High-precision positioning and anti-collision method and system of forklift for factory

Abstract

The invention relates to a high-precision positioning and anti-collision method and system of a forklift for a factory area, and relates to the field of forklift transportation technologies. The method comprises the steps that forklift feedback data and the data detection state of a detection point are obtained; performing data analysis according to the forklift feedback data to determine a feedback existence position; acquiring a previous receiving time point when the data detection state is inconsistent with the data receiving state, and acquiring a previous interval duration according to the previous receiving time point and the current time point; the position drift distance is determined according to the previous interval duration, and the forklift occupied area is delimited according to the feedback existing position and the position drift distance; and in the forklift moving process, the area distance is determined according to the forklift occupied area and the forklift occupied areas of the other forklifts, and when the area distance is smaller than a preset safe distance, avoiding operation is conducted according to a preset avoiding rule. The forklift positioning method has the effect that the situation that the forklift collides with one another due to inaccurate positioning is reduced.

Description

Technical Field

[0001] This application relates to the field of forklift transportation technology, and in particular to a high-precision positioning and collision avoidance method and system for forklifts used in factory areas. Background Technology

[0002] In modern factories, warehouses, and logistics centers, forklifts are core handling tools, and their safety and efficiency are of paramount importance. With the development of smart logistics, achieving real-time high-precision positioning and active collision avoidance of forklifts has become key to improving the level of intelligent management in factories and preventing safety accidents.

[0003] Currently, the most commonly used technology for vehicle positioning within factory areas is Inertial Measurement Unit (IMU) technology. IMU technology relies on sensors such as gyroscopes and accelerometers to autonomously measure the angular velocity and acceleration of an object, and then calculates the object's attitude, velocity, and position through integration. Its advantage lies in its independence from external signals. However, IMU measurement errors accumulate over time, causing significant drift in the calculated position. It cannot provide long-term stable absolute position information independently, resulting in insufficient forklift positioning accuracy and potentially leading to collisions between forklifts. Therefore, there is still room for improvement. Summary of the Invention

[0004] To reduce collisions between forklifts caused by inaccurate positioning, this application provides a high-precision positioning and collision avoidance method and system for forklifts used in factory areas.

[0005] Firstly, this application provides a high-precision positioning and collision avoidance method for forklifts used in factory areas, employing the following technical solution: A high-precision positioning and collision avoidance method for forklifts used in factory areas includes: Acquire forklift feedback data and the data detection status of preset detection points; Data analysis is performed based on forklift feedback data to determine the location of the feedback and to determine whether the data detection status is consistent with the preset data reception status. If the data detection status is consistent with the data reception status, the forklift transportation position is determined according to the corresponding detection point, the area occupied by the forklift is determined according to the forklift transportation position, and the forklift feedback data is updated according to the forklift transportation position. If the data detection status is inconsistent with the data reception status, the previous reception time point is obtained, and the previous interval duration is obtained based on the previous reception time point and the current time point. The position drift distance is determined based on the previous interval, and the forklift occupancy area is defined based on the feedback of the existing position and the position drift distance. During forklift movement, the distance between the forklift's occupied area and the forklifts of other forklifts is determined, and when the distance between the areas is less than the preset safe distance, an avoidance operation is performed according to the preset avoidance rules.

[0006] Optionally, it also includes a step for laying out the detection points, which includes: Get the unlaid-out time period; Obtain the task operation path of each forklift during the unplanned period; Based on the task operation path, determine the location usage popularity according to each location point in the preset operation map; The number of detection points is determined based on the location's usage frequency and the preset number of detection layouts.

[0007] Optionally, the step of determining the detection points based on location heat and the preset number of detection layouts includes: The virtual layout scheme is determined by randomly selecting locations based on the number of detection layouts. In a virtual layout scheme, the area formed by connecting all location points and enclosing the outermost outline is defined as the layout coverage area. The layout coverage ratio is determined by calculating the distribution uniformity coefficient based on the layout coverage area and the preset point representative parameter, and the virtual layout scheme with a layout coverage ratio greater than the preset demand coverage ratio is defined as the effective coverage scheme. In the effective coverage scheme, the effective heat of the scheme is determined by calculating and analyzing the heat of each location point based on the location of the point. The scheme with the largest effective heat value is determined according to the preset sorting rules, and the location point within the effective coverage scheme corresponding to the effective heat value of the scheme is determined as the detection point.

