Distributing machine path planning method and device

Abstract

The invention relates to the technical field of construction engineering machinery, and discloses a distribution machine path planning method and device, and the method comprises the steps: obtaining the boundary information of a construction region and the obstacle position information; dividing the construction area into a plurality of sub-areas; sorting the sub-regions to obtain an optimal sub-region sorting scheme; respectively determining a path access sequence corresponding to each sub-region; when the obstacles exist in the sub-regions, adjusting the paths corresponding to the sub-regions to obtain final paths in the plurality of sub-regions; according to the optimal sub-region sorting scheme, the final paths in the multiple sub-regions are connected in sequence, and the construction path of the material distributing machine is determined; determining the movement rate of the material distributing machine according to the pouring amount of the path area; and determining a material distribution scheme of the material distributor. According to the method, the optimal sub-region sequence and the path sequence corresponding to the sub-regions are determined to determine the optimal final construction path of the material distributing machine, co-evolution of path planning is realized, and the path planning efficiency and the execution flexibility of the material distributing machine in a complex environment are greatly improved.

Description

Technical Field

[0001] The present application relates to the technical field of construction engineering machinery, and more specifically to a method and device for path planning of a concrete placing machine. Background Art

[0002] In highly complex operation scenarios such as building construction and automatic control of concrete placing booms, path planning, as a core element for efficient equipment operation, faces many severe challenges. Placing booms often need to perform laying operations in construction environments with staggered steel bars (as laying obstacles) and irregular spaces, so traditional path planning algorithms often have difficulty effectively dealing with these complex conditions. The distribution of obstacles is random and complex, and the placing boom must accurately avoid obstacles and collisions while ensuring full coverage of the entire construction area. Summary of the invention

[0003] The embodiments of the present application provide a method and device for path planning of a concrete placing crane, which determine the optimal sub-area sorting and the path sorting corresponding to the sub-areas to determine the optimal final construction path of the concrete placing crane, realize the collaborative evolution of path planning, and greatly improve the path planning efficiency and execution flexibility of the concrete placing crane in complex environments.

[0004] In a first aspect, an embodiment of the present application provides a method for planning a path for a concrete placing machine, which obtains boundary information and target obstacle position information of a target construction area according to a construction map of the area to be placed; divides the target construction area into multiple sub-areas according to the boundary information and the target obstacle position information; performs region sorting on the multiple sub-areas to obtain an optimal sub-area sorting scheme; and determines a path access sequence corresponding to each sub-area respectively; takes a sub-area as a target sub-area, and when there is a target obstacle in the target sub-area, adjusts the path access sequence corresponding to the target sub-area according to the target obstacle position information, and after adjusting the path access sequence corresponding to each target sub-area, updates the path access sequence corresponding to each sub-area to obtain a final path in a plurality of sub-areas; connects the final paths in the plurality of sub-areas in sequence according to the optimal sub-area sorting scheme to determine a construction path of the concrete placing machine; determines a movement rate of the concrete placing machine according to the construction path of the concrete placing machine and the amount of concrete poured within the coverage of the construction path; and determines a placing scheme of the concrete placing machine according to the construction path of the concrete placing machine and the movement rate of the concrete placing machine.

[0005] In one embodiment, the step of performing sub-region sorting on the multiple sub-regions to obtain an optimal sub-region sorting scheme includes: An objective function for region sorting is defined, wherein a minimum value of the objective function indicates a minimum number of path intersections; Initialize the number and iterations of sub-region sorting schemes; Generate multiple sub-region initial sorting schemes according to the number of the sub-region sorting schemes, and generate an initial random sub-region sorting for each sub-region initial sorting scheme; Initializing a priority matrix, wherein the priority matrix includes a path priority between any two sub-areas, wherein the path priority represents a priority for moving from one sub-area to another sub-area; Performing a heuristic search and updating on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain a plurality of updated sub-region sorting schemes; After obtaining the updated multiple sub-region sorting schemes, an optimal sub-region sorting scheme is determined.

[0006] In one embodiment, performing a heuristic search and updating on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain a plurality of updated sub-region sorting schemes includes: Calculating the probability of moving from one sub-region to another sub-region in each sub-region sorting scheme according to the priority matrix; Each sub-region sorting scheme is updated according to the probability and the number of iterations to obtain a plurality of updated sub-region sorting schemes.

[0007] In one embodiment, respectively determining the path access order corresponding to each sub-area includes: Taking a sub-region as a target sub-region according to the sorting order in the optimal sub-region sorting scheme; Determine a path access starting point of the target sub-area; Determining a path access endpoint of the target sub-area according to a relative position of a next sub-area of ​​the target sub-area; Determine the optimal step size of the target sub-region; Determine the path access sequence corresponding to the target sub-area according to the path access starting point, path access end point and optimal step length of the target sub-area; After the path access sequence corresponding to each target sub-region is determined, the path access sequence corresponding to each sub-region is determined.

[0008] In one embodiment, determining the path access starting point of the target sub-area includes: If the target sub-region is the first region in the optimal sub-region sorting scheme, determining the vertex at the upper left corner of the target sub-region as the path access starting point of the target sub-region; If the target sub-region is not the first region in the optimal sub-region sorting scheme, the point in the target sub-region that is closest to the end point of the path access of the previous sub-region of the target sub-region is determined as the starting point of the path access of the target sub-region, wherein the previous sub-region of the target sub-region is the sub-region of the previous order of the target sub-region in the optimal sub-region sorting scheme.

[0009] In one embodiment, determining the path access endpoint of the target sub-area according to the relative position of the next sub-area of ​​the target sub-area includes: Acquire the coordinates of the center point of the next sub-region of the target sub-region, wherein the next sub-region of the target sub-region is the sub-region of the next order of the target sub-region in the optimal sub-region sorting scheme; Acquire the coordinates of the optional end point, wherein the optional end point is three vertices in the target sub-area excluding the path access starting point; Calculating the distance between the coordinates of the optional end point and the coordinates of the center point of the next sub-region according to a preset function to obtain an end point estimation function; The endpoint estimation function is minimized to solve the coordinates of the optimal endpoint, and the optimal endpoint is determined as the path access endpoint of the target sub-area.

[0010] In one embodiment, determining the optimal step size of the target sub-region includes: Initialize a value range of the step length of the target sub-region, select a value for the step length within the range, and construct a value group for the step length; Randomly select an initial step size from the value group; A fitness function is constructed based on the coverage of the path constructed by the step length and the distance between the end point of the path visit of the target sub-region and the starting point of the next sub-region of the target sub-region; The value of the initial step length is iteratively optimized until the value of the fitness function corresponding to the step length reaches a preset condition, thereby determining the optimal step length of the target sub-region.

[0011] In one embodiment, the position information of the target obstacle includes a center coordinate and a radius, and when the target obstacle exists in the target sub-area, adjusting the path access order corresponding to the target sub-area according to the target obstacle position information includes: Obtaining the center coordinates and radius of the target obstacle; When a target path formed by the path access sequence corresponding to the marker area intersects with the target obstacle, a target detour path is generated, wherein the intersection point is the point on the target path that is closest to the target obstacle, and the distance between the intersection point and the center coordinate of the target obstacle is less than the radius; The path access sequence corresponding to the target sub-area is adjusted according to the target detour path.

[0012] In one embodiment, determining the movement speed of the concrete placing boom according to the construction path of the concrete placing boom and the amount of concrete poured within the coverage of the construction path includes: Calculating the initial movement rate of the concrete placing boom, wherein the initial movement rate of the concrete placing boom is a value obtained by dividing the amount of concrete poured within the coverage of the construction path by the total length of the construction path; Adjusting the movement speed of the concrete placing boom at the turning point according to the curvature of the construction path at the turning point; If the construction path passes through the target obstacle, the movement speed of the concrete placing machine when encountering the target obstacle is adjusted according to a preset speed adjustment formula; The movement speed of the material placing machine is determined according to the initial movement speed, the movement speed of the material placing machine at the corner, and the movement speed of the material placing machine when encountering the target obstacle.

