Path optimization control method and system based on AGV system

Abstract

The present invention discloses a path optimization control method and system based on an AGV system, and relates to the technical field related to AGV control. The method comprises: receiving a first driving path of a first guide vehicle; establishing multiple buffer test areas for multiple continuous target points according to a preset distance; extracting the first buffer test area, and obtaining the corresponding first target point; performing a deceleration test when detecting that the first guide vehicle enters the first buffer test area, generating a first deceleration test result; optimizing braking control parameters, generating a first segmented braking optimization result; and performing braking optimization control on the first road section. The method solves the technical problem that the existing AGV path optimization is based on fixed path planning and speed control, and is difficult to accurately control according to complex and changeable environments, which leads to unstable driving and reduced safety of the AGV. The method realizes accurate braking control of the AGV system, and achieves the technical effect of improving task accuracy, driving safety and stability.

Description

Technical Field

[0001] The present application relates to the technical field related to AGV control, and specifically to a path optimization control method and system based on an AGV system. Background Art

[0002] With the rapid development of automation and intelligent technology, automated guided vehicles (AGVs) are increasingly widely used in warehousing, logistics, manufacturing and other fields. AGV systems can not only significantly improve production efficiency, but also greatly reduce labor costs. They are an important part of modern industrial automation. However, the operating efficiency and safety of AGV systems depend to a large extent on their path optimization control technology. In the AGV system, in situations where precise speed control is required, such as approaching the target point, encountering obstacles or emergency braking, the AGV often "rushes" the target point when reaching the target point. This is mainly manifested in the AGV's unstable parking near the target point or reduced safety, causing it to exceed the predetermined parking position in front of or behind the target point, which not only affects the accuracy of the task, but also may cause delays in subsequent operations and even damage to equipment or goods. Traditional AGV path planning is often based on fixed paths and fixed speed control. This simple control method is incapable of meeting the expectations in the face of complex and changeable industrial environments, especially when there are obstacles on the path, frequent starts and stops, or precise speed control is required. Traditional control methods often fail to achieve the expected results.

[0003] Therefore, in the current AGV system path optimization control related technologies, there are technical problems such as fixed path planning and speed control, which are difficult to accurately control according to complex and changing environments, thus leading to unstable AGV driving and reduced safety. Summary of the invention

[0004] The present application provides a path optimization control method and system based on an AGV system, thereby solving the technical problem that the existing AGV path optimization is based on fixed path planning and speed control, which makes it difficult to perform precise control according to complex and changeable environments, thus leading to unstable AGV driving and reduced safety. The application realizes precise braking control of the AGV system, achieving the technical effect of improving task accuracy, driving safety and stability.

[0005] The present application provides a path optimization control method based on an AGV system, the method comprising: connecting the AGV system to receive a first driving path of a first guide vehicle; extracting multiple continuous target points according to the first driving path, and establishing multiple buffer test areas for the multiple continuous target points according to preset distances; extracting a first buffer test area from the multiple buffer test areas, and obtaining the corresponding first target point; controlling the first guide vehicle to travel to the first target point according to the first driving path, and performing a deceleration test when it is detected that the first guide vehicle enters the first buffer test area, generating a first deceleration test result; optimizing braking control parameters for a first section between the first buffer test area and the first target point according to the first deceleration test result, and generating a first segmented braking optimization result; and performing braking optimization control on the first section with the first segmented braking optimization result.

[0006] In a possible implementation, multiple continuous target points are extracted according to the first driving path, and multiple buffer test areas are established for the multiple continuous target points according to preset distances, and the following processing is also performed: multiple segmented paths with the multiple continuous target points as stop targets are obtained according to the first driving path; segmented load conditions and pre-braking speeds corresponding to the multiple segmented paths are obtained; the segmented load conditions and the pre-braking speeds are input into a braking simulation model for braking simulation to generate braking distances corresponding to the multiple segmented paths, wherein the braking simulation model is trained based on historical braking data of the same road conditions and the same guide vehicle; the braking distance is amplified according to a preset tolerance constraint to generate a preset distance corresponding to the segmented path; and the multiple buffer test areas are configured on the multiple segmented paths according to the preset distances.

[0007] In a possible implementation, the multiple buffer test areas are configured on the multiple segmented paths according to the preset distance, and the following processing is also performed: configuring a preset deceleration test distance; using the preset deceleration test distance as the area length of the multiple buffer test areas, using the preset distance as the distance from the multiple buffer test areas to the multiple continuous target points, and configuring the multiple buffer test areas on the multiple segmented paths.

[0008] In a possible implementation, the first guide vehicle is controlled to travel toward the first target point according to the first driving path. When it is detected that the first guide vehicle enters the first buffer test area for a deceleration test, a first deceleration test result is generated, and the following processing is also performed: a buffer test sample constraint is established, wherein the buffer test sample constraint includes a first test sample constraint and a second test sample constraint, the first test sample constraint is that the deceleration threshold satisfies a first preset threshold, the second test sample constraint is that the deceleration threshold satisfies a second preset threshold, and the first preset threshold is greater than the second preset threshold; deceleration test data is configured according to the first test sample constraint and the second test sample constraint; the deceleration test data is input into the controller of the first guide vehicle for a deceleration test, and the deceleration control deviation is analyzed to generate the first deceleration test result.

