CN119148718B - Path optimization control method and system based on AGV system - Google Patents
Path optimization control method and system based on AGV system Download PDFInfo
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Abstract
The invention discloses a path optimization control method and a path optimization control system based on an AGV system, and relates to the technical field of AGV control, wherein the method comprises the steps of receiving a first travel path of a first guide vehicle; the method comprises the steps of establishing a plurality of buffer test areas for a plurality of continuous target points according to preset distances, extracting a first buffer test area, obtaining a corresponding first target point, carrying out deceleration test when a first guide vehicle is detected to enter the first buffer test area, generating a first deceleration test result, carrying out brake control parameter optimization, generating a first sectional brake optimization result, and carrying out brake optimization control on a first road segment. The technical problems that the existing AGV path optimization is based on fixed path planning and speed control, accurate control is difficult to carry out according to complex and changeable environments, and therefore the running instability and the safety of an AGV system are reduced are solved, accurate braking control of the AGV system is achieved, and the technical effects of improving task accuracy, running safety and stability are achieved.
Description
Technical Field
The application relates to the technical field related to AGV control, in particular to a path optimization control method and system based on an AGV system.
Background
Along with the rapid development of automation and intelligent technology, the Automatic Guided Vehicle (AGV) is widely applied in the fields of warehouse logistics, production and manufacturing and the like, and the AGV system not only can remarkably improve the production efficiency, but also can greatly reduce the labor cost, thereby being an important component of modern industrial automation. However, the operation efficiency and safety of an AGV system depend on the path optimization control technology to a great extent, in an Automatic Guided Vehicle (AGV) system, in situations where accurate speed control is required, such as approaching a target point, encountering an obstacle or emergency braking, the AGV often "rushes over" the target point when reaching the target point, which is mainly represented by unstable stopping of the AGV near the target point or reduced safety, resulting in exceeding a predetermined stopping position in front of or behind the target point, which not only affects the accuracy of a task, but also may cause delay of subsequent operations, and even damage to equipment or goods. Conventional AGV path planning is often based on a fixed path and fixed speed control, and this simple control method is very attractive when facing complex and variable industrial environments, and particularly when there are obstacles on the path, frequent start and stop are required, or accurate speed control is required, the conventional control method often cannot achieve the expected effect.
Therefore, in the related technology of the path optimization control of the AGV system at the present stage, the technical problems that the AGV running is unstable and the safety is reduced due to the fact that the accurate control is difficult to be performed according to complex and changeable environments based on fixed path planning and speed control exist.
Disclosure of Invention
The application solves the technical problems that the existing AGV path optimization is difficult to accurately control according to complex and changeable environments and further causes unstable running and reduced safety of the AGV, realizes accurate braking control of the AGV system, and achieves the technical effects of improving task accuracy, running safety and stability.
The application provides a path optimization control method based on an AGV system, which comprises the steps of connecting the AGV system to receive a first running path of a first guided vehicle, extracting a plurality of continuous target points according to the first running path, establishing a plurality of buffer test areas for the plurality of continuous target points according to preset distances, extracting a first buffer test area in the plurality of buffer test areas, acquiring corresponding first target points, controlling the first guided vehicle to run towards the first target points according to the first running path, performing a deceleration test when the first guided vehicle is detected to enter the first buffer test area, generating a first deceleration test result, performing brake control parameter optimization for a first path segment between the first buffer test area and the first target points according to the first deceleration test result, generating a first segmented brake optimization result, and performing brake optimization control for the first path segment according to the first segmented brake optimization result.
In a possible implementation manner, a plurality of continuous target points are extracted according to the first driving path, a plurality of buffer test areas are built for the plurality of continuous target points according to preset distances, the following processing is further carried out, a plurality of segmented paths taking the plurality of continuous target points as stopping targets are obtained according to the first driving path, segmented load conditions and pre-braking speeds corresponding to the plurality of segmented paths are obtained, the segmented load conditions and the pre-braking speeds are input into a braking simulation model to carry out braking simulation, braking distances corresponding to the plurality of segmented paths are generated, wherein the braking simulation model is trained based on historical braking data of the same road surface conditions and the same guide vehicle, the braking distances are amplified according to preset tolerance constraints, the preset distances corresponding to the segmented paths are generated, and the plurality of buffer test areas are configured on the plurality of segmented paths according to the preset distances.
In a possible implementation manner, the plurality of buffer test areas are configured on the plurality of segment paths according to the preset distance, and the following processing is further performed, wherein the preset deceleration test distance is configured, the preset deceleration test distance is used as the area length of the plurality of buffer test areas, the preset distance is used as the distance from the plurality of buffer test areas to the plurality of continuous target points, and the plurality of buffer test areas are configured on the plurality of segment paths.
In a possible implementation manner, the first guided vehicle is controlled to travel to the first target point according to the first travel path, when the first guided vehicle is detected to enter the first buffer test area for deceleration test, a first deceleration test result is generated, and further, a buffer test sample constraint is established, wherein the buffer test sample constraint comprises a first test sample constraint and a second test sample constraint, the first test sample constraint is that a deceleration threshold meets a first preset threshold, the second test sample constraint is that a deceleration threshold meets a second preset threshold, the first preset threshold is larger 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 a controller of the first guided vehicle for deceleration test, and a deceleration control deviation is analyzed to generate the first deceleration test result.