[0013] In a second aspect, an embodiment of the present application provides a cloth spreading machine path planning device, which has the function of implementing the cloth spreading machine path planning method provided in the first aspect above. The function can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, and the modules can be software and / or hardware. In one embodiment, the cloth spreading machine path planning device includes: Acquisition module: used to obtain the boundary information of the target construction area and the location information of the target obstacle according to the construction map of the area to be laid; A division module: used for dividing the target construction area into a plurality of sub-areas according to the boundary information and the target obstacle position information; A region sorting module: used for sorting the multiple sub-regions to obtain an optimal sub-region sorting scheme; Path sorting module: used to determine the path access order corresponding to each sub-area; Path adjustment module: used to take a sub-region as a target sub-region, and when there is a target obstacle in the target sub-region, adjust the path access sequence corresponding to the target sub-region according to the position information of the target obstacle, and after adjusting the path access sequence corresponding to each target sub-region, update the path access sequence corresponding to each sub-region to obtain the final path in multiple sub-regions; Connection module: used to connect the final paths in multiple sub-areas in order according to the optimal sub-area sorting scheme to determine the construction path of the concrete placing machine; A rate determination module: determining the movement rate of the concrete placing boom according to the construction path of the concrete placing boom and the amount of concrete poured within the coverage of the construction path; A plan generation module generates a material distribution plan for the material distribution machine according to the construction path of the material distribution machine and the movement speed of the material distribution machine.

[0014] In one embodiment, the region sorting module is specifically used to: An objective function for sorting the sub-regions is defined, wherein a minimum value of the objective function indicates a minimum number of path intersections; Initialize the number and iterations of sub-region sorting schemes; Generate multiple sub-region initial sorting schemes according to the number of the sub-region sorting schemes, and generate an initial random sub-region sorting for each sub-region initial sorting scheme; Initializing a priority matrix, wherein the priority matrix includes a path priority between any two sub-areas, wherein the path priority represents a priority for moving from one sub-area to another sub-area; Performing a heuristic search and updating on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain a plurality of updated sub-region sorting schemes; After obtaining the updated multiple sub-region sorting schemes, an optimal sub-region sorting scheme is determined.

[0015] In one embodiment, the region sorting module is further used to: Calculating the probability of moving from one sub-region to another sub-region in each sub-region sorting scheme according to the priority matrix; Each sub-region sorting scheme is updated according to the probability and the number of iterations to obtain a plurality of updated sub-region sorting schemes.

[0016] In one embodiment, the path sorting module is specifically used to: Taking a sub-region as a target sub-region according to the sorting order in the optimal sub-region sorting scheme; Determine a path access starting point of the target sub-area; Determining a path access endpoint of the target sub-area according to a relative position of a next sub-area of ​​the target sub-area; Determine the optimal step size of the target sub-region; Determine the path access sequence corresponding to the target sub-area according to the path access starting point, path access end point and optimal step length of the target sub-area; After the path access sequence corresponding to each target sub-region is determined, the path access sequence corresponding to each sub-region is determined.

[0017] In one embodiment, the path sorting module is further configured to: If the target sub-region is the first region in the optimal sub-region sorting scheme, determining the vertex at the upper left corner of the target sub-region as the path access starting point of the target sub-region; If the target sub-region is not the first region in the optimal sub-region sorting scheme, the point in the target sub-region that is closest to the end point of the path access of the previous sub-region of the target sub-region is determined as the starting point of the path access of the target sub-region, wherein the previous sub-region of the target sub-region is the sub-region of the previous order of the target sub-region in the optimal sub-region sorting scheme.

[0018] In one embodiment, the path sorting module is further configured to: Acquire the coordinates of the center point of the next sub-region of the target sub-region, wherein the next sub-region of the target sub-region is the sub-region of the next order of the target sub-region in the optimal sub-region sorting scheme; Acquire the coordinates of the optional end point, wherein the optional end point is three vertices in the target sub-area excluding the path access starting point; Calculating the distance between the coordinates of the optional end point and the coordinates of the center point of the next sub-region according to a preset function to obtain an end point estimation function; The endpoint estimation function is minimized to solve the coordinates of the optimal endpoint, and the optimal endpoint is determined as the path access endpoint of the target sub-area.

[0019] In one embodiment, the path sorting module is further configured to: Initialize a value range of the step length of the target sub-region, select a value for the step length within the range, and construct a value group for the step length; Randomly select an initial step size from the value group; A fitness function is constructed based on the coverage of the path constructed by the step length and the distance between the end point of the path visit of the target sub-region and the starting point of the next sub-region of the target sub-region; The value of the initial step length is iteratively optimized until the value of the fitness function corresponding to the step length reaches a preset condition, thereby determining the optimal step length of the target sub-region.

[0020] In one embodiment, the path adjustment module is specifically used to: Obtaining the center coordinates and radius of the target obstacle; When a target path formed by the path access sequence corresponding to the marker area intersects with the target obstacle, a target detour path is generated, wherein the intersection point is the point on the target path that is closest to the target obstacle, and the distance between the intersection point and the center coordinate of the target obstacle is less than the radius; The path access sequence corresponding to the target sub-area is adjusted according to the target detour path.

[0021] In one embodiment, the rate determination module is specifically configured to: Calculating the initial movement rate of the concrete placing boom, wherein the initial movement rate of the concrete placing boom is a value obtained by dividing the amount of concrete poured within the coverage of the construction path by the total length of the construction path; Adjusting the movement speed of the concrete placing boom at the turning point according to the curvature of the construction path at the turning point; If the construction path passes through the target obstacle, the movement speed of the concrete placing machine when encountering the target obstacle is adjusted according to a preset speed adjustment formula; The movement speed of the material placing machine is determined according to the initial movement speed, the movement speed of the material placing machine at the corner, and the movement speed of the material placing machine when encountering the target obstacle.

[0022] This application iteratively optimizes and determines the optimal sub-area sorting and the path sorting corresponding to the sub-areas to determine the optimal final construction path of the placing crane, realizes the collaborative evolution of path planning, and greatly improves the path planning efficiency and execution flexibility of the placing crane in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0024] Figure 1 This is a schematic diagram of a scenario of a path planning device for a material placing machine provided in an embodiment of the present application; Figure 2 It is a schematic diagram of an embodiment of a method for path planning of a material placing machine provided in an embodiment of the present application; Figure 3 A schematic diagram of an example scenario of dividing initial sub-areas in an embodiment of the present application; Figure 4 In the embodiment of this application, Figure 3 A schematic diagram of an embodiment of dividing the initial sub-areas and then merging and dividing them again; Figure 5This is a schematic diagram of an embodiment scenario after sub-region sorting is completed using a preset algorithm in an embodiment of the present application; Figure 6 A schematic diagram of an embodiment scenario of different path access sequence schemes that may exist in a target sub-area in an embodiment of the present application; Figure 7 A schematic diagram of an example scenario for obtaining a construction path for an embodiment of the present application; Figure 8 A schematic diagram of an example scenario of generating a detour path in an embodiment of the present application; Fig. 9 Schematic diagram of the structure of the path planning method device for a material placing machine according to an embodiment of the present application.

[0025] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0026] 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 only 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 those skilled in the art without creative work are within the scope of protection of this application.

[0027] In the following description, the specific embodiments of the present application will be described with reference to the steps and symbols performed by one or more computers, unless otherwise specified. Therefore, these steps and operations will be mentioned several times as being performed by a computer, and the computer execution referred to herein includes the operation of a computer processing unit by an electronic signal representing data in a structured form. This operation converts the data or maintains it at a location in the memory system of the computer, which can be reconfigured or otherwise change the operation of the computer in a manner familiar to testers in the field. The data structure maintained by the data is a physical location in the memory, which has specific characteristics defined by the data format. However, the principles of the present application are described in the above text, which does not represent a limitation, and testers in the field will understand that the various steps and operations described below can also be implemented in hardware.

[0028] The terms "module" or "unit" used herein may be considered as software objects executed on the computing system. The different components, modules, engines and services described herein may be considered as implementation objects on the computing system. The devices and methods described herein are preferably implemented in software, but may also be implemented in hardware, all within the scope of protection of this application.

[0029] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0030] Embodiments of the present application provide a method, device, and storage medium for path planning of a material placing machine.

[0031] See also Figure 1 , Figure 1 The schematic diagram of the scene of the placing machine path planning device provided in the embodiment of the present application is a placing machine path planning device, which may include a placing machine path planning system 100 and a user terminal 200. The placing machine path planning system 100 is connected via a network, and the placing machine path planning device is integrated in the placing machine path planning system 100. In the embodiment of the present application, the placing machine path planning system 100 may be a terminal device or a server, and the placing machine path planning system 100 may send the construction path of the placing machine to the user terminal 200.