[0008] Optionally, after the effective coverage plan is determined, the high-precision positioning and collision avoidance methods for forklifts used in the factory area also include: The distance between any two locations in the effective coverage scheme is determined, and the smallest distance between locations determined by a single location is defined as the proximity distance. From all similar distances, randomly select one similar distance to define as the primary similar distance, and define all other similar distances as secondary similar distances; The point representative parameter is determined by calculating based on the primary proximity distance and all secondary proximity distances, and the smallest point representative parameter is defined as the distribution uniformity coefficient. Effective coverage schemes with a distribution uniformity coefficient less than the preset reasonable uniformity coefficient are eliminated.

[0009] Optionally, the step of determining the position drift distance based on the previous interval includes: Construct the period of drift existence based on the current time point and the duration of the previous interval; During the period when drift exists, the forklift operation data is determined based on the current forklift feedback data, which includes the acceleration runtime, deceleration runtime, constant speed runtime, and turning runtime. Construct a historical interval on the preset timeline with the current time point as the end point and a width of the preset historical duration, and determine the historical drift distance in the historical interval based on the feedback location of the forklift whose data detection status is consistent with the data reception status and the forklift transportation position; The operational similarity is determined based on the historical forklift operation data and the current forklift operation data, and the historical drift distance of the forklift corresponding to the highest operational similarity is determined as the position drift distance.

[0010] Optionally, after the position drift distance is determined, the high-precision positioning and collision avoidance methods for forklifts in the factory area also include: Determine if the position drift distance is greater than the preset required adjustment distance; If the position drift distance is not greater than the required adjustment distance, control the forklift to maintain the current movement task and move; If the position drift distance is greater than the required adjustment distance, obtain the remaining task path and determine whether there is a detection point in the remaining task path; If there are detection points in the remaining task path, control the forklift to maintain the current movement task and move; If there are no detection points in the remaining task path, the starting point and the target point are determined based on the remaining task path, and a virtual adjustment path containing at least one detection point is constructed on the task map based on the starting point and the target point. Determine a practical adjustment path from all virtual adjustment paths, and control the forklift to move according to the practical adjustment path.

[0011] Optionally, the step of determining a useful adjustment path from all virtual adjustment paths includes: The virtual path distance is determined based on the virtual adjustment path, and the remaining path distance is determined based on the remaining task path; The path deviation distance is determined by calculating the difference between the virtual path distance and the remaining path distance. The number of obstacles to avoid is determined based on the movement tasks of the other forklifts under the virtual adjustment path; The reasonable replacement coefficient is determined based on the path deviation distance and the number of obstacles, and the virtual adjustment path corresponding to the largest reasonable replacement coefficient is determined as the practical adjustment path.

[0012] Secondly, this application provides a high-precision positioning and anti-collision system for forklifts used in factory areas, employing the following technical solution: A high-precision positioning and collision avoidance system for forklifts used in factory areas includes: The acquisition module is used to acquire forklift feedback data and the data detection status of preset detection points; The processing module, connected to the acquisition and judgment modules, is used for information storage and processing; The judgment module, connected to the acquisition and processing modules, is used for judging information. The processing module performs data analysis based on the forklift feedback data to determine the location of the feedback, and the judgment module determines whether the data detection status is consistent with the preset data reception status. If the judgment module determines that the data detection status is consistent with the data reception status, the processing module determines the forklift transportation position based on the corresponding detection point, determines the area occupied by the forklift based on the forklift transportation position, and updates the forklift feedback data based on the forklift transportation position. If the judgment module determines that the data detection status and the data reception status are inconsistent, the acquisition module obtains the previous reception time point and obtains the previous interval duration based on the previous reception time point and the current time point. The processing module determines the position drift distance based on the previous interval duration, and delineates the forklift-occupied area based on the feedback of the existing position and the position drift distance. During forklift movement, the processing module determines the distance between the areas occupied by the forklift and those occupied by other forklifts, and performs an avoidance operation according to preset avoidance rules when the distance between the areas is less than the preset safe distance.