In a possible implementation manner, deceleration test data is configured according to the first test sample constraint and the second test sample constraint, and the following processing is further performed, wherein 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, continuous deceleration stage data is generated by taking the first real-time speed as a base number and combining the first test sample constraint and the second test sample constraint, and the deceleration test data is generated according to the continuous deceleration stage data, and the deceleration test data comprises two deceleration control nodes.
In a possible implementation manner, the deceleration test data are input into a controller of the first guide vehicle to conduct deceleration test, deceleration control deviation is analyzed to generate a first deceleration test result, the following processing is further carried out, the smoothness characteristics of wheels and road surfaces of the first guide vehicle are collected, the controller of the first guide vehicle is conducted to conduct deceleration modeling by combining segmented load conditions to generate a first deceleration simulation model, the deceleration test data are input into the first deceleration simulation model to conduct deceleration simulation to generate a standard speed change time sequence, the deceleration test data are input into the controller of the first guide vehicle to conduct deceleration test, an actual test speed change time sequence is recorded, time and space alignment is conducted on the standard speed change time sequence and the actual test speed change time sequence, speed deviations corresponding to a plurality of space-time nodes are generated, and the first deceleration test result is generated according to the speed deviations corresponding to the plurality of space-time nodes.
In a possible implementation manner, according to the first deceleration test result, brake control parameter optimization is performed on a first road segment between the first buffer test area and the first target point to generate a first segmented brake optimization result, and the following processing is further performed, namely, a first pre-brake speed and a first brake point location are extracted on the first road segment, whether the deceleration control deviation meets a preset deviation threshold value is judged according to the first deceleration test result, if not, the first pre-brake speed is corrected according to the deceleration control deviation, then brake distance simulation is performed, and according to a prediction result, first brake point location optimization is performed to generate the first segmented brake optimization result.
The application further provides a path optimization control system based on the AGV system, which comprises a first travel path receiving module, a buffer test area establishing module, a first target point obtaining module, a first deceleration test result generating module and a brake control parameter optimizing module, wherein the first travel path receiving module is used for being connected with the AGV system to receive a first travel path of a first guided vehicle, the buffer test area establishing module is used for extracting a plurality of continuous target points according to the first travel path and establishing a plurality of buffer test areas according to a preset distance, the first target point obtaining module is used for extracting a first buffer test area in the plurality of buffer test areas and obtaining a corresponding first target point, the first deceleration test result generating module is used for controlling the first guided vehicle to travel to the first target point according to the first travel path, and when the first guided vehicle is detected to enter the first buffer test area to conduct a deceleration test, a first deceleration test result is generated, the brake control parameter optimizing module is used for conducting brake control parameter optimization on a first road segment between the first buffer test area and the first target point according to the first deceleration test result, and the brake optimizing control module is used for conducting brake control on the first road segment according to the first deceleration test result.
The path optimization control method and system based on the AGV system are used for receiving a first driving path of a first guided vehicle, establishing a plurality of buffer test areas for a plurality of continuous target points according to preset distances, extracting the first buffer test areas, acquiring corresponding first target points, performing deceleration test when the first guided vehicle is detected to enter the first buffer test areas, generating a first deceleration test result, performing brake control parameter optimization, generating a first subsection brake optimization result, and performing brake optimization control on the first road section. The technical problems that the existing AGV path optimization is based on fixed path planning and speed control, accurate control is difficult to carry out according to complex and changeable environments, and therefore the running instability and the safety of an AGV system are reduced are solved, accurate braking control of the AGV system is achieved, and the technical effects of improving task accuracy, running safety and stability are achieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following will briefly describe the drawings of the embodiments of the present disclosure, in which flowcharts are used to illustrate operations performed by a system according to embodiments of the present disclosure. It should be understood that the preceding or following operations are not necessarily performed in order precisely. Rather, the various steps may be processed in reverse order or simultaneously, as desired. Also, other operations may be added to or removed from these processes.
FIG. 1 is a schematic flow chart of a path optimization control method based on an AGV system according to an embodiment of the present application;
fig. 2 is a schematic diagram of a path optimization control system based on an AGV system according to an embodiment of the present application.
Reference numerals illustrate the first travel path receiving module 10, the buffer test area establishing module 20, the first target point acquiring module 30, the first deceleration test result generating module 40, the brake control parameter optimizing module 50, and the brake optimizing control module 60.
Detailed Description
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail with reference to the accompanying drawings, and the described embodiments should not be construed as limiting the present application, and all other embodiments obtained by those skilled in the art without making any inventive effort are within the scope of the present application.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is to be 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, the term "first\second" being referred to merely as distinguishing between similar objects and not representing a particular ordering for the objects. The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or server that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly listed or inherent to such process, method, article, or apparatus, but may include other steps or modules that may not be expressly listed or inherent to such process, method, article, or apparatus, and unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used herein is for the purpose of describing embodiments of the application only.
The embodiment of the application provides a path optimization control method based on an AGV system, as shown in FIG. 1, comprising the following steps:
step S100, the connected AGV system receives a first travel path of a first guided vehicle.