[0032] In the embodiment of the present application, when the path planning system 100 of the fabric spreading machine is a server, the server can be an independent server, or a server network or server cluster composed of servers. For example, the server described in the embodiment of the present application includes but is not limited to a computer, a network host, a single network server, a plurality of network server sets or a cloud server composed of a plurality of servers. Among them, the cloud server is composed of a large number of computers or network servers based on cloud computing. In the embodiment of the present application, communication between the server and the client can be achieved through any communication method, including but not limited to mobile communication based on the 3rd Generation Partnership Project (3GPP), Long Term Evolution (LTE), Worldwide Interoperability for Microwave Access (WiMAX), or computer network communication based on TCP / IP Protocol suite (TCP / IP), User Datagram Protocol (UDP) protocol, etc.

[0033] It is understandable that when the fabric spreading machine path planning system 100 used in the embodiment of the present application is a terminal device, the terminal device can be a device including both receiving hardware and transmitting hardware, that is, a device having receiving and transmitting hardware capable of performing two-way communication on a two-way communication link. Such terminal devices may include: cellular or other communication devices having a single-line display or a multi-line display or a cellular or other communication device without a multi-line display. The specific fabric spreading machine path planning system 100 can be a desktop terminal or a mobile terminal, and the fabric spreading machine path planning system 100 can be one of a mobile phone, a tablet computer, a laptop computer, etc.

[0034] The terminal device involved in the embodiments of the present application may also refer to a device that provides voice and / or data connectivity to a user, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem. For example, a mobile phone (or "cellular" phone) and a computer with a mobile terminal, for example, a portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile device, which exchanges voice and / or data with a wireless access network. For example, personal communication service (English full name: Personal Communication service, English abbreviation: PCs) phone, cordless phone, session initiation protocol (sIP) phone, wireless local loop (Wireless Local Loop, English abbreviation: WLL) station, personal digital assistant (English full name: Personal Digital Assistant, English abbreviation: PDA) and other devices.

[0035] Those skilled in the art will understand that Figure 1 The application environment shown in the figure is only one application scenario of the present application solution and does not constitute a limitation on the application scenario of the present application solution. Other application environments may also include Figure 1 More or fewer computing devices, or computing device network connection relationships, such as Figure 1 Only one computing device is shown in the figure. It can be understood that the cloth spreading machine path planning device can also include one or more other computing devices, or / and one or more other computing devices connected to the cloth spreading machine path planning system 100 network, which is not specifically limited here.

[0036] In addition, if Figure 1 As shown, the material placing machine path planning device may also include a memory 300 for storing data, such as obstacle location information, path access sequence, etc.

[0037] It should be noted that Figure 1 The scenario diagram of the cloth fabric path planning device shown is merely an example. The cloth fabric path planning device and scenario described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application. A person of ordinary skill in the art can appreciate that with the evolution of the cloth fabric path planning device and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.

[0038] This application iteratively optimizes and determines the optimal sub-area sorting and path sorting corresponding to the sub-area to determine the optimal final construction path of the concrete placing machine, realizes the co-evolution of path planning, and greatly improves the path planning efficiency and execution flexibility of the concrete placing machine in complex environments. The following is a detailed description in conjunction with specific embodiments.

[0039] In this embodiment, the path planning method for a material placing machine will be described from the perspective of the path planning method for a material placing machine, and the path planning method for a material placing machine can be specifically integrated into the path planning system 100 for a material placing machine.

[0040] The present application provides a method for planning a concrete placing machine path, which includes: acquiring boundary information and target obstacle position information of a target construction area according to a construction map of an area to be placed; dividing the target construction area into multiple sub-areas according to the boundary information and the target obstacle position information; performing sub-area sorting on the multiple sub-areas to obtain an optimal sub-area sorting scheme; respectively determining a path access sequence corresponding to each sub-area; taking a sub-area as a target sub-area, when there is a target obstacle in the target sub-area, adjusting the path access sequence corresponding to the target sub-area according to the target obstacle position information, and after adjusting the path access sequence corresponding to each target sub-area, updating the path access sequence corresponding to each sub-area to obtain final paths in multiple sub-areas; connecting the final paths in multiple sub-areas in sequence according to the optimal sub-area sorting scheme to determine a construction path of the concrete placing machine; determining a movement rate of the concrete placing machine according to the construction path of the concrete placing machine and a concrete pouring amount within a coverage range of the construction path; and generating a concrete placing scheme of the concrete placing machine according to the construction path of the concrete placing machine and the movement rate of the concrete placing machine.

[0041] See also Figure 2 , Figure 2 This is a flow chart of an embodiment of a method for path planning of a material placing machine in an embodiment of the present application. The method for path planning of a material placing machine includes the following steps 201 to 208: 201. Obtain boundary information of a target construction area and location information of target obstacles according to a construction map of the area to be laid.

[0042] Specifically, before obtaining the boundary information of the target construction area and the target obstacle position information according to the construction map of the area to be laid, the construction map of the area to be laid is obtained, wherein the area to be laid is the construction area of ​​the fabric placing machine, and the construction area waiting for laying. The boundary information of the construction area can be determined according to the construction map of the area to be laid. Specifically, the construction area can be a regular plane area, such as a rectangle, or an irregular figure. After obtaining the boundary information of the construction area, a corresponding plane figure can be drawn according to the area and boundary of the construction area, so as to divide the construction area into sub-areas later. Optionally, if there is an obstacle in the construction area, the position information of the obstacle is obtained according to the construction map. Specifically, the position information of the obstacle may include the center coordinates of the obstacle on the plane map and the radius of the target obstacle. Optionally, when the target obstacle is an irregular figure, the radius of the target obstacle is the maximum radius of the target obstacle, that is, the distance between the point on the boundary of the target obstacle that is farthest from the center coordinate and the center coordinate.

[0043] 202. Divide the target construction area into multiple sub-areas according to the boundary information and the target obstacle position information.

[0044] Specifically, Figure 3 As shown, Figure 3 The following is a schematic diagram of an embodiment scenario for dividing the initial sub-areas in the embodiment of the present application. A plan view of the corresponding target construction area can be drawn based on the boundary information and the position information of the target obstacle. After the position of the obstacle is marked in proportion in the plan view, the target construction area can be divided into multiple sub-areas, wherein it is ensured that there is no intersection between the boundary of each sub-area and the obstacle, that is, it is ensured that each target obstacle is within the area boundary of each sub-area. Optionally, the basis for dividing the target sub-area into multiple sub-areas may be to facilitate the material distribution by the material distribution machine, to avoid duplicate paths in the subsequent path planning process, and so on. Optionally, the division of the target sub-area into multiple sub-areas may be accomplished by a preset algorithm, such as a clustering algorithm. Optionally, after obtaining the initial sub-area division result, the initial sub-areas after division may also be merged and divided. As Figure 4 As shown, Figure 4 In the embodiment of this application, Figure 3Schematic diagram of an implementation scenario of dividing the initial sub-areas and then merging and re-dividing them. After the target construction area is initially divided into multiple sub-areas, an optimization objective function can be initialized to iteratively optimize the partitions, merge the sub-areas or re-divide the sub-areas. Optionally, the basis for merging or re-dividing the initially divided sub-areas can be that the sub-areas are adjacent and connected. Optionally, the initially divided sub-areas can be re-divided and merged multiple times to obtain multiple merged schemes, and the optimization objective function is used to evaluate the pros and cons of the re-divided sub-areas until the best area division scheme is selected, and the final division plan is obtained to obtain multiple sub-areas.

[0045] 203. Sorting the multiple sub-regions to obtain an optimal sub-region sorting solution.

[0046] Specifically, after completing the area division, multiple sub-areas are obtained , , … , these sub-areas need to be sorted to ensure that all sub-areas can be connected in series in order to form a path with as few intersections as possible. In order to optimize the area sorting, the Ant Colony Optimization (ACO) can be used for optimization. The ACO performs global search and optimization by simulating the pheromone paths left by ants when searching for food, and is particularly suitable for handling path sorting problems. Figure 5 As shown, Figure 5 The present invention is a schematic diagram of an embodiment scenario after the sub-region sorting is completed using a preset algorithm in an embodiment of the present application. Optionally, the process of sorting the sub-regions using a preset algorithm includes: defining an objective function for the sub-region sorting, wherein the minimum value of the objective function indicates the minimum number of path intersections; initializing the number of sub-region sorting schemes and the number of iterations; generating multiple sub-region initial sorting schemes according to the number of sub-region sorting schemes, and generating an initial random sub-region sorting for each sub-region initial sorting scheme; initializing a priority matrix, the priority matrix includes the path priority between any two sub-regions, and the path priority indicates the priority of moving from one sub-region to another; performing a heuristic search update on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain multiple updated sub-region sorting schemes; after obtaining multiple updated sub-region sorting schemes, determining the optimal sub-region sorting scheme.