[0013] In summary, this application includes at least one of the following beneficial technical effects: During the movement of the forklift, the sensing between the forklift and the detection point is used to eliminate the drift accumulated by the forklift itself, thereby realizing the forklift positioning using IMU technology and reducing the occurrence of collisions between forklifts due to inaccurate positioning. By rationally arranging the detection points, the forklift is less likely to experience excessive drift during movement, thus achieving better high-precision positioning. When a forklift has accumulated significant drift, the drift can be eliminated by modifying the forklift's task, thereby improving the safety and stability of forklift operations. Attached Figure Description

[0014] Figure 1 This is a flowchart of a high-precision positioning and collision avoidance method for forklifts used in factory areas.

[0015] Figure 2This is a flowchart of a module for high-precision positioning and collision avoidance methods for forklifts used in factory areas. Detailed Implementation

[0016] To make the purpose, technical solution, and advantages of this application clearer, the following is combined with Figures 1-2 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0017] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0018] This application discloses a high-precision positioning and collision avoidance method for forklifts used in factory areas, referring to... Figure 1 The process of high-precision positioning and collision avoidance for forklifts in the factory area includes the following steps: Step S100: Obtain forklift feedback data and the data detection status of preset detection points.

[0019] Forklift feedback data refers to data fed back by devices installed inside the forklift that enable IMU positioning, such as built-in gyroscopes and accelerometers, which measure the forklift's acceleration, angular velocity, and directional changes in real time. Detection points are the locations on the work map where equipment that can establish a connection with the forklift to reflect its actual position is installed, such as RFID base stations. Data detection status refers to the status corresponding to whether the device at the detection point has established a connection with the forklift.

[0020] Step S101: Analyze the data based on the forklift feedback data to determine the location of the feedback and determine whether the data detection status is consistent with the preset data reception status.

[0021] The feedback location refers to the position of the forklift obtained after data analysis based on the forklift's feedback data, which is the location of the location drift obtained using IMU technology; the data reception status refers to the status corresponding to when the forklift establishes a connection with the equipment at the detection point. The purpose of this judgment is to determine whether the actual position of the forklift can be accurately located through the detection point.

[0022] Step S1011: If the data detection status is consistent with the data reception status, then determine the forklift transportation position based on the corresponding detection point, determine the forklift occupied area based on the forklift transportation position, and update the forklift feedback data based on the forklift transportation position.

[0023] When the data detection status is consistent with the data reception status, the actual position of the forklift can be accurately fed back through the detection point. Therefore, the actual position of the forklift can be output based on the detection point, which is the forklift transportation position. The forklift occupied area is the area that the forklift will occupy during the movement when it is in the forklift transportation position. It can be determined by combining the fixed occupied range with the forklift transportation position. At this time, there is no need for IMU positioning technology to locate the forklift. Therefore, the forklift feedback data is reset to zero to eliminate the accumulated drift error. Thus, after the forklift passes the detection point, it can be positioned again with an error starting from 0, thereby improving the forklift positioning accuracy.

[0024] Step S1012: If the data detection status is inconsistent with the data reception status, obtain the previous reception time point, and obtain the previous interval duration based on the previous reception time point and the current time point.

[0025] When the data detection status is inconsistent with the data reception status, it indicates that the forklift cannot be accurately located through the detection point and further analysis is required. The previous reception time point is the time when the current forklift last passed the detection point, and the previous interval duration is the cumulative time that the current forklift has moved since it last passed the detection point.

[0026] Step S102: Determine the position drift distance based on the previous interval duration, and delineate the forklift-occupied area based on the feedback of the existing position and the position drift distance.

[0027] The position drift distance is the maximum distance of positional deviation that will occur under the cumulative movement of the previous interval. Specifically, it can be determined by first training each drift data sample to build a corresponding database of the previous interval and position drift distance. The current position drift distance can be determined by searching the database, or it can be determined by the method in steps S500-S503. By taking the feedback location as the center and the position drift distance as the radius, the area where the forklift may be located in the actual situation can be delineated. Then, by performing the union of the areas occupied by the forklift at each location point, the area occupied by the forklift that will be affected can be obtained.