Preferably, an automatic Guided VEHICLE SYSTEM (AGV) system refers to a material handling system based on an automation technology, which implements automatic handling and transportation of cargoes by using an automatic Guided vehicle (AGV, automated Guided Vehicle), generally includes an AGV vehicle, which is responsible for handling cargoes according to a preset path or instruction, and is designed and customized according to different application scenarios, such as a forklift type AGV for handling heavy cargoes, a drum type AGV for material distribution of a production line, etc., a navigation and positioning unit, which is required to accurately know the position and the driving direction of the AGV vehicle, is usually implemented by a navigation and positioning unit, including a magnetic stripe navigation, a laser navigation, an inertial navigation, a visual navigation, etc., to ensure that the AGV vehicle can stably and accurately drive under 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, implementing path planning, task allocation, traffic management, etc., and a communication and interaction unit, which is required to communicate and interact with other systems or devices, such as a programmable logic controller (may acquire and communicate with a warehouse system to acquire information of the goods to acquire and control the information of the system.
Preferably, connecting the AGV system to receive the first travel path of the first guided vehicle means that the AGV system has established a communication connection with a particular guided vehicle (possibly one of the AGV fleet), such as through a wireless network, a wired network, or other communication protocol, to ensure that the AGV system is able to receive and process data and information from the guided vehicle, specifically, the AGV system receives information from the guided vehicle regarding the first travel path, possibly including the start point, end point, intermediate point, type of path (e.g., straight line, curve, intersection, etc.), location of obstacles on the path, travel speed, braking point, and other factors that may affect the travel of the AGV, the first travel path being the travel path corresponding to the first guided vehicle, and based on the travel path information, a particular travel strategy may be planned, possibly including determining parameters such as optimal travel speed, acceleration, steering angle, etc., and how to avoid or re-plan the path should be performed when encountering an obstacle.
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 a preset distance.
Preferably, the received first travel path is parsed, a plurality of continuous target points on the travel path are extracted according to characteristics and actual requirements of the path, the target points are usually key positions on the path, such as turning points, intersections, front obstacles and the like, then a plurality of buffer test areas are established for the plurality of continuous target points according to preset distances, specifically, after the plurality of continuous target points are extracted, the AGV system establishes a certain range of buffer test areas around each target point according to preset distance parameters, the preset distance is usually comprehensively determined according to factors such as performance parameters (such as braking distance, acceleration and the like) of the AGV, path characteristics (such as curvature, gradient and the like) and safety requirements and the like, the buffer test areas are round or oval areas (can also be in other shapes (such as rectangles and the like and are dependent on application scenes and path characteristics) with the preset distances as well) with the preset distances as radius, and the areas are used for performing experiments such as speed reduction test and brake control parameter optimization when the AGV travels nearby the target points so as to ensure that the AGV can safely and stably reach the target points. The main function of the buffer test area is to provide a safe and controllable test environment for evaluating and optimizing the running performance and braking control parameters of the AGV when approaching to the target point, and the AGV system can more accurately master the running characteristics of the AGV under different conditions by carrying out deceleration test and braking control parameter optimization in the areas, so that the fine control and optimization of the running process of the AGV are realized.
In a possible implementation manner, the step S200 further includes a step S210 of acquiring a plurality of segment paths with the plurality of continuous target points as stop targets according to the first driving path, a step S220 of acquiring segment load conditions and pre-braking speeds corresponding to the plurality of segment paths, a step S230 of inputting the segment load conditions and the pre-braking speeds into a braking simulation model to perform braking simulation to generate braking distances corresponding to the plurality of segment paths, wherein the braking simulation model is trained based on historical braking data of the same road surface conditions and the same guide vehicle, a step S240 of amplifying the braking distances according to preset tolerance constraints to generate preset distances corresponding to the segment paths, and a step S250 of configuring the plurality of buffer test areas on the plurality of segment paths according to the preset distances.
Preferably, the first travel path includes a plurality of continuous target points, the complete travel path is divided into a plurality of segmented paths, the end point of each segmented path is a target stop point, so as to more precisely control the travel and braking of the AGV, a plurality of segmented paths with the target points as stop targets are obtained, the load condition and the speed of the AGV can change during the travel, the change can directly affect the braking performance of the AGV, for each segmented path, the corresponding load condition and the speed before braking are collected or calculated, the load condition can include the weight, the distribution and the like of the goods borne by the AGV, the speed before braking is the speed of the AGV when entering the segmented path, then a braking simulation model is used for simulation, the braking distance of the AGV under different load and speed conditions is predicted, in particular, the braking simulation model is trained based on the same road condition and the historical braking data of the same guide vehicle, the simulated braking process can be calculated according to the input load condition and the speed before braking speed.
In actual running, as various uncertainty factors (such as road surface condition change, AGV performance fluctuation and the like) may be longer than a simulation result, a preset tolerance constraint, namely a safety margin, is set, the braking distance is amplified according to the preset tolerance constraint, the preset distance corresponding to each segmented path is obtained, the preset distance is longer than the braking simulation result, so that the AGV has enough safety distance to brake in actual running, and finally a buffer test area is configured according to the preset distance, namely an obvious mark or obstacle (such as a deceleration strip, a warning lamp and the like) is set in the preset distance range of each segmented path, so that the AGV is reminded and guided to carry out a deceleration test, and finally a plurality of buffer test areas are obtained for carrying out the deceleration test before the AGV actually runs, so that the braking performance of the AGV is ensured to meet the requirement, and the running efficiency is improved.