[0009] In a possible implementation, deceleration test data is configured according to the first test sample constraint and the second test sample constraint, and the following processing is also performed: when the first guide vehicle is detected to enter the first buffer test area, the first real-time speed of the first guide vehicle is obtained; based on the first real-time speed, continuous deceleration phase data is generated in combination with the first test sample constraint and the second test sample constraint; the deceleration test data is generated based on the continuous deceleration phase data, wherein the deceleration test data includes two deceleration control nodes.

[0010] In a possible implementation, the deceleration test data is input into the controller of the first guide vehicle for a deceleration test, and the deceleration control deviation is analyzed to generate the first deceleration test result, and the following processing is also performed: the smoothness characteristics of the wheels and the road surface of the first guide vehicle are collected, and in combination with the segmented load conditions, the deceleration modeling of the controller of the first guide vehicle is performed to generate a first deceleration simulation model; the deceleration test data is input into the first deceleration simulation model to perform a deceleration simulation and generate a standard speed change timing sequence; the deceleration test data is input into the controller of the first guide vehicle for a deceleration test and the actual test speed change timing sequence is recorded; the standard speed change timing sequence is aligned with the actual test speed change timing sequence in time and space and then compared to generate speed deviations corresponding to multiple space-time nodes; the first deceleration test result is generated with the speed deviations corresponding to the multiple space-time nodes.

[0011] In a possible implementation, braking control parameters are optimized for a first section between the first buffer test area and the first target point based on the first deceleration test result to generate a first segmented braking optimization result, and the following processing is also performed: a first pre-braking speed and a first braking point are extracted on the first section; a deceleration control deviation is determined based on the first deceleration test result to determine whether a preset deviation threshold is met; if not, a braking distance is simulated after correcting the first pre-braking speed based on the deceleration control deviation, and the first braking point is optimized based on the prediction result to generate the first segmented braking optimization result.

[0012] The present application also provides a path optimization control system based on an AGV system, including: a first driving path receiving module, used to connect to the AGV system to receive a first driving path of a first guide vehicle; a buffer test area establishment module, used to extract multiple continuous target points according to the first driving path, and establish multiple buffer test areas for the multiple continuous target points according to a preset distance; a first target point acquisition module, used to extract a first buffer test area from the multiple buffer test areas, and obtain the corresponding first target point; a first deceleration test result generation module, used to control the first guide vehicle to travel to the first target point according to the first driving path, and when it is detected that the first guide vehicle enters the first buffer test area, a deceleration test is performed to generate a first deceleration test result; a braking control parameter optimization module, used to optimize the braking control parameters for the first section between the first buffer test area and the first target point according to the first deceleration test result, and generate a first segmented braking optimization result; a braking optimization control module, used to perform braking optimization control on the first section with the first segmented braking optimization result.

[0013] The path optimization control method and system based on the AGV system proposed in this application is intended to receive the first driving path of the first guide vehicle; establish multiple buffer test areas for multiple continuous target points according to the preset distance; extract the first buffer test area and obtain the corresponding first target point; when the first guide vehicle is detected to enter the first buffer test area, a deceleration test is performed and a first deceleration test result is generated; brake control parameters are optimized to generate a first segmented braking optimization result; and brake optimization control is performed on the first road section. The technical problem that the existing AGV path optimization is based on fixed path planning and speed control, which makes it difficult to accurately control according to complex and changing environments, and thus leads to unstable driving and reduced safety of AGVs is solved, and accurate braking control of the AGV system is achieved, achieving the technical effect of improving task accuracy, driving safety and stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure will be briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0015] Figure 1 A schematic diagram of a path optimization control method based on an AGV system provided in an embodiment of the present application;

[0016] Figure 2 A schematic diagram of the structure of a path optimization control system based on an AGV system provided in an embodiment of the present application.

[0017] Explanation of the reference numerals: first driving path receiving module 10 , buffer test area establishing module 20 , first target point acquiring module 30 , first deceleration test result generating module 40 , braking control parameter optimizing module 50 , braking optimization control module 60 . DETAILED DESCRIPTION

[0018] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0019] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0020] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0021] The present application embodiment provides a path optimization control method based on an AGV system, such as Figure 1 As shown, the method includes:

[0022] Step S100, connecting to the AGV system to receive a first driving path of a first guide vehicle.

[0023] Preferably, the AGV system (Automated Guided Vehicle System) refers to a material handling system based on automation technology, which realizes automatic handling and transportation of goods by using an automated guided vehicle (AGV), and usually includes an AGV vehicle, which is responsible for carrying goods according to a preset path or instruction. The AGV vehicle can be designed and customized according to different application scenarios, such as a forklift AGV for carrying heavy goods, a roller AGV for material distribution on a production line, etc.; a navigation and positioning unit, the AGV system needs to be able to accurately know the position and driving direction of the AGV vehicle, which is usually achieved through a navigation and positioning unit, including magnetic stripe navigation, laser navigation, inertial navigation, visual navigation, etc., to ensure that the AGV vehicle can travel stably and accurately in various environments; a central control unit, which is responsible for receiving and processing information from each AGV vehicle, and issuing instructions to control the driving of the AGV vehicle, realizing path planning, task allocation, traffic management, etc.; a communication and interaction unit, the AGV system needs to communicate and interact with other systems or devices, such as communicating with the PLC (programmable logic controller) of the production line to obtain production requirements, or interacting with the warehouse management system to obtain cargo information.