[0028] Step S103: During the movement of the forklift, determine the distance between the areas occupied by the forklift and the areas occupied by other forklifts, and perform an avoidance operation according to the preset avoidance rules when the distance between the areas is less than the preset safe distance.

[0029] The area separation distance is the distance between the nearest points in the areas occupied by two forklifts. The safe distance is the minimum area separation distance set by the staff to ensure that the two forklifts can maintain relative safety. When the area separation distance is less than the safe distance, it indicates that there is a risk of collision between the forklifts. Therefore, the two forklifts can be avoided according to the preset avoidance rules. The setting of the avoidance rules is not an innovation of this application. The staff can construct appropriate avoidance rules based on the map of each workshop. It will not be elaborated here.

[0030] It also includes the step of laying out the detection points, which includes: Step S200: Obtain the unlaid-out time period.

[0031] The "unmarked period" refers to the time period when no testing points have been set up in the current workshop.

[0032] Step S201: Obtain the task operation path of each forklift during the unplanned period.

[0033] The task operation path is the historical movement path of the forklift that moves during the non-layout period.

[0034] Step S202: Determine the location and use heat according to each location point in the preset task map based on the task operation path.

[0035] The work map is a map of the work area where the forklift is located, such as a workshop map. Location usage heat reflects the frequency with which a location is passed by forklifts. The more forklifts pass by a single location during the non-deployment period, the greater the location usage heat. The data matching relationship between the two can be determined in advance by the staff.

[0036] Step S203: Determine the detection points based on the location, heat usage, and the preset number of detection layouts.

[0037] The number of inspection layouts refers to the number of inspection points that the staff needs to place on the work map. At this time, the inspection points can be determined based on the location using heat. Generally, inspection points will be selected first for locations with higher heat, so that the accumulated drift error can be better eliminated during the subsequent movement of the forklift.

[0038] The steps for determining the number of detection points based on location usage heat and the preset number of detection layouts include: Step S300: Randomly select from each location point based on the number of detected layouts to determine the virtual layout scheme.

[0039] The virtual layout scheme is a scheme composed of randomly selected location points for detecting the number of layouts.

[0040] Step S301: Under the virtual layout scheme, the area formed by connecting each location point to the others and enclosing the outermost outline is defined as the layout coverage area.

[0041] The coverage area refers to the area that the detection points can cover.

[0042] Step S302: Calculate the layout coverage ratio based on the layout coverage area and the preset maximum point representative parameter, and define the distribution uniformity coefficient. Define the virtual layout scheme with a layout coverage ratio greater than the preset required coverage ratio as an effective coverage scheme.

[0043] The largest point representative parameter is defined as the distribution uniformity coefficient, which is the area that the forklift can reach in the operation map. The layout coverage ratio is the proportion of the layout coverage area to the area of ​​the operation map. The demand coverage ratio is the minimum layout coverage ratio that needs to be achieved when the identification detection points set by the staff are effectively distributed in the operation map. By defining the effective coverage scheme, different virtual layout schemes can be distinguished, which is convenient for subsequent analysis.

[0044] Step S303: Calculate and analyze the heat of each location point in the effective coverage scheme to determine the effective heat of the scheme.

[0045] The effective heat of the scheme is the average heat used in all locations.

[0046] Step S304: Determine the effective heat of the scheme with the largest value according to the preset sorting rules, and determine the location point within the effective coverage scheme corresponding to the effective heat of the scheme as the detection point.

[0047] The sorting rules are methods set by staff to sort numerical values, such as the bubble sort method. By using the sorting rules, the effective heat of the scheme with the largest value can be determined, which means that the distribution range of the location points under the current effective coverage scheme meets the requirements, so it can be determined as the detection point.

[0048] Once the effective coverage plan is determined, the high-precision positioning and collision avoidance methods for forklifts used in the factory area also include: Step S400: Determine the distance between any two locations in the effective coverage scheme, and define the smallest distance between locations among all the distances between locations determined for a single location as the proximity distance.

[0049] The location distance is the shortest distance between any two location points in the effective coverage scheme on the accessible path in the operation map. The location proximity distance is defined to identify and distinguish the location distances corresponding to the nearest location points of a single location point, which facilitates subsequent analysis.

