine at least one obstacle motion position in the at least one obstacle motion position sequence corresponding to the future time node as at least one candidate obstacle motion position. One obstacle motion position corresponds to one candidate obstacle motion position. The obstacle motion position may be the position to which the obstacle moves at the future time node.

[0048] 2. Determine the motion information corresponding to each of the at least one candidate obstacle motion position, and obtain at least one motion information. The motion information may be the position size of the lateral / longitudinal motion of the dynamic obstacle when it is in the candidate obstacle motion position. The lateral motion may be left-right motion on the road. The longitudinal motion may be forward-backward motion on the road. That is, according to the lateral / longitudinal motion of the dynamic obstacle, the corresponding motion information is determined by setting the corresponding motion safety distance.

[0049] The second sub-step is to generate motion region information corresponding to at least one dynamic obstacle according to the obtained at least one motion information sequence. For each motion information sequence in the at least one motion information sequence, the execution subject may connect the motion information in the motion information sequence to generate the motion region information corresponding to the dynamic obstacle.

[0050] The third sub-step is to generate the drivable area information according to the above movement area information. First, the above execution subject can determine the road area information. Then, the movement area information is removed from the road space information to obtain the drivable area information.

[0051] In the fourth step, based on the drivable area information, the at least one obstacle motion position sequence and the at least one route node change position sequence, the driving route score information corresponding to each drivable route in the at least one drivable route is generated. The at least one drivable route corresponds to the at least one route node change position sequence. For example, the number of route node change positions included in the route node change position sequence corresponding to the drivable route can be determined as the driving route score information.

[0052] Step 5: obtaining a drivable route whose corresponding driving route score information satisfies a preset condition from the at least one drivable route as the latest driving route corresponding to the articulated boom truck, and controlling the articulated boom truck to travel according to the latest driving route. The preset condition may be: the driving route score indicated by the driving route score information is the smallest.

[0053] Therefore, by determining the movement position of each dynamic obstacle at each future time node, not only can the movement of each dynamic obstacle be dynamically grasped, but also the subsequent driving route can be generated to avoid the movement corresponding to the dynamic obstacle, which not only reduces the cost of the boom truck in complex construction scenes, but also improves safety. It can effectively avoid the occurrence of boom truck collisions.

[0054] Step 105 , in response to determining that the articulated boom truck has traveled to the target area, controlling a camera disposed on the articulated boom truck to capture an area image of the target area.

[0055] In some embodiments, the execution subject may control a camera disposed on the articulated boom vehicle to capture an area image of the target area in response to determining that the articulated boom vehicle has traveled to the target area. The camera device may be a 3D point cloud camera. The area image may represent the entire target area. The area image may be a point cloud image.

[0056] Step 106: perform region segmentation processing on the above region image to obtain a set of region sub-images.

[0057] In some embodiments, the execution subject may perform a regional segmentation process on the regional image to obtain a set of regional sub-images. First, the length and width of the articulated boom truck may be determined; then, the length of the articulated boom truck may be used as a longitudinal segmentation length unit and the width may be used as a transverse segmentation width unit; and then the longitudinal segmentation length unit and the transverse segmentation width unit may be scaled to a length and width corresponding to the regional image according to the image scaling ratio. Then, the regional image may be segmented according to the scaled length and width to obtain a set of regional sub-images.

[0058] Step 107: input the above regional sub-image set into a pre-trained ground regional flat plane recognition model to obtain a regional sub-image flat plane recognition result set.

[0059] In some embodiments, the execution subject may input the above-mentioned regional sub-image set into a pre-trained ground regional flat plane recognition model to obtain a regional sub-image flat plane recognition result set. Among them, one regional sub-image corresponds to one regional sub-image flat plane recognition result. The ground regional flat plane recognition model may be a pre-trained regional flat plane recognition model that takes the regional sub-image as input and the regional sub-image as output, and may include: laser point cloud technology and ground segmentation learning model. Laser point cloud technology: This method involves multiple steps, including field survey, data collection of phased points, point cloud data collection of the site, data preprocessing, establishment of a digital elevation model (DEM) of a three-dimensional point cloud, data verification, generation of a three-dimensional real scene model of the site, and finally leveling recognition according to the site leveling requirements. Ground segmentation learning model: This model obtains sample point cloud data and the corresponding standard ground surface, fits the initial sample ground plane based on the sample point cloud data, obtains the sample distance distribution of the sample point cloud data relative to the initial sample ground plane, and iterates the pre-selected network learning model according to the sample distance distribution and the standard ground surface to obtain a ground segmentation learning model for identifying the ground plane. The flat plane recognition result of the regional sub-image may represent the flatness of the area displayed by the recognized regional sub-image.