In a possible implementation manner, the step S250 further includes a step S251 of configuring a preset deceleration test distance, and a step S252 of configuring the plurality of buffer test areas on the plurality of segment paths with the preset deceleration test distance as an area length of the plurality of buffer test areas and the preset distance as a distance from the plurality of buffer test areas to the plurality of continuous target points.
Preferably, the preset deceleration test distance is determined based on factors such as braking performance, road surface condition and load condition of the AGV, the preset deceleration test distance should be long enough to ensure that the AGV can safely reduce the speed in the deceleration test process, meanwhile, the AGV cannot be overlong, so that a driving path is not wasted, a buffer test area is configured subsequently, then the configured preset deceleration test distance is used as the area length of each buffer test area, namely, each buffer test area has the same deceleration test length and is used for deceleration test, the preset distance is used as the distance from each buffer test area to the corresponding continuous target point of the AGV, namely, the AGV needs to travel the preset distance from the starting point of the buffer test area to reach the target point, the specific distance from each buffer test area to the corresponding target point is determined, finally, the corresponding buffer test areas are configured on each section path according to the preset deceleration test distance of each section path, the length of each buffer test area and the distance from each buffer test area to the target point, and the corresponding buffer test areas should be located on the driving path, and the distance is a certain preset distance is used to ensure that the AGV has enough space to stop before approaching the target point to decelerate and can stop the AGV to reach the target point when the AGV is stopped smoothly.
Step S300, extracting a first buffer test area from the plurality of buffer test areas, and acquiring a corresponding first target point.
Preferably, a buffer test area to be processed is selected and extracted from a plurality of buffer test areas at random to serve as a first buffer test area, and the position and the range of the first buffer test area are accurately identified, wherein the position and the range are usually set in a path planning stage, a round or oval area (or other shapes) with a target point as a center and a preset distance as a radius are used as centers, after the first buffer area is extracted, a first target point corresponding to the area is further identified and acquired, the first target point is usually the center point of the buffer test area and is also a key position which an AGV needs to reach in the driving process, and besides the position information of the target point, the AGV system also acquires other information related to the target point, such as a path type, an obstacle position, a speed limit and the like, so that the follow-up driving control and optimization are facilitated. After acquiring the information of the first target point, the AGV system may prepare subsequent running control and optimization steps, such as planning a running path according to the position of the target point and related information, setting running parameters (such as speed, acceleration, etc.), and preparing to perform experiments such as deceleration test and brake control parameter optimization.
And step S400, controlling the first guided vehicle to travel towards the first target point according to the first travel path, and generating a first deceleration test result when detecting that the first guided vehicle enters the first buffer test area for deceleration test.
Preferably, the AGV system controls the first guided vehicle (i.e., the specific AVG guided vehicle) to travel along the preset first travel path toward the first target point, during the travel, the AGV system monitors the position and speed of the guided vehicle in real time to ensure that the guided vehicle can travel accurately along the path, usually uses advanced navigation and positioning technologies, such as laser navigation, visual navigation, etc., to implement accurate travel control, and ensure that the guided vehicle maintains a stable travel state in a complex and variable environment, when the first guided vehicle approaches the first buffer test area, the AGV system recognizes whether the guided vehicle has entered the first buffer test area through a sensor or other detection means, ensures that the guided vehicle can perform a test in a safe environment, and when the guided vehicle is detected to enter the first buffer test area, immediately triggers a deceleration test program, and controls the guided vehicle to decelerate according to a preset deceleration strategy to evaluate the braking performance and stability of the guided vehicle when approaching the target point, during the deceleration test, collects key data, such as the speed, acceleration, position, etc., of the guided vehicle in real time, and analyzes and processes these data to generate a first deceleration test result, usually including whether the first deceleration test result, the braking performance, the key performance, the distance, and the stability, etc., exist in the critical indicators.
In a possible implementation manner, step S400 further includes step S410 of establishing a buffer test sample constraint, where the buffer test sample constraint includes a first test sample constraint and a second test sample constraint, the first test sample constraint is that a deceleration threshold meets a first preset threshold, the second test sample constraint is that a deceleration threshold meets a second preset threshold, the first preset threshold is greater than the second preset threshold, step S420 of configuring deceleration test data according to the first test sample constraint and the second test sample constraint, step S430 of inputting the deceleration test data into a controller of the first guide vehicle for deceleration test, and analyzing a deceleration control deviation to generate the first deceleration test result.
Preferably, during deceleration testing of an AGV (automated guided vehicle), a buffer test sample constraint (comprising 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 is that the deceleration threshold meets a first preset threshold, wherein the deceleration threshold is the minimum deceleration rate that the AGV needs to achieve during the deceleration test, the first preset threshold is a relatively high value that requires the AGV to rapidly decelerate during the test for evaluating the braking performance of the AGV in an emergency, the second test sample constraint is that the deceleration threshold meets a second preset threshold, different from the first test sample constraint, that is a relatively low value that requires the AGV to smoothly decelerate during the test for evaluating the braking stability of the AGV during normal running, and the first preset threshold is larger than the second preset threshold, meaning that the first test sample constraint requires a higher braking performance, and the second test sample constraint is more focused on the braking stability, and the second test sample constraint is different from the first test sample constraint.