[0047] 204. Determine the path access sequence corresponding to each sub-area respectively.

[0048] Specifically, after obtaining the order between each sub-region, the connection order between each sub-region can be determined. However, since there are still distribution paths between each sub-region, after determining the optimal ordering scheme between sub-regions, it is also necessary to determine the path planning within each sub-region according to the order of the optimal ordering scheme of the sub-regions. Figure 6 As shown, Figure 6 This is a schematic diagram of an embodiment scenario of different path access sequence schemes that may exist in a target sub-region in an embodiment of the present application. That is, the optimal path access sequence corresponding to each sub-region is determined, so as to determine the optimal path inside each sub-region. After determining the path access sequence corresponding to each sub-region, the material path inside each sub-region can be confirmed by connecting in sequence according to the path scheme sequence. Optionally, the specific process of determining the path access sequence corresponding to each sub-region may include: taking a sub-region as the target sub-region according to the sorting order in the optimal sub-region sorting scheme; determining the path access starting point of the target sub-region; determining the path access end point of the target sub-region according to the relative position of the next sub-region of the target sub-region; determining the optimal step length of the target sub-region; determining the path access sequence corresponding to the target sub-region according to the path access starting point, path access end point and optimal step length of the target sub-region; after completing the determination of the path access sequence corresponding to each target sub-region, determine the path access sequence corresponding to each sub-region. Optionally, since the paths within each sub-area need to be connected according to the sub-area optimal sorting scheme to ensure that the entire path planning can obtain a complete and connected path, in the sub-area optimal sorting scheme, the paths within two adjacent sub-areas are connected. Therefore, after obtaining the sub-area optimal sorting scheme, the path access order within each sub-area is determined according to the sorting order.

[0049] 205. A sub-region is a target sub-region. When there is a target obstacle in the target sub-region, the path access order corresponding to the target sub-region is adjusted according to the position information of the target obstacle. After adjusting the path access order corresponding to each target sub-region, the path access order corresponding to each sub-region is updated to obtain the final path in multiple sub-regions.

[0050] Specifically, after determining the optimal path in each sub-area, further adjustments need to be made to the optimal path. For example, when there is a target obstacle in the sub-area, ensure that the target obstacle in the sub-area can be avoided. This process involves refining and correcting the part of the path that passes through the obstacle to ensure that the path can bypass the obstacle while maintaining the overall smoothness and effectiveness of the path. Assume that there is a set of obstacles in the sub-area , where each obstacle Through its center coordinates and radius To express it as During the path adjustment process, it is necessary to ensure that all grid points in the path The following conditions are met to ensure that the points do not lie within the range of any obstacles:

[0051] in, is a grid point With obstacles Euclidean distance from the center. All points in the path should maintain a distance from the obstacle greater than its radius , thus avoiding the path passing through obstacles.

[0052] 206. The final paths in the multiple sub-areas are connected in sequence according to the optimal sub-area sorting scheme to determine the construction path of the concrete placing machine.

[0053] Specifically, after determining the optimal sub-region sorting scheme and the final path corresponding to each sub-region, the final path of each sub-region is connected according to the sub-region sorting scheme to obtain the construction path of the concrete placing machine. Figure 7 As shown, Figure 7 A schematic diagram of an example scenario of a construction path obtained for an embodiment of the present application. Specifically, for example, after determining the optimal sorting order of the sub-areas After that, the paths of all sub-areas should be effectively connected to form a complete construction path. Each sub-area Its internal path, i.e. the final path, has been planned Now we need to connect the paths of these sub-areas in series to ensure that the concrete placing machine can smoothly transition during the coverage of the entire construction area. and , the fabric machine needs to start from End point of sub-region Move to the starting point of the next sub-area The coordinates of the end point and the starting point are and The construction process of the complete path can be summarized as follows: the cloth placing machine starts from the starting point of the first sub-area Set off along the path Cover the first sub-area , and then along the connecting path Enter the next sub-area , repeat this process until all sub-areas are covered and the paths are smoothly connected. Based on the determined sub-area sequence, the paths of each sub-area are reasonably connected to form a complete construction path. The connecting paths must ensure that obstacles are avoided and the transition is smooth, so as to achieve efficient and barrier-free coverage of the concrete placing machine in the entire construction area.

[0054] 207. Determine a movement speed of the concrete placing boom according to a construction path of the concrete placing boom and a concrete pouring amount within a coverage area of ​​the construction path.

[0055] Specifically, during the path planning process within a region, the speed of the concrete placing machine is not only subject to physical limitations, but is also directly related to the task requirements (such as the amount of concrete pouring) within the sub-region. In order to ensure the efficiency of path planning and execution, the speed of the concrete placing machine is At each waypoint A series of constraints need to be met and dynamically adjusted according to task requirements.

[0056] The average movement rate of the fabric distribution machine can be calculated based on the fabric distribution task requirements. Specifically, assuming that each sub-area The amount of concrete required to be poured is , the speed of the placing machine should be adjusted according to the demand for concrete. We can adjust the amount of concrete to be poured by Divide by the total length of the path To calculate the average speed of the fabric placing machine in this area , the formula is as follows:

[0057] in: Is the fabric machine in the sub-area The amount of concrete to be poured. is the total path length of the placing machine in this sub-area.

[0058] This formula ensures that the speed is proportional to the task volume, so that the speed is adjusted accordingly as the path length changes. If the amount of concrete to be poured is large, the speed of the placing boom should be slow to ensure accurate execution of the task; when the amount of concrete to be poured is small, the placing boom can speed up to improve construction efficiency.

[0059] At the same time, the speed of the fabric placing machine must also meet physical constraints. Assume that the maximum allowable speed of the fabric placing machine is , its instantaneous speed The speed must be kept below this upper limit at all times, and the speed must be appropriately reduced when the path has a large curvature or approaches an obstacle. The specific speed constraints are as follows:

[0060] Optionally, when there is a target obstacle in the sub-area, or when the material placing machine encounters a path bend during material placing movement, the speed of the material placing machine can be further adjusted to ensure that the material placing machine completes material placing smoothly.

[0061] 208. Generate a material placing plan for the material placing machine according to the construction path of the material placing machine and the movement speed of the material placing machine.

[0062] Specifically, in determining the global optimal construction path of the concrete placing crane After determining the movement rate of the placing machine in each sub-area, a corresponding placing machine material distribution plan can be generated. Optionally, the placing machine is controlled by a placing machine control module during the construction process, and the placing machine control module can obtain the control instructions of the placing machine according to the parsed placing plan, thereby controlling the placing machine to perform material distribution construction according to the optimal construction path and the corresponding movement rate.

[0063] The embodiment of the present application iteratively optimizes and determines the optimal sub-area sorting and the path sorting corresponding to the sub-areas to determine the optimal final construction path of the concrete placing crane, realizes the collaborative evolution of path planning, and greatly improves the path planning efficiency and execution flexibility of the concrete placing crane in complex environments.

[0064] In one embodiment of the present application, performing sub-region sorting on a plurality of sub-regions to obtain an optimal sub-region sorting scheme includes: Define the objective function of sub-region sorting, where the minimum value of the objective function indicates the minimum number of path intersections; initialize the number of sub-region sorting schemes and the number of iterations; generate multiple sub-region initial sorting schemes according to the number of sub-region sorting schemes, and generate an initial random sub-region sorting for each sub-region initial sorting scheme; initialize the priority matrix, the priority matrix includes the path priority between any two sub-regions, and the path priority represents the priority of moving from one sub-region to another; perform heuristic search and update on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain multiple updated sub-region sorting schemes; after obtaining the multiple updated sub-region sorting schemes, determine the optimal sub-region sorting scheme.