[0024] Preferably, connecting the AGV system to receive the first driving path of the first guide vehicle means that the AGV system has established a communication connection with a specific guide vehicle (which may be one of the AGV fleet), such as through a wireless network, a wired network or other communication protocols, to ensure that the AGV system can receive and process data and information from the guide vehicle. Specifically, the AGV system receives information about the first driving path from the guide vehicle, which may include the starting point, end point, intermediate point, path type (such as a straight line, a curve, an intersection, etc.), obstacle positions on the path, driving speed, braking points and other factors that may affect the driving of the AGV. The first driving path is the driving path corresponding to the first guide vehicle. Based on the driving path information, a specific driving strategy can be planned, which may include determining the optimal driving speed, acceleration, steering angle and other parameters, as well as how to avoid obstacles or re-plan the path when encountering obstacles.

[0025] Step S200: extracting a plurality of continuous target points according to the first driving path, and establishing a plurality of buffer test areas for the plurality of continuous target points according to preset distances.

[0026] Preferably, the received first driving path is parsed, and multiple continuous target points on the driving path are extracted according to the characteristics of the path and actual needs. These target points are usually key positions on the path, such as turning points, intersections, in front of obstacles, etc., and then multiple buffer test areas are established for the multiple continuous target points according to preset distances. Specifically, after extracting multiple continuous target points, the AGV system establishes a buffer test area of ​​a certain range around each target point according to preset distance parameters. This preset distance is usually determined based on factors such as AGV performance parameters (such as braking distance, acceleration, etc.), path characteristics (such as curvature, slope, etc.) and safety requirements. The buffer test area is a circular or elliptical area with each target point as the center and a preset distance as the radius (it can also be other shapes, such as rectangles, etc., depending on the application scenario and path characteristics). These areas are used to perform deceleration tests, brake control parameter optimization and other experiments when the AGV travels near the target point to ensure that the AGV can reach the target point safely and stably. The main function of the buffer test area is to provide a safe and controllable test environment for evaluating and optimizing the driving performance and braking control parameters of the AGV when approaching the target point. By performing deceleration tests and optimizing braking control parameters in these areas, the AGV system can more accurately grasp the driving characteristics of the AGV under different conditions, thereby achieving fine control and optimization of the AGV driving process.

[0027] In a possible implementation, step S200 further includes step S210, obtaining multiple segmented paths with the multiple continuous target points as stop targets according to the first driving path; step S220, obtaining segmented load conditions and pre-braking speeds corresponding to the multiple segmented paths; step S230, inputting the segmented load conditions and the pre-braking speed into a braking simulation model for braking simulation, and generating braking distances corresponding to the multiple segmented paths, wherein the braking simulation model is trained based on historical braking data of the same road conditions and the same guide vehicle; step S240, amplifying the braking distance according to a preset tolerance constraint, and generating a preset distance corresponding to the segmented path; step S250, configuring the multiple buffer test areas on the multiple segmented paths according to the preset distance.

[0028] Preferably, the first driving path includes multiple continuous target points, and this complete driving path is divided into multiple segmented paths. The end point of each segmented path is a target stop point, so as to more accurately control the driving and braking of the AGV, thereby obtaining multiple segmented paths with the target points as the stop targets. During the driving process of the AGV, its load conditions and speed may change, and these changes will directly affect its braking performance. For each segmented path, its corresponding load conditions and pre-braking speed are collected or calculated. The load conditions may include the weight and distribution of the goods carried by the AGV, and the pre-braking speed is the speed of the AGV when entering the segmented path. Then, a braking simulation model is used for simulation to predict the braking distance of the AGV under different load and speed conditions. Specifically, the braking simulation model is trained based on the historical braking data of the same road conditions and the same guide vehicle. The braking process of the AGV can be simulated according to the input load conditions and pre-braking speed, and the braking distance can be calculated.

[0029] Preferably, the load condition and pre-braking speed of each segmented path are input into the braking simulation model to perform braking simulation, thereby generating braking distances corresponding to multiple segmented paths; in actual driving, due to various uncertain factors (such as changes in road conditions, fluctuations in AGV performance, etc.), the actual braking distance of the AGV may be longer than the simulation result, so a preset tolerance constraint is set, that is, a safety margin, and then the braking distance is amplified according to the preset tolerance constraint to obtain a preset distance corresponding to each segmented path, and the preset distance is longer than the braking simulation result to ensure that the AGV has enough safety distance for braking in actual driving; finally, a buffer test area is configured according to the preset distance, that is, within the preset distance range of each segmented path, obvious signs or obstacles (such as speed bumps, warning lights, etc.) are set to remind and guide the AGV to perform a deceleration test, and finally multiple buffer test areas are obtained for performing a deceleration test before the AGV actually drives to ensure that its braking performance meets the requirements and improves the driving efficiency of the AGV.