Preferably, the deceleration test data are configured according to the first test sample constraint and the second test sample constraint, including configuring parameters such as initial speed, target speed, deceleration time and deceleration distance of the AGV, so as to ensure that the test process meets constraint requirements, then the configured deceleration test data are input into a controller of the first guide vehicle for deceleration test, the AGV can decelerate according to the input deceleration test data in the test process, the deceleration process of the AGV is recorded, including parameters such as deceleration rate, deceleration time and deceleration distance, after the test is completed, the deceleration process of the AGV is analyzed, including calculating deviation between actual deceleration rate and expected deceleration rate of the AGV, and evaluating stability and accuracy of the AGV in the deceleration process, and a first deceleration test result is generated according to the analyzed result, including the performance of the AGV in the deceleration test, the magnitude of deceleration control deviation, and whether the information such as buffering test sample constraint is met, so as to more comprehensively evaluate the braking performance and stability of the AGV.
In a possible implementation manner, step S420 further includes step S421, when it is detected that the first guided vehicle enters the first buffer test area, obtaining a first real-time speed of the first guided vehicle, step S422, generating continuous deceleration stage data by combining the first test sample constraint and the second test sample constraint with the first real-time speed as a base, and step S423, generating the deceleration test data with the continuous deceleration stage data, where the deceleration test data includes two deceleration control nodes.
Preferably, the AGV (automated guided vehicle) continuously monitors the position of the AGV during the running process, when the AGV is detected to enter a preset first buffer test area, the current speed of the AGV, namely, the first real-time speed is immediately acquired, then the first real-time speed is taken as a base, the first test sample constraint and the second test sample constraint are combined to generate data of a continuous deceleration stage, which describes the process of gradually decelerating the AGV from the current speed to a target speed, specifically, the first test sample constraint requires the AGV to achieve a higher deceleration rate (namely, a faster deceleration speed change) during the deceleration process, the AGV is used for evaluating the braking performance of the AGV under the emergency condition, the second test sample constraint requires the AGV to be stably decelerated during the deceleration process, the excessive speed fluctuation is avoided, the AGV is used for evaluating the braking stability during the normal running process, the AGV is further generated to meet the emergency braking requirement, the data of the continuous deceleration stage is also ensured to be stably decelerated, the AGV is finally, the complete deceleration test data is generated according to the data of the continuous deceleration stage, which comprises two key deceleration control nodes, the first deceleration control nodes mark the moment and the first deceleration control node is used for marking the moment of deceleration and the moment and the first deceleration control node is the key speed of the deceleration control of the AGV, and the deceleration performance is required to reach the real-time and the speed of the speed is the speed of the first deceleration control and the speed. Through the two deceleration control nodes, the speed change of the AGV in the deceleration test process can be completely described, so that the braking performance and the stability of the AGV can be evaluated.
In a possible implementation manner, step S430 further includes step S431 of collecting smoothness characteristics of wheels and a road surface of the first guide vehicle, performing deceleration modeling on a controller of the first guide vehicle in combination with a sectional load condition to generate a first deceleration simulation model, step S432 of inputting the deceleration test data into the first deceleration simulation model to perform deceleration simulation to generate a standard speed change time sequence, step S433 of inputting the deceleration test data into the controller of the first guide vehicle to perform deceleration test and recording an actual test speed change time sequence, step S434 of comparing the standard speed change time sequence with the actual test speed change time sequence after time and space alignment to generate speed deviations corresponding to a plurality of space-time nodes, and step S435 of generating the first deceleration test result according to the speed deviations corresponding to the plurality of space-time nodes.
Preferably, the smoothness characteristics of the wheels of the first guide vehicle and the current running road surface are collected, wherein the smoothness characteristics comprise friction coefficients between the wheels and the road surface, the unevenness of the road surface and the like, meanwhile, the current load conditions of the AGV, such as the weight, the distribution and the like of the load, are considered, the braking performance and the deceleration effect of the AGV are influenced, then the controller of the first guide vehicle is subjected to deceleration modeling based on the collected smoothness characteristics and the sectional load conditions, the deceleration process of the AGV under different road surfaces and under different load conditions is simulated by the model, and a first deceleration simulation model is generated; the method comprises inputting the generated deceleration test data (such as initial speed, target speed, deceleration time, etc. of AGVs) into a first deceleration simulation model, simulating the deceleration process of AGVs according to the input deceleration test data and a preset algorithm, generating a standard speed change time sequence describing the speed change process of AGVs under ideal conditions (i.e. model prediction conditions), inputting the deceleration test data into an actual controller of a first guide vehicle, performing deceleration test according to the instructions of the controller by the AGVs, recording the speed change of the AGVs in real time to generate an actual test speed change time sequence, then performing time and space alignment on the standard speed change time sequence and the actual test speed change time sequence, namely finding corresponding time points and space positions in the two time sequences, accurately comparing the standard speed change time sequence and the actual test speed change time sequence, calculating the deviation between the standard speed and the actual speed on each space-time node, reflecting the difference between the actual speed change process and the model prediction, summarizing the speed deviation on all space-time nodes, and generating a complete speed deviation data set, and further generating a first deceleration test result, wherein the first deceleration test result comprises information such as the performance of the AGV in a deceleration test, the size and the distribution of the speed deviation and the like. From this information, the braking performance and deceleration stability of the AGV, as well as the accuracy of the model predictions, can be evaluated.