[0065] Specifically, define the objective function of sub-region sorting, and in the search and update process, when the value of the objective function is the minimum, the optimal sub-region sorting solution is obtained. Optionally, the objective function can be used to represent the number of intersections between paths, for example: define the objective function , reducing the number of path crossings. Assuming the area and The connecting line between , the objective function can be expressed as:

[0066] in, Indicates the path and The number of intersections between paths. Path intersections increase the complexity of the path, so the goal is to minimize , that is, reduce the number of crossovers, ideally there should be no crossover.

[0067] Specifically, the number m of sub-region sorting schemes and the number of iterations N are initialized. Correspondingly, when the ant colony algorithm is used to complete the sub-region sorting, the number m of sub-region sorting schemes corresponds to the number of ants in the algorithm. According to the number of sub-region sorting schemes, multiple sub-region initial sorting schemes are generated, and an initial random sub-region sorting is generated for each sub-region initial sorting scheme. The corresponding algorithm generates an initial random path sorting for each ant. At the same time, the priority matrix between each region is initialized. The corresponding priority is the pheromone concentration in the corresponding algorithm. The priority matrix That is, it corresponds to the pheromone concentration matrix in the algorithm, where Indicates from the area To area Optionally, to speed up the search, you can also define heuristic information , Indicates from the area arrive The search heuristic information is usually related to the distance and connection between two regions. The calculation formula of the heuristic information can be defined as:

[0068] in is the Euclidean distance between two regions.

[0069] According to the priority matrix and heuristic information, the initial sorting scheme of each sub-region is updated by heuristic search to obtain multiple updated sub-region sorting schemes; after N rounds of iteration, after obtaining multiple updated sub-region sorting schemes, the optimal sub-region sorting scheme is determined, where the objective function value of the optimal sub-region sorting scheme is the smallest. Optionally, at the end of each round of iteration, the current optimal sub-region sorting scheme can be recorded, and its corresponding objective function value can be recorded. During the iteration process, the optimal sub-region sorting scheme is continuously updated, and the objective function value corresponding to the optimal sorting scheme is updated.

[0070] Optionally, to further improve the quality of the optimal sub-region sorting solution, a local search mechanism can be introduced based on each path found by the ants. Local search can use Large Neighborhood Search (LNS), and the specific operations include: Region swap: randomly select two regions from the path and , swapping their positions in the sorting to generate a new solution .

[0071] Reverse interval: randomly select a subinterval from the current sort , sort the regions in the interval in reverse order.

[0072] Local optimization: Fine-tune the local path and reduce the number of intersections by adjusting the positions of several areas in the path.

[0073] Through local search, the algorithm can further improve the solution found by the ants and avoid falling into the local optimum.

[0074] Pheromone renewal and selection mechanism In each iteration, the new sorting scheme Accepted or rejected based on the following mechanism:

[0075] in, is the current temperature, is the probability of accepting the new solution when it is not better than the old one. Temperature Decays exponentially after each iteration:

[0076] in, is the initial temperature, is the temperature attenuation coefficient, is the number of iterations. Through the pheromone update and selection mechanism, the algorithm gradually converges to the optimal sorting.

[0077] go through After iterations, the ant colony algorithm finally outputs the optimal sub-region sorting solution. ,This scheme minimizes the path crossing while ensuring the sequential optimization of ,each sub-region.

[0078] The embodiment of the present application introduces an algorithm and determines the optimal sub-area sorting scheme through iterative heuristic updates, which facilitates the subsequent path planning of the material placing machine.

[0079] In one embodiment of the present application, a heuristic search is performed on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain multiple updated sub-region sorting schemes, including: The probability of moving from one sub-region to another sub-region in each sub-region sorting scheme is calculated according to the priority matrix; each sub-region sorting scheme is updated according to the probability and the number of iterations to obtain multiple updated sub-region sorting schemes.

[0080] Specifically, the probability of each ant moving to another area can be calculated based on the priority matrix and heuristic information, and the initial sorting scheme of each sub-area can be updated through heuristic search according to the number of iterations to obtain multiple updated sorting schemes of sub-areas. The specific process may include: sorting schemes for each sub-area, that is, constructing a path for each ant based on the priority matrix and heuristic information. When the ant chooses to move from the current area Move to the next area When Determined by the following formula:

[0081] in, and is the weight parameter of path priority and heuristic information, is the set of areas that the ant has not visited yet. Furthermore, in the process of path construction, each ant chooses a path from one area to another according to the above probability, and gradually builds a sorting scheme for the entire area. . Each ant will traverse all areas and eventually form a complete area sorting path, that is, generate an updated sub-area sorting scheme. According to the number of iterations, each round of iteration is completed. During each iteration, the sub-area sorting scheme of each ant is continuously updated. At the same time, after each round of iteration, the ant will update the path priority according to the quality of the path. Optionally, some pheromones can be evaporated to avoid over-strengthening of early paths. The formula is as follows:

[0082] in, is the evaporation coefficient of the path priority, Then, based on the path found by each ant The path priority is enhanced. The increase in path priority is inversely proportional to the path quality. The formula is:

[0083] in, is a constant, is the objective function value of the path found by the ant, that is, the number of path intersections. The fewer the path intersections, the more the path priority increases, thereby guiding more ants to choose high-quality paths. After each round of iteration, at the end of a new round of iteration, each ant will update the priority matrix for a new round of iteration, update its own sub-region sorting scheme, and complete the heuristic search update. Optionally, after multiple rounds of iteration, the ants gradually build better and better sorting schemes. After each round of iteration, the current best sorting is recorded. And its corresponding objective function value Iteration After the round, the final sub-region sorting scheme is determined to be the optimal sub-region sorting scheme.

[0084] The embodiment of the present application completes iteration and updates the priority matrix to ensure that the optimal sub-region sorting scheme is the global optimal.

[0085] In one embodiment of the present application, the path access order corresponding to each sub-region is determined separately, including: taking a sub-region as a target sub-region according to the sorting order in the optimal sub-region sorting scheme; determining the path access starting point of the target sub-region; determining the path access end point of the target sub-region according to the relative position of the next sub-region of the target sub-region; determining the optimal step length of the target sub-region; determining the path access order corresponding to the target sub-region according to the path access starting point, path access end point and optimal step length of the target sub-region; after completing the determination of the path access order corresponding to each target sub-region, determine the path access order corresponding to each sub-region.

[0086] Specifically, in each sub-area The path planning is based on the grid map, which divides the construction area into a series of regular grids. Each grid cell is marked as passable. Or impassable , the fabric machine needs to be Plan a path in the grid to ensure that the entire area is covered and obstacles are avoided. According to the order in the optimal sub-region sorting scheme, solve the path access order corresponding to each sub-region respectively, so as to obtain the path inside each sub-region. Optionally, take the first sub-region in the optimal sub-region sorting scheme as the target sub-region, determine the path access starting point of the target sub-region as the vertex in the upper left corner, determine the path access end point of the first sub-region according to the position of the second sub-region, and determine the optimal step length of the target sub-region, so as to take the path access starting point as the starting point, the path access end point as the midpoint, and the optimal step length as the step length, and make a back-and-forth movement in the target sub-region until the path covers the entire sub-region, connect each grid in the sub-region, and thus obtain the path access order of the target sub-region. Correspondingly, take the second sub-region in the optimal sub-region sorting scheme as the target sub-region, and repeat the path access order determination procedure until the path access order of each sub-region is determined.

[0087] The embodiment of the present application determines the optimal path within each sub-area through path planning within each sub-area, which facilitates the subsequent generation of a construction path.

[0088] In one implementation of the present application, determining a path access starting point of a target sub-area includes: If the target sub-region is the first region in the optimal sub-region sorting scheme, the vertex in the upper left corner of the target sub-region is determined as the starting point of the path access to the target sub-region; if the target sub-region is not the first region in the optimal sub-region sorting scheme, the point in the target sub-region closest to the path access end point of the previous sub-region of the target sub-region is determined as the starting point of the path access to the target sub-region, wherein the previous sub-region of the target sub-region is the sub-region of the previous order of the target sub-region in the optimal sub-region sorting scheme.

[0089] Specifically, first select the starting point for each sub-region. If the current sub-region is not the first sub-region , the starting point is based on the previous sub-region The end point To determine, select the nearest passable grid cell to the end point as the starting point of the current area , to ensure the continuity of the fabric placing machine's movement. If the current sub-area is the first area , by default the upper left grid cell is selected As a starting point, it is convenient for the placing machine to start construction from the sub-area boundary.