[0030] In a possible implementation, step S250 further includes step S251, configuring a preset deceleration test distance; step S252, using the preset deceleration test distance as the area length of the multiple buffer test areas, using the preset distance as the distance from the multiple buffer test areas to the multiple continuous target points, and configuring the multiple buffer test areas on the multiple segmented paths.

[0031] Preferably, a preset deceleration test distance is determined based on factors such as the braking performance, road conditions, and load conditions of the AGV. This preset deceleration test distance should be long enough to ensure that the AGV can safely reduce its speed during the deceleration test, but not too long to avoid wasting the driving path, for subsequent configuration of a buffer test area; then the configured preset deceleration test distance is used as the area length of each buffer test area, that is, each buffer test area has the same deceleration test length, which is used for the AGV to perform a deceleration test, and then the preset distance is used as the distance from each buffer test area to its corresponding continuous target point, that is, starting from the starting point of the buffer test area, the AGV needs to travel this preset distance to reach the target point, and the specific distance from each buffer test area to its corresponding target point is determined. Finally, according to the preset deceleration test distance of each segmented path, the length of each buffer test area, and the distance from each buffer test area to the target point, the corresponding buffer test area is configured on each segmented path. These areas should be located on the AGV driving path and have a certain preset distance from the target point to ensure that the AGV has enough space for a deceleration test before approaching the target point, and ensure that it can smoothly decelerate and stop when approaching the target point.

[0032] Step S300 , extracting a first buffer test area from the plurality of buffer test areas, and acquiring a corresponding first target point.

[0033] Preferably, a buffer test area to be processed is randomly selected from multiple buffer test areas as the first buffer test area, and the position and range of the first buffer test area are accurately identified. This position and range are usually set in the path planning stage. It is a circular or elliptical area (or other shapes) with the target point as the center and a preset distance as the radius. After extracting the first buffer area, further identify and obtain the first target point corresponding to the area. This first target point is usually the center point of the buffer test area and is also the key position that the AGV needs to reach during driving. In addition to the position information of the target point, the AGV system also obtains other information related to the target point, such as path type, obstacle location, speed limit, etc., which is helpful for subsequent driving control and optimization. After obtaining the information of the first target point, the AGV system can prepare for subsequent driving control and optimization steps, such as planning the driving path according to the position of the target point and related information, setting driving parameters (such as speed, acceleration, etc.), and preparing for deceleration tests and braking control parameter optimization experiments.

[0034] Step S400: Control the first guide vehicle to travel toward the first target point according to the first driving path, and generate a first deceleration test result when it is detected that the first guide vehicle enters the first buffer test area to perform a deceleration test.

[0035] Preferably, the AGV system controls the first guide vehicle (i.e., a specific AVG guide vehicle) to travel along the preset first driving path toward the first target point. During the driving process, the AGV system monitors the position and speed of the guide vehicle in real time to ensure that it can accurately travel along the path. Advanced navigation and positioning technologies, such as laser navigation and visual navigation, are usually used to achieve precise driving control to ensure that the guide vehicle maintains a stable driving state in a complex and changeable environment. When the first guide vehicle approaches the first buffer test area, the AGV system uses sensors or other detection means to identify whether the guide vehicle has entered the area to ensure that the guide vehicle can be tested in a safe environment. When it is detected that the guide vehicle has entered the first buffer test area, the deceleration test program is immediately triggered. The program controls the guide vehicle to decelerate according to the preset deceleration strategy to evaluate its braking performance and stability when approaching the target point. During the deceleration test, key data such as the speed, acceleration, and position of the guide vehicle are collected in real time, and these data are analyzed and processed to generate a first deceleration test result, which usually includes key indicators such as the deceleration performance, braking distance, stability, and whether there are abnormalities of the guide vehicle.

[0036] In a possible implementation, step S400 further includes step S410, establishing a buffer test sample constraint, wherein the buffer test sample constraint includes a first test sample constraint and a second test sample constraint, the first test sample constraint is that the deceleration threshold satisfies a first preset threshold, the second test sample constraint is that the deceleration threshold satisfies a second preset threshold, and the first preset threshold is greater than the second preset threshold; step S420, configuring deceleration test data according to the first test sample constraint and the second test sample constraint; step S430, inputting the deceleration test data into the controller of the first guide vehicle for a deceleration test, and analyzing the deceleration control deviation to generate the first deceleration test result.

[0037] Preferably, during the deceleration test of the AGV (automated guided vehicle), a buffer test sample constraint (including a first test sample constraint and a second test sample constraint) is established to ensure the accuracy and effectiveness of the test. Specifically, the first test sample refers to the deceleration threshold satisfying the first preset threshold, wherein the deceleration threshold refers to the minimum deceleration rate that the AGV needs to reach during the deceleration test. The first preset threshold is a relatively high value, which requires the AGV to be able to decelerate quickly during the test, and is used to evaluate the braking performance of the AGV in an emergency situation; the second test sample constraint refers to the deceleration threshold satisfying the second preset threshold. Unlike the first test sample constraint, the second preset threshold is a relatively low value, which requires the AGV to be able to decelerate smoothly during the test, and is used to evaluate the braking stability of the AGV during normal driving; the first preset threshold being greater than the second preset threshold means that the first test sample constraint has higher requirements on the braking performance of the AGV, while the second test sample constraint pays more attention to braking stability. Through the first test sample constraint and the second test sample constraint, the braking performance of the AGV under different conditions can be more comprehensively evaluated.