And step S500, performing brake control parameter optimization on a first road segment between the first buffer test area and the first target point according to the first deceleration test result, and generating a first segmented brake optimization result.
Preferably, according to a first deceleration test result (including speed change, braking distance, acceleration, etc. of the AGV in the first buffer test area), a first road segment between the first buffer test area and the first target point is subjected to braking control parameter optimization, that is, a braking parameter combination most suitable for the road segment is found, so as to improve running safety and efficiency of the AGV in the road segment, specifically, collected data are analyzed, problems and defects existing in running of the AGV under the current braking control parameter are found, for example, problems of overlong braking distance, unstable acceleration change, etc. may be found, and based on the data analysis result, the braking control parameter is adjusted and optimized, which may include parameters such as response time of a brake, magnitude of braking force, shape of a braking curve, etc. so that braking performance of the AGV on the first road segment is more stable and efficient, and after the braking control parameter is adjusted, deceleration test is required again to verify the optimization effect. The effectiveness of the optimization measures can be evaluated by comparing test results before and after optimization, and a first segmented brake optimization result is finally generated, wherein the first segmented brake optimization result generally comprises an optimized brake control parameter combination, performance comparison data before and after optimization and the like, and important support is provided for subsequent AGV system optimization decisions, for example, the running strategy of the AGV can be adjusted based on the result, so that the running performance and stability of the AGV on a specific road section are further improved.
In a possible implementation manner, the step S500 further includes a step S510 of extracting a first pre-braking speed and a first braking point location at the first road segment, a step S520 of judging whether a deceleration control deviation meets a preset deviation threshold according to the first deceleration test result, and a step S530 of performing simulation of a braking distance after correcting the first pre-braking speed according to the deceleration control deviation if not, performing optimization of the first braking point location according to a prediction result, and generating the first segmented braking optimization result.
Preferably, the speed of the AGV (automatic guided vehicle) immediately before braking is recorded in the first path, that is, the speed of the AGV before braking is recorded, and the position of the AGV before braking is recorded, that is, the first braking point, which determines when the AGV starts to decelerate, then determines whether the deceleration control deviation meets a preset deviation threshold according to the first deceleration test result, specifically, analyzes the deceleration control deviation in the first deceleration test result, compares the deceleration control deviation with the preset deviation threshold, if the deceleration control deviation is smaller than or equal to the preset deviation threshold, it is indicated that the braking performance of the AGV meets the requirement, no further optimization is required, if the deceleration control deviation is greater than the preset deviation threshold, then an optimization measure is required to be adopted, the speed of the AGV before braking is corrected according to the deceleration control deviation, so that the speed of the AGV before braking is closer to the expected braking speed, and after correction, the simulation of the braking distance is performed, that is, factors such as the current speed, braking performance, road surface condition of the point are considered, the braking distance of the AGV under different speeds is predicted, and the simulation result of the braking distance is optimized, if the deceleration control deviation is less than the preset deviation threshold, if the deceleration control deviation is smaller than or equal to the preset deviation threshold, the deceleration control deviation is greater than the preset, the first braking control deviation is calculated, the first braking speed is optimized, if the speed is greater than a proper, and the speed of the AGV is more stable and the speed is ensured to be more stable, and the actual braking speed is ensured to be ahead, and the speed is better and the speed is better and ahead and the speed is better and stable.
And S600, performing brake optimization control on the first road segment according to the first segmented brake optimization result.
Preferably, the first sectional braking optimization result obtained through testing and analysis is applied to the braking control process of the first road section to achieve better running performance and higher safety, specifically, according to the first sectional braking optimization result, braking control parameters of the AGV during running of the first road section are adjusted, such as response time of a brake, magnitude of braking force, speed threshold value of braking start and end and the like, the adjusted braking control parameters are input into a control system of the AGV, braking control can be conducted according to new parameters when the AGV runs to the first road section, in the running process of the AGV, running states of the AGV, including speed, acceleration, position and the like, are detected in real time through a sensor and a monitoring system, so that the AGV can run according to an expected braking control strategy, braking distance, braking stability, running efficiency and the like are evaluated, the effect of optimal control is verified, according to the result of performance evaluation, if running performance of the AGV is still to be improved, the braking control parameters can be further adjusted, optimal control of the new wheels is conducted, and the running performance of the AGV on a specific road section and the safety can be remarkably improved through fine adjustment and optimization of the braking control parameters.
In the above, the path optimization control method based on the AGV system according to the embodiment of the present invention is described in detail with reference to fig. 1. Next, a path optimization control system based on an AGV system according to an embodiment of the present invention will be described with reference to fig. 2.