[0090] Determining the starting point After that, the placing machine will perform path planning in the current sub-area. For each rectangular sub-area, path planning has three different modes, which correspond to three different end point selections. Assume that the current area is a rectangle with four vertices. , remove the starting point Finally, there are three vertices that can be used as the end point The placement machine will select one of the three remaining vertices as the path endpoint based on specific construction requirements and an estimate of the relative position of the next area.

[0091] The embodiment of the present application determines the starting points of the internal paths of different sub-areas to ensure that the paths between each sub-area are successfully connected.

[0092] In one embodiment of the present application, determining the path access end point of the target sub-area according to the relative position of the next sub-area of ​​the target sub-area includes: Obtain the coordinates of the center point of the next sub-region of the target sub-region, wherein the next sub-region of the target sub-region is the sub-region of the next order of the target sub-region in the optimal sub-region sorting scheme; obtain the coordinates of the optional end point, wherein the optional end point is the three vertices in the target sub-region excluding the path access starting point; calculate the distance between the coordinates of the optional end point and the coordinates of the center point of the next sub-region according to a preset function, and obtain the end point estimation function; minimize the end point estimation function to solve the coordinates of the optimal end point, and determine the optimal end point as the path access end point of the target sub-region.

[0093] Specifically, the next sub-area By the border In order to select the current area The optimal end point of the next region is introduced. , whose coordinates are:

[0094] At this time, the destination selection goal of the current sub-area of ​​the placing machine is to find the next area To select the most appropriate endpoint, a relative position estimation function is used, which calculates the relative position of each potential endpoint. (Right now ) and the center point of the next area The specific formula is:

[0095] in, and are the potential endpoints in the current region. The goal of the fabric placement machine is to minimize this relative position estimation function to find the optimal end point. Specifically, by minimizing the relative position offset function , get the optimal end point : ; Thus, the optimal end point is determined as the path access end point of the target sub-area.

[0096] The embodiment of the present application calculates the optimal path access end point of each sub-area through a relative position estimation function, so as to facilitate the subsequent determination of the optimal path within each sub-area.

[0097] In one embodiment of the present application, determining the optimal step size of the target sub-region includes: Initialize the range of step length values ​​of the target sub-region, select the step length value within the range, and construct a step length value group; randomly select an initial step length from the value group; construct a fitness function based on the coverage rate of the path constructed by the step length and the distance between the path access end point of the target sub-region and the starting point of the next sub-region of the target sub-region; iteratively optimize the value of the initial step length until the value of the fitness function corresponding to the step length reaches a preset condition, and determine the optimal step length of the target sub-region.

[0098] Optional, in the current target sub-region The path planning of the fabric placing machine involves the step length The choice of step length directly determines the coverage efficiency of the cloth placing machine in the area. In order to find the optimal step length, a series of candidate paths are first generated according to different step lengths. Assume that the range of step length is , the system takes multiple discrete step values ​​within this range , each step generates a corresponding coverage path. These paths use a reciprocating motion method, starting from the starting point Start moving along a row to the border, then work your way back in reverse, repeating the process until the entire area is completely covered.

[0099] Optional, to find the optimal step size , we can introduce the simulated annealing algorithm to optimize the step size selection. The simulated annealing algorithm gradually explores the step size space and uses the fitness function to evaluate it to find the step size value that gives the highest quality of path planning. The specific process is as follows: 1. Initial step size selection: From the step size set Randomly select an initial step size , and calculate its fitness function To evaluate the effectiveness of the path.

[0100] 2. Fitness function evaluation: The goal of the fitness function is to measure the performance of the path in the following aspects: Maximizing coverage: Assume that the sub-area The total area is , the area covered by the placing machine is , then part of the fitness function is the coverage:

[0101] Smooth connection between regions: The end point of the route planning should be consistent with the estimated starting point of the next region. Maintain an appropriate distance to ensure smooth switching. Part of the fitness function Used to evaluate the impact of step size selection on switching between regions, the goal is to minimize the distance from the end of the path to the starting point of the next region:

[0102] in,

[0103] 3. Comprehensive fitness function: the overall fitness function It can be expressed as:

[0104] in, , are the importance weights of coverage and inter-regional connectivity, respectively.

[0105] 4. Step size update and annealing process: Neighborhood step size selection: In each round of iteration, from the current step size Start and randomly select a neighboring step size , which can be obtained by making a small random perturbation to the current step size. The acceptance criteria for simulated annealing are as follows:

[0106] in is the current temperature. As the number of iterations increases, the temperature gradually decreases.

[0107] 5. Temperature drop: As the number of iterations increases, the temperature Gradually lowering the temperature can be achieved in the following ways:

[0108] in is the initial temperature, is the temperature attenuation coefficient, is the current iteration number. At high temperatures, the system is more likely to accept poor solutions. As the temperature decreases, the system gradually only accepts better solutions, thus finding the global optimal solution.

[0109] 6. Step length determination: After multiple rounds of annealing iterations, the optimal step length is finally obtained , the corresponding path has a higher coverage rate and can be smoothly connected to the next area.

[0110] The embodiment of the present application introduces a simulated annealing algorithm to iteratively optimize the optimal step length in each sub-region, so as to facilitate the subsequent construction of the optimal path in the sub-region.

[0111] In one embodiment of the present application, the location information of the target obstacle includes the center coordinates and the radius, and when the target obstacle exists in the target sub-area, adjusting the path access order corresponding to the target sub-area according to the location information of the target obstacle includes: Obtain the center coordinates and radius of the target obstacle; when the target path connected by the path access sequence corresponding to the target sub-area intersects with the target obstacle, generate a target detour path, wherein the intersection point is the point on the target path that is closest to the target obstacle, and the distance between the intersection point and the center coordinates of the target obstacle is less than the radius; adjust the path access sequence corresponding to the target sub-area according to the target detour path.

[0112] Specifically, Figure 8 As shown, Figure 8 This is a schematic diagram of an example scenario for generating a detour path in an embodiment of the present application. and a target obstacle in the target sub-area When the paths intersect, local adjustments can be made to the path so that the path can bypass the obstacle and continue to move forward. The specific adjustment process can be carried out through the following steps: 1. Intersection point detection: First, determine the path and obstacles in the target sub-area The intersection point This point is the closest point on the path to the center of the obstacle, and its distance is less than the radius of the obstacle. .

[0113] 2. Local path reconstruction: Once the intersection is detected, the local path can be reconstructed in the vicinity of the intersection. The goal of the reconstructed path is to bypass the obstacle along the edge of the obstacle so that the new path can bypass the obstacle while maintaining the shape of the original path as much as possible. Optionally, the path can be adjusted by the following steps: Determine the path bypass direction, and choose to bypass the obstacle in a clockwise or counterclockwise direction based on the direction of the path and the relative position of the obstacle. Generate a bypass segment. During the bypass process, each new point on the path Need to keep distance from obstacle center for ,in is a small safety distance to ensure that the path does not cling to the edge of the obstacle. The detour formula can be expressed as: ; 3. Return to the obstacle-free area: After the detour path is generated, reconnect the detour path after bypassing the obstacle with the obstacle-free area of ​​the original path, adjust the new path access order, and regenerate the optimal path in the target sub-area according to the updated path access order.

[0114] In the embodiment of the present application, a detour path is generated and the optimal path in the target sub-area is re-updated to ensure that obstacles will not affect the material distribution during the material distribution process of the material distribution machine.

[0115] In one embodiment of the present application, the movement speed of the concrete placing boom is determined according to the construction path of the concrete placing boom and the amount of concrete poured within the coverage of the construction path, including: The initial movement rate of the concrete placing boom is calculated, wherein the initial movement rate of the concrete placing boom is the value of the concrete pouring amount within the coverage range of the construction path divided by the total length of the construction path; the movement rate of the concrete placing boom at the turning point of the construction path is adjusted according to the curvature of the turning point of the construction path; if the construction path passes through the target obstacle, the movement rate of the concrete placing boom when encountering the target obstacle is adjusted according to a preset speed adjustment formula; the movement rate of the concrete placing boom is determined according to the initial movement rate, the movement rate of the concrete placing boom at the turning point, and the movement rate of the concrete placing boom when encountering the target obstacle.