[0038] Preferably, the deceleration test data is configured according to the first test sample constraint and the second test sample constraint, including configuring the initial speed, target speed, deceleration time, deceleration distance and other parameters of the AGV to ensure that the test process meets the constraint requirements, and then the configured deceleration test data is input into the controller of the first guide vehicle for a deceleration test. During the test, the AGV will decelerate according to the input deceleration test data, and record the deceleration process of the AGV, including deceleration rate, deceleration time, deceleration distance and other parameters. After the test is completed, the deceleration process of the AGV is analyzed, including calculating the deviation between the actual deceleration rate of the AGV and the expected deceleration rate, and evaluating the stability and accuracy of the AGV during the deceleration process. According to the analysis results, a first deceleration test result is generated, including the performance of the AGV in the deceleration test, the size of the deceleration control deviation, and whether the buffer test sample constraints are met, so as to more comprehensively evaluate the braking performance and stability of the AGV.

[0039] In a possible implementation, step S420 further includes step S421, when it is detected that the first guide vehicle enters the first buffer test area, obtaining the first real-time speed of the first guide vehicle; step S422, taking the first real-time speed as a base, combining the first test sample constraint and the second test sample constraint to generate continuous deceleration phase data; step S423, generating the deceleration test data with the continuous deceleration phase data, wherein the deceleration test data includes two deceleration control nodes.

[0040] Preferably, during the driving process of the AGV (automated guided vehicle), its position is continuously monitored. When the first guide vehicle is detected to enter the preset first buffer test area, its current speed, i.e., the first real-time speed, is immediately obtained. Then, based on the first real-time speed, combined with the first test sample constraint and the second test sample constraint, data of the continuous deceleration stage is generated, which describes the process of how the AGV gradually decelerates from the current speed to the target speed. Specifically, the first test sample constraint requires that the AGV can achieve a higher deceleration rate (i.e., a faster deceleration speed change) during the deceleration process, which is used to evaluate the braking performance of the AGV in emergency situations; the second test sample constraint requires that the AGV can achieve a higher deceleration rate (i.e., a faster deceleration speed change) during the deceleration process, which is used to evaluate the braking performance of the AGV in emergency situations; the second test sample constraint requires that the AGV V can decelerate smoothly during the deceleration process to avoid excessive speed fluctuations, which is used to evaluate the braking stability of the AGV during normal driving; and then generate a continuous deceleration stage data that meets the emergency braking requirements and ensures smooth deceleration; finally, based on the data of the continuous deceleration stage, generate complete deceleration test data, including two key deceleration control nodes. The first deceleration control node marks the moment and speed when the AGV starts to decelerate, which usually corresponds to the first real-time speed and is the starting point of the deceleration test; the second deceleration control node marks the moment and speed when the AGV decelerates, which is the target speed that the AGV needs to achieve during the deceleration test, and is also a key indicator for evaluating deceleration performance. Through these two deceleration control nodes, the speed changes of the AGV during the deceleration test can be fully described, thereby evaluating its braking performance and stability.

[0041] In a possible implementation, step S430 further includes step S431, collecting the smoothness characteristics of the wheels and the road surface of the first guide vehicle, and combining the segmented load conditions to perform deceleration modeling on the controller of the first guide vehicle to generate a first deceleration simulation model; step S432, inputting the deceleration test data into the first deceleration simulation model to perform deceleration simulation and generate a standard speed change timing; step S433, inputting the deceleration test data into the controller of the first guide vehicle to perform a deceleration test, and recording the actual test speed change timing; step S434, performing time and space alignment on the standard speed change timing and the actual test speed change timing, and then comparing them to generate speed deviations corresponding to multiple space-time nodes; step S435, generating the first deceleration test result with the speed deviations corresponding to the multiple space-time nodes.

[0042] Preferably, the smoothness characteristics of the wheels of the first guide vehicle and the current driving road surface are collected, including the friction coefficient between the wheels and the road surface, the unevenness of the road surface, etc., and the current load conditions of the AGV are considered, such as the weight and distribution of the load, which affect the braking performance and deceleration effect of the AGV. Then, based on the collected smoothness characteristics and segmented load conditions, the deceleration model of the controller of the first guide vehicle is performed. This model will simulate the deceleration process of the AGV under different road surfaces and load conditions, and generate a first deceleration simulation model; the generated deceleration test data (such as the initial speed, target speed, deceleration time and other parameters of the AGV) is input into the first deceleration simulation model. The model will simulate the deceleration process of the AGV according to the input deceleration test data and the preset algorithm, and generate a standard speed change time series. This time series describes the AGV under ideal conditions (i.e., the situation predicted by the model). Similarly, the deceleration test data is input into the actual controller of the first guide vehicle, and the AGV will perform a deceleration test according to the instructions of the controller, record the speed change of the AGV test process in real time, generate an actual test speed change sequence, and then align the standard speed change sequence with the actual test speed change sequence in time and space, that is, find the corresponding time points and spatial positions in the two sequence to accurately compare the standard speed change sequence with the actual test speed change sequence, and then calculate the deviation between the standard speed and the actual speed at each time and space node, reflecting the difference between the AGV in the actual deceleration process and the model prediction, and summarize the speed deviations at all time and space nodes to generate a complete speed deviation data set, and then generate the first deceleration test results, including the performance of the AGV in the deceleration test, the size and distribution of the speed deviation, and other information. This information can be used to evaluate the braking performance and deceleration stability of the AGV, as well as the accuracy of the model prediction.