[0050] Step S401: Randomly select one location proximity distance from all locations proximity distances and define it as the primary proximity distance, and define all other location proximity distances as secondary proximity distances.

[0051] Define primary and secondary proximity distances to distinguish proximity distances at different locations, which facilitates subsequent analysis.

[0052] Step S402: Calculate the point representative parameter based on the primary proximity distance and all secondary proximity distances, and define the smallest point representative parameter as the distribution uniformity coefficient.

[0053] The point representation parameter reflects the value when the current primary proximity distance represents all other secondary proximity distances. It can be determined by subtracting the primary proximity distance from each secondary proximity distance and taking the reciprocal of the absolute mean. Different primary proximity distances correspond to different point representation parameters. The largest point representation parameter best illustrates the distribution of all current location points. Therefore, it can be defined as the distribution uniformity coefficient.

[0054] Step S403: Eliminate effective coverage schemes whose distribution uniformity coefficient is less than the preset reasonable uniformity coefficient.

[0055] The reasonable uniformity coefficient is the minimum distribution uniformity coefficient that the staff sets to ensure that all locations are relatively evenly distributed on the work map. By eliminating effective coverage schemes with a distribution uniformity coefficient that is less than the reasonable uniformity coefficient, the occurrence of invalid data analysis in the subsequent process can be reduced.

[0056] The steps for determining the position drift distance based on the previous interval include: Step S500: Construct the drift existence period based on the current time point and the previous interval duration.

[0057] The period during which drift exists is the period during which drift accumulates.

[0058] Step S501: During the drift period, determine the forklift operation data based on the current forklift feedback data, wherein the forklift operation data includes acceleration operation duration, deceleration operation duration, constant speed operation duration, and turning operation duration.

[0059] Acceleration runtime is the time the forklift accelerates during the drift period; deceleration runtime is the time the forklift decelerates during the drift period; constant speed runtime is the time the forklift travels at a constant speed during the drift period; and turning runtime is the time the forklift turns during the drift period.

[0060] Step S502: Construct a historical interval on the preset time axis with the current time point as the end point and the width as the preset historical duration, and determine the historical drift distance in the historical interval based on the feedback location of the forklift with the data detection status and data reception status being consistent, as well as the forklift transportation position.

[0061] The time axis is a coordinate axis formed by combining various time points. This coordinate axis points from the time points that have already passed to the time points that have not yet been reached. The time points that have already passed are on the left side of the coordinate axis, and the left side of the coordinate axis is defined as the front side of the time axis. The historical duration is the duration set by the staff for acquiring historical movement data of each forklift. Historical intervals are constructed to facilitate the acquisition and analysis of data within the historical duration. The historical drift distance is the distance of the detected position drift of the forklift at the detection point within the historical interval, which is also the straight-line distance between the feedback position and the forklift's transport position.

[0062] Step S503: Determine the operation similarity based on the historical forklift operation data and the current forklift operation data, and determine the historical drift distance of the forklift corresponding to the highest operation similarity as the position drift distance.

[0063] Operational similarity is a parameter value that reflects the similarity in operation between two forklifts. The specific calculation formula is as follows: ,in To perform similarity calculations, This is the current acceleration runtime of the forklift. For historical forklift acceleration runtime, The weighted parameters are used to reflect the impact of forklift acceleration on the similarity of forklift operation. This represents the current deceleration duration of the forklift. For historical forklift deceleration time, The weighted parameters are used to reflect the impact of forklift deceleration on the similarity of forklift operation. This represents the duration of the forklift's constant speed operation. This refers to the duration of the historical forklift's constant-speed operation. The weighted parameters are used to reflect the impact of the forklift's constant speed travel on the similarity of forklift operation. This represents the current turning time of the forklift. For historical forklift turning time, The weighted parameters reflect the impact of forklift turning on the similarity of forklift operation. By determining the maximum operational similarity, the historical forklift with the most similar movement is identified. The historical drift distance of the historical forklift is then the required position drift distance.

[0064] After determining the position drift distance, the high-precision positioning and collision avoidance methods for forklifts in the factory area also include: Step S600: Determine whether the position drift distance is greater than the preset required adjustment distance.