According to the path optimization control system based on the AGV system, which is disclosed by the embodiment of the invention, the technical problems that the AGV is unstable in running and the safety is reduced due to the fact that the accurate control is difficult to be performed according to complex and changeable environments due to the fact that the fixed path planning and the speed control exist in the conventional AGV path optimization are solved, the accurate braking control of the AGV system is realized, and the technical effects of improving the accuracy of tasks, the running safety and the stability are achieved. The path optimization control system based on the AGV system comprises a first travel path receiving module 10, a buffer test area establishing module 20, a first target point obtaining module 30, a first deceleration test result generating module 40, a brake control parameter optimizing module 50 and a brake optimizing control module 60.
The system comprises a first travel path receiving module 10 for connecting an AGV system to receive a first travel path of a first guided vehicle, a buffer test area establishing module 20 for extracting a plurality of continuous target points according to the first travel path and establishing a plurality of buffer test areas for the plurality of continuous target points according to a preset distance, a first target point obtaining module 30 for extracting a first buffer test area in the plurality of buffer test areas and obtaining a corresponding first target point, a first deceleration test result generating module 40 for controlling the first guided vehicle to travel to the first target point according to the first travel path, when the first guided vehicle is detected to enter the first buffer test area for deceleration test, a first deceleration test result is generated, a brake control parameter optimizing module 50 for performing brake control parameter optimization for a first road segment between the first buffer test area and the first target point according to the first deceleration test result, a brake optimizing control module 60 for performing brake optimizing control for the first road segment by the first segmented brake optimizing result.
Next, the specific configuration of the buffer test area creation module 20 will be described in detail. The buffer test area establishing module 20 may further include obtaining a plurality of segment paths with the plurality of continuous target points as stop targets according to the first driving path, obtaining segment load conditions and pre-braking speeds corresponding to the plurality of segment paths, inputting the segment load conditions and the pre-braking speeds into a braking simulation model to perform braking simulation, and generating braking distances corresponding to the plurality of segment paths, wherein the braking simulation model trains based on historical braking data of the same road surface conditions and the same guide vehicle, amplifies the braking distances according to preset tolerance constraints, generates preset distances corresponding to the segment paths, and configures the plurality of buffer test areas on the plurality of segment paths according to the preset distances.
Next, the specific configuration of the buffer test area creation module 20 will be described in further detail. The buffer test region establishing module 20 may further include configuring a preset deceleration test distance, and configuring the plurality of buffer test regions at the plurality of segment paths with the preset deceleration test distance as a region length of the plurality of buffer test regions and the preset distance as a distance from the plurality of buffer test regions to the plurality of continuous target points.
Next, the specific configuration of the first deceleration test result generation module 40 will be described in detail. The first deceleration test result generation module 40 may further include establishing a buffer test sample constraint, where the buffer test sample constraint includes a first test sample constraint and a second test sample constraint, the first test sample constraint is that a deceleration threshold meets a first preset threshold, the second test sample constraint is that a deceleration threshold meets a second preset threshold, 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 a controller of the first guide vehicle to perform a deceleration test, and a deceleration control deviation is analyzed to generate the first deceleration test result.
Next, the specific configuration of the first deceleration test result generation module 40 will be described in further detail. The first deceleration test result generating module 40 may further include obtaining a first real-time speed of the first guided vehicle when the first guided vehicle is detected to enter the first buffer test area, generating continuous deceleration stage data with the first test sample constraint and the second test sample constraint based on the first real-time speed, and generating the deceleration test data with the continuous deceleration stage data, wherein the deceleration test data includes two deceleration control nodes.
Next, the specific configuration of the first deceleration test result generation module 40 will be described in further detail. The first deceleration test result generating module 40 may further include collecting smoothness characteristics of wheels and a road surface of the first guide vehicle, performing deceleration modeling on a controller of the first guide vehicle in combination with a sectional load condition to generate a first deceleration simulation model, inputting deceleration test data into the first deceleration simulation model to perform deceleration simulation to generate a standard speed change time sequence, inputting the deceleration test data into the controller of the first guide vehicle to perform deceleration test, recording an actual test speed change time sequence, comparing the standard speed change time sequence with the actual test speed change time sequence after time and space alignment to generate speed deviations corresponding to a plurality of space-time nodes, and generating the first deceleration test result according to the speed deviations corresponding to the plurality of space-time nodes.
Next, the specific configuration of the brake control parameter optimization module 50 will be described in detail. The brake control parameter optimization module 50 may further include extracting a first pre-brake speed and a first brake point location at the first road segment, determining whether a deceleration control deviation meets a preset deviation threshold according to the first deceleration test result, if not, performing simulation of a brake distance after correcting the first pre-brake speed according to the deceleration control deviation, performing optimization of the first brake point location according to a prediction result, and generating the first segmented brake optimization result.
The path optimization control system based on the AGV system provided by the embodiment of the invention can execute the path optimization control method based on the AGV system provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Although the present application makes various references to certain modules in a system according to an embodiment of the present application, any number of different modules may be used and run on a user terminal and/or a server, and each unit and module included are merely divided according to functional logic, but are not limited to the above-described division, so long as the corresponding functions can be implemented, and in addition, specific names of each functional unit are only for convenience of distinguishing from each other, and are not intended to limit the scope of protection of the present application.