[0043] Step S500: optimizing braking control parameters for a first road section between the first buffer test area and the first target point according to the first deceleration test result, and generating a first segmented braking optimization result.

[0044] Preferably, according to the first deceleration test result (including the speed change, braking distance, acceleration, etc. of the AGV in the first buffer test area), the braking control parameters of the first section between the first buffer test area and the first target point are optimized, that is, the most suitable braking parameter combination for the section is found to improve the driving safety and efficiency of the AGV in the section. Specifically, the collected data is analyzed to find out the problems and shortcomings of the AGV driving under the current braking control parameters. For example, problems such as long braking distance and unstable acceleration change may be found. Based on the data analysis results, the braking control parameters are adjusted and optimized, which may include adjusting parameters such as the response time of the brake, the size of the braking force, and the shape of the braking curve, so that the braking performance of the AGV on the first section is more stable and efficient. After adjusting the braking control parameters, it is necessary to perform a deceleration test again to verify the optimization effect. By comparing the test results before and after optimization, the effectiveness of the optimization measures can be evaluated, and finally the first-segment braking optimization results can be generated, which usually include the optimized braking control parameter combination, performance comparison data before and after optimization, etc., providing important support for subsequent AGV system optimization decisions. For example, the driving strategy of the AGV can be adjusted based on the results to further improve the driving performance and stability of the AGV on a specific road section.

[0045] In a possible implementation, step S500 further includes step S510, extracting the first pre-braking speed and the first braking point on the first road section; step S520, judging whether the deceleration control deviation meets the preset deviation threshold according to the first deceleration test result; step S530, if not, correcting the first pre-braking speed according to the deceleration control deviation and then simulating the braking distance, optimizing the first braking point according to the prediction result, and generating the first segmented braking optimization result.

[0046] Preferably, the speed of the AGV (automated guided vehicle) before braking, i.e., the first pre-braking speed, is recorded in the first section, and the position where the AGV starts braking, i.e., the first braking point, is recorded. This position determines when the AGV starts decelerating. Then, based on the first deceleration test result, it is determined whether the deceleration control deviation meets the preset deviation threshold. Specifically, the deceleration control deviation in the first deceleration test result is analyzed, and the deceleration control deviation is compared with the preset deviation threshold. If the deceleration control deviation is less than or equal to the preset deviation threshold, it means that the braking performance of the AGV meets the requirements and no further optimization is required. If the deceleration control deviation is greater than the preset deviation threshold, then Optimization measures need to be taken to correct the first pre-braking speed according to the deceleration control deviation, so that the speed of the AGV before braking is closer to the expected braking speed, thereby reducing the deceleration control deviation. After correction, the braking distance is simulated, that is, considering the current speed, braking performance, road conditions and other factors of the AGV, and predicting the braking distance of the AGV at different pre-braking speeds. Then, based on the simulation results of the braking distance, the first braking point is optimized to find a more suitable braking starting position, so that the AGV can decelerate to the target speed more smoothly while ensuring safety. Finally, the first segmented braking optimization result is generated to ensure its safety and stability during actual driving.

[0047] Step S600: performing braking optimization control on the first road section based on the first segmented braking optimization result.

[0048] Preferably, the first segment braking optimization result obtained through testing and analysis is applied to the braking control process of the first section to achieve better driving performance and higher safety. Specifically, according to the first segment braking optimization result, the braking control parameters of the AGV when driving on the first section are adjusted, such as the response time of the brake, the size of the braking force, the speed threshold for the start and end of braking, etc. The adjusted braking control parameters are input into the control system of the AGV to ensure that the AGV can perform braking control according to the new parameters when driving to the first section. During the driving of the AGV, its driving state, including speed, acceleration, position, etc., is detected in real time through sensors and monitoring systems to ensure that the AGV can drive according to the expected braking control strategy. The braking distance, braking stability, driving efficiency and other indicators of the AGV are evaluated to verify the effect of the optimized control. According to the results of the performance evaluation, if it is found that the driving performance of the AGV still needs to be improved, the braking control parameters can be further adjusted, and a new round of optimized control can be carried out. Through fine adjustment and optimization of the braking control parameters, the driving performance and safety of the AGV on a specific section can be significantly improved.

[0049] In the above, refer to Figure 1The path optimization control method based on the AGV system according to the embodiment of the present invention is described in detail. Figure 2 A path optimization control system based on an AGV system according to an embodiment of the present invention is described.

[0050] The path optimization control system based on the AGV system according to the embodiment of the present invention is used to solve the technical problems that the existing AGV path optimization is based on fixed path planning and speed control, which is difficult to accurately control according to complex and changeable environments, thereby causing unstable driving and reduced safety of the AGV, and realizes precise braking control of the AGV system, achieving the technical effect of improving task accuracy, driving safety and stability. The path optimization control system based on the AGV system includes: a first driving path receiving module 10, a buffer test area establishment module 20, a first target point acquisition module 30, a first deceleration test result generation module 40, a braking control parameter optimization module 50, and a braking optimization control module 60.