[0065] The required adjustment distance is the minimum positional drift distance that the staff sets when the forklift's drift distance is considered severe. The purpose of this judgment is to determine whether the current positional drift of the forklift is severe, so as to determine whether the current positional drift of the forklift at the detection point needs to be compensated and updated.

[0066] Step S6001: If the position drift distance is not greater than the required adjustment distance, control the forklift to maintain the current movement task and move.

[0067] When the position drift distance is not greater than the required adjustment distance, it means that the current forklift drift distance is not large and may meet the current motion requirements, so it is sufficient to continue its motion.

[0068] Step S6002: If the position drift distance is greater than the required adjustment distance, obtain the remaining task path and determine whether there is a detection point in the remaining task path.

[0069] When the position drift distance is greater than the required adjustment distance, it indicates that the current forklift has drifted too far and drift data compensation is needed, that is, the current forklift needs to be moved to the detection point; the remaining task path is the path that the current forklift needs to move after performing the current task. The purpose of the judgment is to know whether it can pass the detection point during the subsequent movement.

[0070] Step S60021: If there are detection points in the remaining task path, control the forklift to maintain the current motion task and move.

[0071] If there is a detection point in the remaining task path, it means that the current forklift can make drift data compensation through the detection point in the future. Therefore, the movement operation can continue according to the current task.

[0072] Step S60022: If there are no detection points in the remaining task path, determine the starting point and the target point based on the remaining task path, and construct a virtual adjustment path containing at least one detection point on the work map based on the starting point and the target point.

[0073] When there are no detection points in the remaining task path, it means that the forklift will not pass through the detection points in the future, so further analysis is needed; the starting position point is the position point of the forklift at the current time point, the target position point is the position point to which the forklift needs to move, and the virtual adjustment path is the movement path with the starting position point as the starting point and the target position point as the ending point, and there is no path repetition. This path contains at least one detection point.

[0074] Step S601: Determine a practical adjustment path from all virtual adjustment paths, and control the forklift to move according to the practical adjustment path.

[0075] The practical adjustment path is one of the paths among all the virtual adjustment paths. It can be randomly selected or selected through steps S700-S703. By controlling the forklift to move along the practical adjustment path, the forklift can pass through the detection point, thereby achieving effective compensation for drift data and reducing the occurrence of excessive cumulative drift error of the forklift.

[0076] The steps to determine a useful adjustment path from all virtual adjustment paths include: Step S700: Determine the virtual path distance based on the virtual adjustment path, and determine the remaining path distance based on the remaining task path.

[0077] The virtual path distance is the distance corresponding to the virtual adjusted path, and the remaining path distance is the distance corresponding to the remaining task path.

[0078] Step S701: Calculate the difference between the virtual path distance and the remaining path distance to determine the path deviation distance.

[0079] The path deviation distance is the difference between the virtual path distance and the remaining path distance, and is determined by subtracting the remaining path distance from the virtual path distance.

[0080] Step S702: Determine the number of obstacles to avoid based on the movement tasks of the remaining forklifts under the virtual adjustment path.

[0081] The number of times a forklift will theoretically need to avoid obstacles while moving along a virtual adjusted path is the number of times such an obstacle will occur.

[0082] Step S703: Determine the reasonable replacement coefficient based on the path deviation distance and the number of obstacles, and determine the virtual adjustment path corresponding to the largest reasonable replacement coefficient as the practical adjustment path.

[0083] The replacement appropriateness coefficient is a parameter value that reflects the suitability of the current virtual adjustment path. The larger the value, the better the corresponding virtual adjustment path will be for forklift use. The calculation formula is as follows: ,in To replace the appropriate coefficient, To avoid quantity, The parameter value reflects the importance of the number of obstacles to the calculation of the replacement rationality coefficient. This represents the path deviation distance. The parameter value reflects the importance of the path deviation distance to the calculation of the replacement rationality coefficient; at this time, the virtual adjustment path corresponding to the largest replacement rationality coefficient is determined as the practical adjustment path so that the subsequent forklift movement effect is better.