[0116] Specifically, when the concrete placing machine is at a bend or encounters an obstacle, the speed needs to be further adjusted. The specific adjustment method depends on the local curvature of the path. Distance to obstacles When the path curvature is large (i.e. the turning radius is small), the concrete placing machine needs to slow down to maintain accurate path following. The speed calculation formula is:

[0117] in: is the coefficient of speed reduction, Yes The curvature of the path at .

[0118] In addition, when the conveyor moves closer to an obstacle, its speed needs to decrease as the distance to the obstacle decreases. Assume that the distance to the obstacle is , then the speed constraint is further modified as:

[0119] in, is a parameter used to adjust the impact of obstacles.

[0120] In the sub-area, the speed of the placing machine Dynamic adjustment is performed based on the preset amount of concrete to be poured, path curvature, and obstacle distance. After obtaining the corresponding adjustment rate, a specific speed adjustment plan can be generated based on the initial movement rate and the adjusted movement rate, and the speed adjustment plan can be synthesized in the material laying plan. When the material placing crane control module analyzes the material laying plan, it can obtain specific speed adjustment instructions, thereby controlling the material placing crane during the task execution process to ensure that the speed meets the material laying requirements while ensuring safety and accuracy.

[0121] The embodiment of the present application ensures that the material placing machine can ensure the feasibility of path planning while maintaining task efficiency through speed adjustment, thereby avoiding execution errors caused by excessive speed.

[0122] In order to facilitate better implementation of the cloth placing machine path planning method provided in the embodiment of the present application, the embodiment of the present application also provides a device based on the above cloth placing machine path planning method. The meanings of the terms are the same as those in the above cloth placing machine path planning method, and the specific implementation details can refer to the description in the embodiment of the cloth placing machine path planning method.

[0123] The cloth placing machine path planning method device in the embodiment of the present application has the function of implementing the cloth placing machine path planning method provided in the above embodiment. The function can be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more modules corresponding to the above functions, and the modules can be software and / or hardware.

[0124] See also Fig. 9 , Fig. 9 The structure diagram of the cloth placing machine path planning method device provided in the embodiment of the present application is as follows. The cloth placing machine path planning method device can be applied to a computing device in a scenario where a cloth placing machine path planning is required. Specifically, the cloth placing machine path planning method device 900 may include an acquisition module 901, a division module 902, an area sorting module 903, a path sorting module 904, a path adjustment module 905, a connection module 906, a rate determination module 907 and a solution generation module 908, which are as follows: Acquisition module: used to obtain the boundary information of the target construction area and the location information of the target obstacle according to the construction map of the area to be laid; A division module: used for dividing the target construction area into a plurality of sub-areas according to the boundary information and the target obstacle position information; A region sorting module: used for sorting the multiple sub-regions to obtain an optimal sub-region sorting scheme; Path sorting module: used to determine the path access order corresponding to each sub-area; Path adjustment module: used to take a sub-region as a target sub-region, and when there is a target obstacle in the target sub-region, adjust the path access sequence corresponding to the target sub-region according to the position information of the target obstacle, and after adjusting the path access sequence corresponding to each target sub-region, update the path access sequence corresponding to each sub-region to obtain the final path in multiple sub-regions; Connection module: used to connect the final paths in multiple sub-areas in order according to the optimal sub-area sorting scheme to determine the construction path of the concrete placing machine; A rate determination module: determining the movement rate of the concrete placing boom according to the construction path of the concrete placing boom and the amount of concrete poured within the coverage of the construction path; A plan generation module generates a material distribution plan for the material distribution machine according to the construction path of the material distribution machine and the movement speed of the material distribution machine.

[0125] In one embodiment, the region sorting module is specifically used to: An objective function for sorting the sub-regions is defined, wherein a minimum value of the objective function indicates a minimum number of path intersections; Initialize the number and iterations of sub-region sorting schemes; Generate multiple sub-region initial sorting schemes according to the number of the sub-region sorting schemes, and generate an initial random sub-region sorting for each sub-region initial sorting scheme; Initializing a priority matrix, wherein the priority matrix includes a path priority between any two sub-areas, wherein the path priority represents a priority for moving from one sub-area to another sub-area; Performing a heuristic search and updating on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain a plurality of updated sub-region sorting schemes; After obtaining the updated multiple sub-region sorting schemes, an optimal sub-region sorting scheme is determined.

[0126] In one embodiment, the region sorting module is further used to: Calculating the probability of moving from one sub-region to another sub-region in each sub-region sorting scheme according to the priority matrix; Each sub-region sorting scheme is updated according to the probability and the number of iterations to obtain a plurality of updated sub-region sorting schemes.

[0127] In one embodiment, the path sorting module is specifically used to: Taking a sub-region as a target sub-region according to the sorting order in the optimal sub-region sorting scheme; Determine a path access starting point of the target sub-area; Determining a path access endpoint of the target sub-area according to a relative position of a next sub-area of ​​the target sub-area; Determine the optimal step size of the target sub-region; Determine the path access sequence corresponding to the target sub-area according to the path access starting point, path access end point and optimal step length of the target sub-area; After the path access sequence corresponding to each target sub-region is determined, the path access sequence corresponding to each sub-region is determined.

[0128] In one embodiment, the path sorting module is further configured to: If the target sub-region is the first region in the optimal sub-region sorting scheme, determining the vertex at the upper left corner of the target sub-region as the path access starting point of the target sub-region; If the target sub-region is not the first region in the optimal sub-region sorting scheme, the point in the target sub-region that is closest to the end point of the path access of the previous sub-region of the target sub-region is determined as the starting point of the path access of the target sub-region, wherein the previous sub-region of the target sub-region is the sub-region of the previous order of the target sub-region in the optimal sub-region sorting scheme.

[0129] In one embodiment, the path sorting module is further configured to: Acquire the coordinates of the center point of the next sub-region of the target sub-region, wherein the next sub-region of the target sub-region is the sub-region of the next order of the target sub-region in the optimal sub-region sorting scheme; Acquire the coordinates of the optional end point, wherein the optional end point is three vertices in the target sub-area excluding the path access starting point; Calculating the distance between the coordinates of the optional end point and the coordinates of the center point of the next sub-region according to a preset function to obtain an end point estimation function; The endpoint estimation function is minimized to solve the coordinates of the optimal endpoint, and the optimal endpoint is determined as the path access endpoint of the target sub-area.

[0130] In one embodiment, the path sorting module is further configured to: Initialize a value range of the step length of the target sub-region, select a value for the step length within the range, and construct a value group for the step length; Randomly select an initial step size from the value group; A fitness function is constructed based on the coverage of the path constructed by the step length and the distance between the end point of the path visit of the target sub-region and the starting point of the next sub-region of the target sub-region; The value of the initial step length is iteratively optimized until the value of the fitness function corresponding to the step length reaches a preset condition, thereby determining the optimal step length of the target sub-region.

[0131] In one embodiment, the path adjustment module is specifically used to: Obtaining the center coordinates and radius of the target obstacle; When a target path formed by the path access sequence corresponding to the marker area intersects with the target obstacle, a target detour path is generated, wherein the intersection point is the point on the target path that is closest to the target obstacle, and the distance between the intersection point and the center coordinate of the target obstacle is less than the radius; The path access sequence corresponding to the target sub-area is adjusted according to the target detour path.

[0132] In one embodiment, the rate determination module is specifically configured to: Calculating the initial movement rate of the concrete placing boom, wherein the initial movement rate of the concrete placing boom is a value obtained by dividing the amount of concrete poured within the coverage of the construction path by the total length of the construction path; Adjusting the movement speed of the concrete placing boom at the turning point according to the curvature of the construction path at the turning point; If the construction path passes through the target obstacle, the movement speed of the concrete placing machine when encountering the target obstacle is adjusted according to a preset speed adjustment formula; The movement speed of the material placing machine is determined according to the initial movement speed, the movement speed of the material placing machine at the corner, and the movement speed of the material placing machine when encountering the target obstacle.