[0051] A first driving path receiving module 10 is used to connect to the AGV system to receive the first driving path of the first guide vehicle; a buffer test area establishment module 20 is used to extract multiple continuous target points according to the first driving path, and establish multiple buffer test areas for the multiple continuous target points according to a preset distance; a first target point acquisition module 30 is used to extract a first buffer test area from the multiple buffer test areas, and obtain the corresponding first target point; a first deceleration test result generation module 40 is used to control the first guide vehicle to travel to the first target point according to the first driving path, and when it is detected that the first guide vehicle enters the first buffer test area, a deceleration test is performed to generate a first deceleration test result; a braking control parameter optimization module 50 is used to optimize the braking control parameters for the first section between the first buffer test area and the first target point according to the first deceleration test result, and generate a first segmented braking optimization result; a braking optimization control module 60 is used to perform braking optimization control on the first section with the first segmented braking optimization result.

[0052] The specific configuration of the buffer test area establishment module 20 will be described in detail below. The buffer test area establishment module 20 may further include: obtaining multiple segmented paths with the multiple continuous target points as stop targets according to the first driving path; obtaining segmented load conditions and pre-braking speeds corresponding to the multiple segmented paths; inputting the segmented load conditions and the pre-braking speeds into a braking simulation model for braking simulation to generate braking distances corresponding to the multiple segmented paths, wherein the braking simulation model is trained based on historical braking data of the same road surface conditions and the same guide vehicle; amplifying the braking distance according to a preset tolerance constraint to generate a preset distance corresponding to the segmented path; and configuring the multiple buffer test areas on the multiple segmented paths according to the preset distances.

[0053] The specific configuration of the buffer test area establishment module 20 will be described in detail below. The buffer test area establishment module 20 may further include: configuring a preset deceleration test distance; using the preset deceleration test distance as the area length of the multiple buffer test areas, using the preset distance as the distance from the multiple buffer test areas to the multiple continuous target points, and configuring the multiple buffer test areas on the multiple segmented paths.

[0054] The specific configuration of the first deceleration test result generating module 40 will be described in detail below. The first deceleration test result generating module 40 may further include: establishing a buffer test sample constraint, wherein the buffer test sample constraint includes a first test sample constraint and a second test sample constraint, the first test sample constraint is that the deceleration threshold satisfies a first preset threshold, the second test sample constraint is that the deceleration threshold satisfies a second preset threshold, and the first preset threshold is greater than the second preset threshold; configuring deceleration test data according to the first test sample constraint and the second test sample constraint; inputting the deceleration test data into the controller of the first guide vehicle for deceleration test, and analyzing the deceleration control deviation to generate the first deceleration test result.

[0055] The specific configuration of the first deceleration test result generating module 40 will be described in detail below. The first deceleration test result generating module 40 may further include: when the first guide vehicle is detected to enter the first buffer test area, obtaining the first real-time speed of the first guide vehicle; taking the first real-time speed as a base, combining the first test sample constraint and the second test sample constraint to generate continuous deceleration phase data; generating the deceleration test data with the continuous deceleration phase data, wherein the deceleration test data includes two deceleration control nodes.

[0056] The specific configuration of the first deceleration test result generating module 40 will be described in detail below. The first deceleration test result generating module 40 may further include: collecting the smoothness characteristics of the wheels and the road surface of the first guide vehicle, and combining the segmented load conditions, performing deceleration modeling on the controller of the first guide vehicle to generate a first deceleration simulation model; inputting the deceleration test data into the first deceleration simulation model to perform deceleration simulation and generate a standard speed change sequence; inputting the deceleration test data into the controller of the first guide vehicle to perform a deceleration test, and recording the actual test speed change sequence; performing time and space alignment and comparison on the standard speed change sequence and the actual test speed change sequence, and generating speed deviations corresponding to multiple space-time nodes; generating the first deceleration test result with the speed deviations corresponding to the multiple space-time nodes.

[0057] The specific configuration of the braking control parameter optimization module 50 will be described in detail below. The braking control parameter optimization module 50 may further include: extracting the first pre-braking speed and the first braking point on the first road section; judging whether the deceleration control deviation meets the preset deviation threshold according to the first deceleration test result; if not, simulating the braking distance after correcting the first pre-braking speed according to the deceleration control deviation, optimizing the first braking point according to the prediction result, and generating the first segmented braking optimization result.