[0084] Reference Figure 2 Based on the same inventive concept, embodiments of the present invention provide a high-precision positioning and collision avoidance system for forklifts used in factory areas, comprising: The acquisition module is used to acquire forklift feedback data and the data detection status of preset detection points; The processing module, connected to the acquisition and judgment modules, is used for information storage and processing; The judgment module, connected to the acquisition and processing modules, is used for judging information. The processing module performs data analysis based on the forklift feedback data to determine the location of the feedback, and the judgment module determines whether the data detection status is consistent with the preset data reception status. If the judgment module determines that the data detection status is consistent with the data reception status, the processing module determines the forklift transportation position based on the corresponding detection point, determines the area occupied by the forklift based on the forklift transportation position, and updates the forklift feedback data based on the forklift transportation position. If the judgment module determines that the data detection status and the data reception status are inconsistent, the acquisition module obtains the previous reception time point and obtains the previous interval duration based on the previous reception time point and the current time point. The processing module determines the position drift distance based on the previous interval duration, and delineates the forklift-occupied area based on the feedback of the existing position and the position drift distance. During forklift movement, the processing module determines the distance between the areas occupied by the forklift and those occupied by other forklifts, and performs an avoidance operation according to the preset avoidance rules when the distance between the areas is less than the preset safe distance. The detection point layout module is used to lay out the detection points used in the operation map; The detection point selection module is used to select the detection points to be used in practice. The effective coverage scheme elimination module is used to eliminate some effective coverage schemes that cannot meet the requirements in advance, thereby reducing the amount of invalid data analysis. The position drift distance determination module is used to determine a more accurate position drift distance; The drift accumulation elimination module is used to control forklift movement to eliminate situations where there is a lot of accumulated drift. The practical adjustment path determination module is used to determine the practical adjustment path from multiple virtual adjustment paths that meet the requirements.

[0085] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

Claims

1. A high-precision positioning and collision avoidance method for forklifts used in factory areas, characterized in that, include: Acquire forklift feedback data and the data detection status of preset detection points; Data analysis is performed based on forklift feedback data to determine the location of the feedback and to determine whether the data detection status is consistent with the preset data reception status. If the data detection status is consistent with the data reception status, the forklift transportation position is determined according to the corresponding detection point, the area occupied by the forklift is determined according to the forklift transportation position, and the forklift feedback data is updated according to the forklift transportation position. If the data detection status is inconsistent with the data reception status, the previous reception time point is obtained, and the previous interval duration is obtained based on the previous reception time point and the current time point. The position drift distance is determined based on the previous interval, and the forklift occupancy area is defined based on the feedback of the existing position and the position drift distance. During forklift movement, the distance between the forklift's occupied area and the forklifts of other forklifts is determined, and when the distance between the areas is less than the preset safe distance, an avoidance operation is performed according to the preset avoidance rules.

2. The high-precision positioning and collision avoidance method for forklifts used in factory areas according to claim 1, characterized in that, It also includes the step of laying out the detection points, which includes: Get the unlaid-out time period; Obtain the task operation path of each forklift during the unplanned period; Based on the task operation path, determine the location usage popularity according to each location point in the preset operation map; The number of detection points is determined based on the location's usage frequency and the preset number of detection layouts.

3. The high-precision positioning and collision avoidance method for forklifts used in factory areas according to claim 2, characterized in that, The steps for determining the number of detection points based on location usage heat and the preset number of detection layouts include: The virtual layout scheme is determined by randomly selecting locations based on the number of detection layouts. In a virtual layout scheme, the area formed by connecting all location points and enclosing the outermost outline is defined as the layout coverage area. The layout coverage ratio is determined by calculating the distribution uniformity coefficient based on the layout coverage area and the preset point representative parameter, and the virtual layout scheme with a layout coverage ratio greater than the preset demand coverage ratio is defined as the effective coverage scheme. In the effective coverage scheme, the effective heat of the scheme is determined by calculating and analyzing the heat of each location point based on the location of the point. The scheme with the largest effective heat value is determined according to the preset sorting rules, and the location point within the effective coverage scheme corresponding to the effective heat value of the scheme is determined as the detection point.