[0060] Step 108, in response to determining that there is a regional sub-image flat plane recognition result that meets the target condition in the above-mentioned regional sub-image flat plane recognition result set, the regional sub-image corresponding to each regional sub-image flat plane recognition result that meets the target condition is determined as a candidate regional sub-image, and a candidate regional sub-image group is obtained.

[0061] In some embodiments, the execution subject may determine the regional sub-image corresponding to each regional sub-image flat plane recognition result that meets the target condition as a candidate regional sub-image in response to determining that there is a regional sub-image flat plane recognition result that meets the target condition in the regional sub-image flat plane recognition result set, and obtain a candidate regional sub-image group. The target condition may refer to: the flatness represented by the regional sub-image flat plane recognition result is greater than or equal to a preset flatness.

[0062] Step 109: Select a target area sub-image from the candidate area sub-image group, and control the articulated boom truck to travel to the area corresponding to the target area sub-image.

[0063] In some embodiments, the execution subject may select a target area sub-image from the candidate area sub-image group, and control the articulated boom truck to travel to an area corresponding to the target area sub-image.

[0064] In an actual application scenario, the execution subject may select the target region sub-image from the candidate region sub-image group through the following steps:

[0065] The first step is to determine the center position of the image area corresponding to each candidate region sub-image in the candidate region sub-image group.

[0066] The second step is to determine the interval distance between the center position of each image area and the above target position to obtain an interval distance group.

[0067] In the third step, the candidate region sub-image corresponding to the shortest interval distance is determined as the target candidate region sub-image.

[0068] Step 110, controlling the lift of the above-mentioned articulated boom truck to rise to the target position, and controlling the pressure sensors between the arms of the lift to detect the pressure data of each arm in real time, and controlling the vehicle level of the above-mentioned articulated boom truck to detect the current horizontal state information.

[0069] In some embodiments, the execution subject may control the lift of the articulated boom truck to rise to the target position, and control the pressure sensors between the arms of the lift to detect the pressure data of each arm in real time, and control the vehicle level of the articulated boom truck to detect the current horizontal state information. The pressure sensor may refer to a pressure sensor arranged between the arms of the lift, which is used to detect the pressure data of each arm when the lift is in operation. The vehicle level may refer to a vehicle balance level, which is used to detect whether the articulated boom truck is tilted. The horizontal state information may refer to the current horizontal information (tilt angle) of the articulated boom truck. The target position may refer to the location of the working area.

[0070] Step 111, in response to determining that there is abnormal pressure data in the collected pressure data, and / or the horizontal state information meets the abnormal horizontal condition, controlling the associated alarm device to issue an alarm prompt, and controlling the lift of the above-mentioned boom truck to return to the initial position.

[0071] In some embodiments, the above-mentioned execution subject may control the associated alarm device to issue an alarm prompt and control the lift of the above-mentioned articulated boom truck to fall back to the initial position in response to determining that there is abnormal pressure data in the collected pressure data, and / or the horizontal state information satisfies the abnormal horizontal condition. Abnormal pressure data indicates that the pressure data exceeds the pressure threshold. The abnormal horizontal condition may be that the inclination angle represented by the horizontal state information is greater than or equal to a preset angle. The alarm device may refer to a loudspeaker provided on the articulated boom truck. The alarm prompt may refer to a danger warning voice. The initial position may refer to the position on the articulated boom truck when the lift is not raised.

[0072] Further, in response to determining that the horizontal state information satisfies the abnormal horizontal condition, a new target region sub-image is selected from each of the unselected candidate region sub-images.

[0073] In some embodiments, the execution subject may select a new target region sub-image from unselected candidate region sub-images in response to determining that the horizontal state information satisfies an abnormal horizontal condition.

[0074] Furthermore, the associated tamping compactor is controlled to compact the area corresponding to the new target area sub-image, and the articulated boom truck is controlled to travel to the area.

[0075] In some embodiments, the execution subject may control the associated compactor to compact the area corresponding to the new target area sub-image, and control the articulated boom truck to travel to the area. The compactor may be a simple compactor provided on the articulated boom, used to compact the ground in the area to prevent the articulated boom truck from tilting during operation.

[0076] The present application also provides a computer device 200. Figure 2 As shown, the computer device 200 includes: a bus 201, a processor 202, a memory 203 and a communication interface 204. The processor 202, the memory 203 and the communication interface 204 communicate with each other through the bus 201. The computer device 200 can be a server or a terminal device. It should be understood that the present application does not limit the number of processors and memories in the computer device 200.

[0077] The bus 201 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 The bus 201 is represented by only one line, but it does not mean that there is only one bus or one type of bus. The bus 201 may include a path for transmitting information between various components of the computer device 200 (for example, the memory 203, the processor 202, and the communication interface 204).