[0058] The path optimization control system based on the AGV system provided in the embodiment of the present invention can execute the path optimization control method based on the AGV system provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0059] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, any number of different modules may be used and run on the user terminal and / or server, and the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0060] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A path optimization control method based on an AGV system, characterized in that: include: Connecting to the AGV system to receive a first driving path of a first guide vehicle; Extracting a plurality of continuous target points according to the first driving path, and establishing a plurality of buffer test areas for the plurality of continuous target points according to a preset distance, specifically includes: Acquire, according to the first driving path, a plurality of segmented paths in which the plurality of continuous target points are respectively used as stop targets; Acquire segmented load conditions and pre-braking speeds corresponding to the plurality of segmented paths; Inputting the segmented load condition and the pre-braking speed into a braking simulation model to perform braking simulation, and generating braking distances corresponding to the multiple segmented paths, wherein the braking simulation model is trained based on historical braking data of the same road condition and the same guide vehicle; The braking distance is enlarged according to a preset tolerance constraint to generate a preset distance corresponding to the segmented path; configuring the plurality of buffer test areas on the plurality of segmented paths according to the preset distance; Extracting a first buffer test area from the plurality of buffer test areas, and acquiring a corresponding first target point; Control the first guide vehicle to travel toward the first target point according to the first driving path, and generate a first deceleration test result when detecting that the first guide vehicle enters the first buffer test area for a deceleration test; According to the first deceleration test result, a braking control parameter is optimized for a first road section between the first buffer test area and the first target point to generate a first segmented braking optimization result; The first section of road is subjected to braking optimization control based on the first segmented braking optimization result.

2. The path optimization control method based on the AGV system according to claim 1, characterized in that: Configuring the plurality of buffer test areas on the plurality of segmented paths according to the preset distance includes: Configure preset deceleration test distance; The preset deceleration test distance is used as the area length of the multiple buffer test areas, the preset distance is used as the distance from the multiple buffer test areas to the multiple continuous target points, and the multiple buffer test areas are configured on the multiple segmented paths.

3. The path optimization control method based on the AGV system according to claim 1, characterized in that: Controlling the first guide vehicle to travel toward the first target point according to the first driving path, and generating a first deceleration test result when detecting that the first guide vehicle enters the first buffer test area for a deceleration test, including: Establishing a buffer test sample constraint, wherein the buffer test sample constraint includes a first test sample constraint and a second test sample constraint, the first test sample constraint is that the deceleration threshold satisfies a first preset threshold, the second test sample constraint is that the deceleration threshold satisfies a second preset threshold, and the first preset threshold is greater than the second preset threshold; configuring deceleration test data according to the first test sample constraint and the second test sample constraint; The deceleration test data is input into the controller of the first lead vehicle to perform a deceleration test, and the deceleration control deviation is analyzed to generate the first deceleration test result.

4. The path optimization control method based on the AGV system according to claim 3, characterized in that: Configuring deceleration test data according to the first test sample constraint and the second test sample constraint includes: When detecting that the first guide vehicle enters the first buffer test area, obtaining a first real-time speed of the first guide vehicle; Taking the first real-time speed as a base, combining the first test sample constraint and the second test sample constraint to generate continuous deceleration phase data; The deceleration test data is generated using the continuous deceleration phase data, wherein the deceleration test data includes two deceleration control nodes.

5. The path optimization control method based on the AGV system according to claim 3, characterized in that: Inputting the deceleration test data into the controller of the first lead vehicle to perform a deceleration test, and analyzing the deceleration control deviation to generate the first deceleration test result, including: Collecting the smoothness characteristics of the wheels of the first guide vehicle and the road surface, and combining the segmented load conditions, performing deceleration modeling on the controller of the first guide vehicle to generate a first deceleration simulation model; Inputting the deceleration test data into the first deceleration simulation model to perform deceleration simulation and generate a standard speed change time sequence; Inputting the deceleration test data into the controller of the first guide vehicle to perform a deceleration test, and recording the actual test speed change sequence; Performing time and space alignment on the standard speed change sequence and the actual test speed change sequence, and then comparing them to generate speed deviations corresponding to a plurality of time and space nodes; The first deceleration test result is generated according to the speed deviations corresponding to the multiple space-time nodes.

6. The path optimization control method based on the AGV system according to claim 1, characterized in that: Optimizing the braking control parameters for the first road section between the first buffer test area and the first target point according to the first deceleration test result to generate a first segmented braking optimization result, including: Extracting a first pre-braking speed and a first braking point on the first road section; Determining whether the deceleration control deviation meets a preset deviation threshold according to the first deceleration test result; If not, the first pre-braking speed is corrected according to the deceleration control deviation, and then a braking distance simulation is performed, and the first braking point is optimized according to the prediction result to generate the first segmented braking optimization result.

7. The path optimization control system based on the AGV system is characterized by: The system is used to implement the path optimization control method based on the AGV system according to any one of claims 1 to 6, and the system includes: A first driving path receiving module, used to connect to the AGV system to receive a first driving path of a first guide vehicle; a buffer test area establishment module, configured to extract a plurality of continuous target points according to the first driving path, and establish a plurality of buffer test areas for the plurality of continuous target points according to a preset distance; A first target point acquisition module, used to extract a first buffer test area from the plurality of buffer test areas and acquire a corresponding first target point; A first deceleration test result generating module, configured to control the first guide vehicle to travel toward the first target point according to the first driving path, and generate a first deceleration test result when it is detected that the first guide vehicle enters the first buffer test area for a deceleration test; a braking control parameter optimization module, configured to optimize the braking control parameters for a first road section between the first buffer test area and the first target point according to the first deceleration test result, and generate a first segmented braking optimization result; A braking optimization control module is used to perform braking optimization control on the first road section based on the first segmented braking optimization result.

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