4. The high-precision positioning and collision avoidance method for forklifts used in factory areas according to claim 3, characterized in that, Once the effective coverage plan is determined, the high-precision positioning and collision avoidance methods for forklifts used in the factory area also include: The distance between any two locations in the effective coverage scheme is determined, and the smallest distance between locations determined by a single location is defined as the proximity distance. From all similar distances, randomly select one similar distance to define as the primary similar distance, and define all other similar distances as secondary similar distances; The point representative parameter is determined by calculating based on the primary proximity distance and all secondary proximity distances, and the smallest point representative parameter is defined as the distribution uniformity coefficient. Effective coverage schemes with a distribution uniformity coefficient less than the preset reasonable uniformity coefficient are eliminated.

5. The high-precision positioning and collision avoidance method for forklifts used in factory areas according to claim 1, characterized in that, The steps for determining the position drift distance based on the previous interval include: Construct the period of drift existence based on the current time point and the duration of the previous interval; During the period when drift exists, the forklift operation data is determined based on the current forklift feedback data, which includes the acceleration runtime, deceleration runtime, constant speed runtime, and turning runtime. Construct a historical interval on the preset timeline with the current time point as the end point and a width of the preset historical duration, and determine the historical drift distance in the historical interval based on the feedback location of the forklift whose data detection status is consistent with the data reception status and the forklift transportation position; The operational similarity is determined based on the historical forklift operation data and the current forklift operation data, and the historical drift distance of the forklift corresponding to the highest operational similarity is determined as the position drift distance.

6. The high-precision positioning and collision avoidance method for forklifts used in factory areas according to claim 1, characterized in that, After determining the position drift distance, the high-precision positioning and collision avoidance methods for forklifts in the factory area also include: Determine if the position drift distance is greater than the preset required adjustment distance; If the position drift distance is not greater than the required adjustment distance, control the forklift to maintain the current movement task and move; If the position drift distance is greater than the required adjustment distance, obtain the remaining task path and determine whether there is a detection point in the remaining task path; If there are detection points in the remaining task path, control the forklift to maintain the current movement task and move; If there are no detection points in the remaining task path, the starting point and the target point are determined based on the remaining task path, and a virtual adjustment path containing at least one detection point is constructed on the task map based on the starting point and the target point. Determine a practical adjustment path from all virtual adjustment paths, and control the forklift to move according to the practical adjustment path.

7. The high-precision positioning and collision avoidance method for forklifts used in factory areas according to claim 6, characterized in that, The steps to determine a useful adjustment path from all virtual adjustment paths include: The virtual path distance is determined based on the virtual adjustment path, and the remaining path distance is determined based on the remaining task path; The path deviation distance is determined by calculating the difference between the virtual path distance and the remaining path distance. The number of obstacles to avoid is determined based on the movement tasks of the other forklifts under the virtual adjustment path; The reasonable replacement coefficient is determined based on the path deviation distance and the number of obstacles, and the virtual adjustment path corresponding to the largest reasonable replacement coefficient is determined as the practical adjustment path.

8. A high-precision positioning and collision avoidance system for forklifts used in factory areas, characterized in that, include: The acquisition module is used to acquire forklift feedback data and the data detection status of preset detection points; The processing module, connected to the acquisition and judgment modules, is used for information storage and processing; The judgment module, connected to the acquisition and processing modules, is used for judging information. The processing module performs data analysis based on the forklift feedback data to determine the location of the feedback, and the judgment module determines whether the data detection status is consistent with the preset data reception status. If the judgment module determines that the data detection status is consistent with the data reception status, the processing module determines the forklift transportation position based on the corresponding detection point, determines the area occupied by the forklift based on the forklift transportation position, and updates the forklift feedback data based on the forklift transportation position. If the judgment module determines that the data detection status and the data reception status are inconsistent, the acquisition module obtains the previous reception time point and obtains the previous interval duration based on the previous reception time point and the current time point. The processing module determines the position drift distance based on the previous interval duration, and delineates the forklift-occupied area based on the feedback of the existing position and the position drift distance. During forklift movement, the processing module determines the distance between the areas occupied by the forklift and those occupied by other forklifts, and performs an avoidance operation according to preset avoidance rules when the distance between the areas is less than the preset safe distance.

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