[0133] The embodiment of the present application simulates the foraging behavior of ants through the Ant Colony Optimization (ACO) algorithm, and uses the pheromone mechanism to sort and optimize the global path. The access order of each sub-area is dynamically generated by the ant colony algorithm, which uses the characteristics of the ant colony to collaboratively select the optimal path in a complex environment, gradually converges to the global optimal path, and reduces path intersection and redundancy. In this process, the ant colony algorithm plays the role of the "selection mechanism" in the evolutionary algorithm, and achieves the global optimal path between regions through iterative updates of the pheromone concentration. Next, the simulated annealing algorithm (SA) plays a core role in local path planning. The algorithm dynamically adjusts the path step size and local adjustment through the temperature decay mechanism of the simulated annealing process to avoid falling into the local optimum. The temperature decay process of simulated annealing is similar to the "mutation and elimination mechanism" in the evolutionary algorithm, which gradually reduces the selection of inferior paths and finally approaches the global optimal solution. This part strengthens the evolutionary search and local optimization in path planning to ensure that the fabricator achieves smooth transition and full coverage in irregular construction areas. In addition, the construction area is discretized through the grid map model, and the concrete placing machine dynamically plans the path based on the feasible area, combined with the real-time obstacle avoidance strategy, and adjusts the path selection in real time according to environmental changes. This dynamic obstacle avoidance and path adjustment process effectively reflects the adaptive characteristics of the evolutionary algorithm. The concrete placing machine can achieve evolutionary correction of the global path by optimizing the local path.

[0134] In summary, the co-evolution of path planning is achieved by combining the global search of the ant colony algorithm with the local optimization of simulated annealing. With the help of the idea of ​​evolutionary algorithm, the algorithm greatly improves the path planning efficiency and execution flexibility of the fabric placing machine in complex environments, and achieves optimal performance in both global and local path planning.

[0135] The technical solutions provided in the embodiments of the present application are introduced in detail above. The principles and implementation methods of the embodiments of the present application are explained by using specific examples in the embodiments of the present application. The description of the above embodiments is only used to help understand the methods and core ideas of the embodiments of the present application. At the same time, for those skilled in the art, according to the ideas of the embodiments of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the embodiments of the present application.

Claims

1. A method for path planning of a material placing machine, characterized in that: The path planning method for a material placing machine comprises: Obtain boundary information of the target construction area and location information of target obstacles according to the construction map of the area to be laid; Dividing the target construction area into a plurality of sub-areas according to the boundary information and the target obstacle position information; Sorting the multiple sub-regions to obtain an optimal sub-region sorting scheme; Determine the path access order corresponding to each sub-area respectively; Taking a sub-region as a target sub-region, when there is a target obstacle in the target sub-region, adjusting the path access order corresponding to the target sub-region according to the position information of the target obstacle, and after adjusting the path access order corresponding to each target sub-region, updating the path access order corresponding to each sub-region to obtain the final paths in the multiple sub-regions; The final paths in multiple sub-areas are connected in sequence according to the optimal sub-area sorting scheme to determine the construction path of the concrete placing machine; Determining the movement speed of the concrete placing boom according to the construction path of the concrete placing boom and the amount of concrete poured within the coverage of the construction path; A material placing plan of the material placing boom is generated according to the construction path of the material placing boom and the movement speed of the material placing boom.

2. The method for path planning of a material placing machine according to claim 1, characterized in that: The step of performing sub-region sorting on the multiple sub-regions to obtain an optimal sub-region sorting scheme includes: An objective function for sorting the sub-regions is defined, wherein a minimum value of the objective function indicates a minimum number of path intersections; Initialize the number and iterations of sub-region sorting schemes; Generate multiple sub-region initial sorting schemes according to the number of the sub-region sorting schemes, and generate an initial random sub-region sorting for each sub-region initial sorting scheme; Initializing a priority matrix, wherein the priority matrix includes a path priority between any two sub-areas, wherein the path priority represents a priority for moving from one sub-area to another sub-area; Performing a heuristic search and updating on each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain a plurality of updated sub-region sorting schemes; After obtaining the updated multiple sub-region sorting schemes, an optimal sub-region sorting scheme is determined.

3. The method for path planning of a material placing machine according to claim 2, characterized in that: The heuristic search and update of each sub-region initial sorting scheme according to the priority matrix and the number of iterations to obtain a plurality of updated sub-region sorting schemes includes: Calculating the probability of moving from one sub-region to another sub-region in each sub-region sorting scheme according to the priority matrix; Each sub-region sorting scheme is updated according to the probability and the number of iterations to obtain a plurality of updated sub-region sorting schemes.

4. The method for path planning of a material placing machine according to claim 1, characterized in that: The determining of the path access sequence corresponding to each sub-area includes: Taking a sub-region as a target sub-region according to the sorting order in the optimal sub-region sorting scheme; Determine a path access starting point of the target sub-area; Determining a path access endpoint of the target sub-area according to a relative position of a next sub-area of ​​the target sub-area; Determine the optimal step size of the target sub-region; Determine the path access sequence corresponding to the target sub-area according to the path access starting point, path access end point and optimal step length of the target sub-area; After the path access sequence corresponding to each target sub-region is determined, the path access sequence corresponding to each sub-region is determined.

5. The method for path planning of a material placing machine according to claim 4, characterized in that: The determining of the path access starting point of the target sub-area includes: If the target sub-region is the first region in the optimal sub-region sorting scheme, determining the vertex at the upper left corner of the target sub-region as the path access starting point of the target sub-region; If the target sub-region is not the first region in the optimal sub-region sorting scheme, the point in the target sub-region that is closest to the end point of the path access of the previous sub-region of the target sub-region is determined as the starting point of the path access of the target sub-region, wherein the previous sub-region of the target sub-region is the sub-region of the previous order of the target sub-region in the optimal sub-region sorting scheme.

6. The method for path planning of a material placing machine according to claim 4, characterized in that: The step of determining the path access endpoint of the target sub-area according to the relative position of the next sub-area of ​​the target sub-area includes: Acquire the coordinates of the center point of the next sub-region of the target sub-region, wherein the next sub-region of the target sub-region is the sub-region of the next order of the target sub-region in the optimal sub-region sorting scheme; Acquire the coordinates of the optional end point, wherein the optional end point is three vertices in the target sub-area excluding the path access starting point; Calculating the distance between the coordinates of the optional end point and the coordinates of the center point of the next sub-region according to a preset function to obtain an end point estimation function; The endpoint estimation function is minimized to solve the coordinates of the optimal endpoint, and the optimal endpoint is determined as the path access endpoint of the target sub-area.

7. The method for path planning of a material placing machine according to claim 4, characterized in that: The step of determining the optimal step length of the target sub-region includes: Initialize a value range of the step length of the target sub-region, select a value for the step length within the range, and construct a value group for the step length; Randomly select an initial step size from the value group; A fitness function is constructed based on the coverage of the path constructed by the step length and the distance between the end point of the path visit of the target sub-region and the starting point of the next sub-region of the target sub-region; The value of the initial step length is iteratively optimized until the value of the fitness function corresponding to the step length reaches a preset condition, thereby determining the optimal step length of the target sub-region.

8. The method for path planning of a material placing machine according to claim 1, characterized in that: The position information of the target obstacle includes a center coordinate and a radius, and when the target obstacle exists in the target sub-area, adjusting the path access sequence corresponding to the target sub-area according to the position information of the target obstacle includes: Obtaining the center coordinates and radius of the target obstacle; When a target path formed by the path access sequence corresponding to the marker area intersects with the target obstacle, a target detour path is generated, wherein the intersection point is the point on the target path that is closest to the target obstacle, and the distance between the intersection point and the center coordinate of the target obstacle is less than the radius; The path access sequence corresponding to the target sub-area is adjusted according to the target detour path.

9. The method for path planning of a material placing machine according to claim 1, characterized in that: The step of determining the movement rate of the concrete placing boom according to the construction path of the concrete placing boom and the amount of concrete poured within the coverage of the construction path includes: Calculating the initial movement rate of the concrete placing boom, wherein the initial movement rate of the concrete placing boom is a value obtained by dividing the amount of concrete poured within the coverage of the construction path by the total length of the construction path; Adjusting the movement speed of the concrete placing boom at the turning point according to the curvature of the construction path at the turning point; If the construction path passes through the target obstacle, the movement speed of the concrete placing machine when encountering the target obstacle is adjusted according to a preset speed adjustment formula; The movement speed of the material placing machine is determined according to the initial movement speed, the movement speed of the material placing machine at the corner, and the movement speed of the material placing machine when encountering the target obstacle.

10. A path planning and analysis device for a material placing machine, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the path planning method for a material distribution machine as claimed in any one of claims 1 to 9 when executing the computer program.

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