The above embodiments do not limit the scope of the present application. It will be apparent to those skilled in the art that various modifications, combinations, and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of the present application.
Claims (7)
1. The path optimization control method based on the AGV system is characterized by comprising the following steps:
connecting the AGV system to receive a first travel path of the first guided 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, wherein the method specifically comprises the following steps:
acquiring a plurality of segmented paths taking the continuous target points as stopping targets according to the first driving path;
acquiring segment load conditions and pre-braking speeds corresponding to the segment paths;
Inputting the segmented load conditions and the pre-braking speed into a braking simulation model to perform braking simulation, and generating braking distances corresponding to the segmented paths, wherein the braking simulation model is trained based on the same road surface conditions and historical braking data of the same guide vehicle;
Amplifying the braking distance 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;
controlling the first guided vehicle to travel towards the first target point according to the first travel path, and generating a first deceleration test result when detecting that the first guided vehicle enters the first buffer test area for deceleration test;
Performing brake control parameter optimization on a first road segment between the first buffer test area and the first target point according to the first deceleration test result to generate a first segmented brake optimization result;
and carrying out brake optimization control on the first road segment according to the first sectional brake optimization result.
2. The AGV system-based path optimization control method according to claim 1, wherein configuring the plurality of buffer test areas at the plurality of segment paths according to the preset distance comprises:
configuring a preset deceleration test distance;
And taking the preset deceleration test distance as the area length of the plurality of buffer test areas, taking the preset distance as the distance from the plurality of buffer test areas to the plurality of continuous target points, and configuring the plurality of buffer test areas on the plurality of segmented paths.
3. The method for optimizing and controlling a path based on an AGV system according to claim 1, wherein controlling the first guided vehicle to travel toward the first target point according to the first travel path, when detecting that the first guided vehicle enters the first buffer test area for deceleration test, generating a first deceleration test result includes:
establishing a buffer test sample constraint, wherein the buffer test sample constraint comprises a first test sample constraint and a second test sample constraint, the first test sample constraint is that a deceleration threshold meets a first preset threshold, the second test sample constraint is that the deceleration threshold meets a second preset threshold, and the first preset threshold is larger than the second preset threshold;
configuring deceleration test data according to the first test sample constraint and the second test sample constraint;
And inputting the deceleration test data into a controller of the first guide vehicle for deceleration test, analyzing deceleration control deviation, and generating a first deceleration test result.
4. The AGV system based path optimization control method according to claim 3, wherein configuring deceleration test data according to the first test specimen constraint and the second test specimen constraint comprises:
When the first guide vehicle is detected to enter the first buffer test area, acquiring a first real-time speed of the first guide vehicle;
generating continuous deceleration stage data by combining the first test sample constraint and the second test sample constraint with the first real-time speed as a base;
And generating the deceleration test data according to the continuous deceleration stage data, wherein the deceleration test data comprises two deceleration control nodes.
5. The method of path optimization control based on an AGV system according to claim 3, wherein inputting the deceleration test data into the controller of the first guided vehicle for deceleration testing and analyzing a deceleration control deviation to generate the first deceleration test result comprises:
Acquiring smoothness characteristics of wheels of the first guide vehicle and a road surface, and carrying out deceleration modeling on a controller of the first guide vehicle by combining sectional load conditions to generate a first deceleration simulation model;
inputting the deceleration test data into the first deceleration simulation model to perform deceleration simulation, and generating a standard speed change time sequence;
inputting the deceleration test data into a controller of the first guide vehicle for deceleration test, and recording the actual test speed change time sequence;
comparing the standard speed change time sequence with the actual test speed change time sequence after time and space alignment, and generating speed deviations corresponding to a plurality of space-time nodes;
and generating the first deceleration test result by using the speed deviation corresponding to the space-time nodes.
6. The AGV system-based path optimization control method according to claim 1, wherein performing brake control parameter optimization for a first path segment between the first buffer test area and the first target point according to the first deceleration test result, generating a first segmented brake optimization result includes:
extracting a first pre-braking speed and a first braking point position from the first road segment;
judging whether the deceleration control deviation meets a preset deviation threshold according to the first deceleration test result;
if not, correcting the speed before the first braking according to the deceleration control deviation, then simulating the braking distance, and optimizing the first braking point position according to the prediction result to generate the first sectional braking optimization result.
7. A path optimization control system based on an AGV system, wherein the system is configured to implement the path optimization control method based on an AGV system according to any one of claims 1 to 6, the system comprising:
The first travel path receiving module is used for connecting the AGV system to receive a first travel path of the first guide vehicle;
the buffer test area establishing module is used for 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;
The first target point acquisition module is used for extracting a first buffer test area from the plurality of buffer test areas and acquiring a corresponding first target point;
The first deceleration test result generation module is used for controlling the first guided vehicle to travel towards the first target point according to the first travel path, and generating a first deceleration test result when detecting that the first guided vehicle enters the first buffer test area for deceleration test;
The brake control parameter optimization module is used for performing brake control parameter optimization on a first road segment between the first buffer test area and the first target point according to the first deceleration test result to generate a first segmented brake optimization result;
And the brake optimization control module is used for carrying out brake optimization control on the first road segment according to the first segmented brake optimization result.
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