[0078] The processor 202 may include any one or more of a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0079] The memory 203 may include a volatile memory, such as a random access memory (RAM). The memory 203 may also include a non-volatile memory, such as a read-only memory (ROM), a flash memory, a hard disk drive (HDD), or a solid state drive (SSD).

[0080] The memory 203 stores executable program codes, and the processor 202 executes the executable program codes to respectively implement the functions of the acquisition module, the sampling module, the determination module, and the mixing module, thereby implementing the above-mentioned method for safety control of an elevator based on an articulated boom truck. That is, the memory 203 stores instructions for executing the above-mentioned method for safety control of an elevator based on an articulated boom truck.

[0081] The communication interface 204 uses a transceiver module such as, but not limited to, a network interface card or a transceiver to implement communication between the computer device 200 and other devices or a communication network.

[0082] An embodiment of the present application also provides a chip, which includes a processor and a data interface. The processor reads instructions stored in a memory through the data interface to execute the above-mentioned method for safety control of an elevator based on a boom truck.

[0083] The embodiment of the present application also provides a computer-readable storage medium. The above-mentioned computer-readable storage medium can be any available medium that can be stored by a computing device or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid-state hard disk). The computer-readable storage medium includes instructions that instruct the computing device to execute the above-mentioned method for safety control of a lift based on a boom truck.

[0084] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0085] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the protection scope of the technical solutions of the embodiments of the present application.

Claims

1. A safety control method for an elevator based on a boom truck, the method comprising: In response to the articulated boom vehicle receiving a task instruction corresponding to a target area, determining a starting position corresponding to the articulated boom vehicle and an end position of the target area; Generating an initial articulated boom truck driving route according to the starting point and the end point; Optimizing the initial articulated boom truck driving route to obtain an optimized articulated boom truck driving route; According to the optimized driving route of the articulated boom truck, controlling the articulated boom truck to drive to the target area; In response to determining that the articulated boom truck has traveled to the target area, controlling a camera device disposed on the articulated boom truck to capture an area image of the target area; Performing region segmentation processing on the region image to obtain a set of region sub-images; Inputting the regional sub-image set into a pre-trained ground regional flat plane recognition model to obtain a regional sub-image flat plane recognition result set, wherein one regional sub-image corresponds to one regional sub-image flat plane recognition result; In response to determining that there is a regional sub-image flattened plane recognition result that meets the target condition in the regional sub-image flattened plane recognition result set, determining the regional sub-image corresponding to each regional sub-image flattened plane recognition result that meets the target condition as a candidate regional sub-image, to obtain a candidate regional sub-image group; Selecting a target area sub-image from the candidate area sub-image group, and controlling the articulated boom vehicle to travel to an area corresponding to the target area sub-image; Control the lift of the articulated boom truck to rise to a target position, control the pressure sensors between the arms of the lift to detect the pressure data of each arm in real time, and control the vehicle level meter of the articulated boom truck to detect the current horizontal state information; In response to determining that there is abnormal pressure data in the collected pressure data, and / or the horizontal state information meets the abnormal horizontal condition, the associated alarm device is controlled to issue an alarm prompt, and the elevator of the articulated boom truck is controlled to fall back to the initial position.

2. The safety control method for an elevator based on a boom truck according to claim 1, characterized in that: The step of optimizing the initial articulated boom driving route to obtain an optimized articulated boom driving route includes: Determine the distance matrix and the route matrix corresponding to the starting point and the end point by using the interpolation method; According to the distance matrix and the route matrix, node route optimization is performed on the node routes between the route nodes in the initial articulated boom driving route to obtain an optimized articulated boom driving route.

3. The safety control method for an elevator based on a boom truck according to claim 1, characterized in that: The step of selecting a target region sub-image from the candidate region sub-image group includes: Determine the center position of the image area corresponding to each candidate region sub-image in the candidate region sub-image group; Determine the interval distance between the center position of each image area and the target position to obtain an interval distance group; The candidate region sub-image corresponding to the shortest interval distance is determined as the target candidate region sub-image.

4. The safety control method for an elevator based on a boom truck according to claim 1, characterized in that: The method further comprises: In response to determining that the horizontal state information satisfies an abnormal horizontal condition, selecting a new target region sub-image from each of the unselected candidate region sub-images; The associated tamping compactor is controlled to compact the area corresponding to the new target area sub-image, and the articulated boom truck is controlled to travel to the area.

5. A computer device, wherein: The computer device comprises a processor, a memory, and a computer program stored in the memory and executable by the processor, wherein when the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 4 are implemented.

6. A computer-readable storage medium, wherein: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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