CN118092457B - Storage AGV commodity circulation dolly operation track control system - Google Patents
Storage AGV commodity circulation dolly operation track control system Download PDFInfo
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Abstract
The invention relates to the field of automatic control, in particular to a running track control system of a storage AGV logistics trolley, which comprises a digital map building module, a road planning module, a road surface condition acquisition module, a motion control module, an obstacle avoidance analysis module, an electric quantity supplementing module and a management database.
Description
Technical Field
The invention relates to the field of automatic control, in particular to a control system for a running track of a storage AGV logistics trolley.
Background
The AGVs are named as automatic guided vehicles, are unmanned automatic delivery vehicles and are used for carrying out automatic transportation and carrying work in places such as factories, warehouses and hospitals, the AGVs are generally provided with various sensors and navigation equipment, can independently move in a work place according to preset paths and behavior rules and complete specified tasks, the AGVs can be custom designed according to the layout and requirements of the work place, common types comprise forklift AGVs, carrier AGVs, trailing AGVs and the like, the application range of the AGVs comprises but is not limited to the fields of raw material delivery, semi-finished product transportation, warehouse management, production line material replenishment and the like, and along with the development of logistics industry and the progress of automation technology, the warehouse AGV logistics trolley is widely applied in the warehouse logistics field and becomes one of important tools for improving the production efficiency and the intelligent level.
According to the technical scheme disclosed by China patent publication with the patent name of 202311356524.X, the vision sensor is used for acquiring environmental data of a warehouse area, a three-dimensional map of the environment of the warehouse area is constructed, specific information of cargoes and position and outline information of obstacles are acquired by using a convolutional neural network identification model, cargoes in each cargo set are subjected to path planning according to priority of the cargo set, a local path is generated, then the local paths are combined into a global path, the operation of the AGV trolley is controlled on the global path, if the path and the obstacles possibly collide, the path is corrected to avoid the obstacles, automation and intellectualization of warehouse operation are realized, labor cost is reduced, operation efficiency is improved, higher precision and convenience are brought to warehouse logistics management, and the following defects are still caused, namely: 1. according to the scheme, only the obstacles in the driving path are monitored, but the road condition is not analyzed, if sundries, pits or other obstacles exist on the road surface, the AGV trolley can be blocked or damaged, so that the carrying task cannot be normally completed, and even accidents occur.
2. According to the scheme, the obstacle in the path is monitored in real time to correct the path to avoid the obstacle, but the gesture parameters during obstacle avoidance are not involved in detection, the obstacle avoidance safety cannot be analyzed, so that data during obstacle avoidance of the same obstacle by a subsequent logistics trolley are corrected, the vehicle is possibly in an unstable state, the same obstacle is encountered again, collision cannot be effectively avoided, and the operation efficiency and the safety of the system are affected.
Disclosure of Invention
In order to overcome the defects in the background art, the embodiment of the invention provides a storage AGV logistics trolley operation track control system which can effectively solve the problems related to the background art.
The aim of the invention can be achieved by the following technical scheme: the invention provides a storage AGV logistics trolley operation track control system, which comprises: the digital map construction module is used for acquiring images of all subareas of the storage area through the camera, constructing a digital map by taking the images as the storage area, and acquiring the position information of all the storages and all the charging piles.
And the road planning module is used for acquiring a transportation list of the logistics trolley and planning an optimal driving path for the logistics trolley by combining the position information of each warehouse.
The road surface condition acquisition module is used for acquiring images of the road surfaces of all road sections of the logistics trolley through the built-in cameras, and further analyzing and obtaining the cracking degree and the sinking degree of the road surfaces of all road sections.
And the motion control module is used for analyzing the road surface flatness of the road surface of the road section according to the cracking degree and the dent degree of the road surface of the road section of the road, and further regulating and controlling the speed of each road section of the logistics trolley.
The obstacle avoidance module is used for detecting obstacles in the driving process of the logistics trolley, so as to control the logistics trolley to avoid the obstacle, and simultaneously detect the gesture data of the logistics trolley during obstacle avoidance, wherein the gesture data of the trolley comprise the distance to the obstacles, the steering angle and the wheel pressure when the obstacle avoidance function is executed.
The obstacle avoidance analysis module is used for analyzing and obtaining the obstacle avoidance safety of the logistics trolley according to the gesture data of the logistics trolley, and further regulating and controlling the gesture data of the subsequent logistics trolley when the logistics trolley avoids the same obstacle.
And the electric quantity supplementing module is used for analyzing the residual electric quantity of the logistics trolley to obtain the predicted endurance mileage of the logistics trolley, and further supplementing the electric quantity of the logistics trolley by combining the position information of each charging pile.
And the management database is used for storing a transportation list of the logistics trolley, and the corresponding logistics vehicle speed and ultrasonic unit speed of the road surface flatness range.
Preferably, the specific analysis method of the digital map construction module is as follows: dividing the storage area into a plurality of subareas with equal areas, acquiring images of the subareas through cameras in the storage area, recording the images as images of the subareas in the storage area, constructing a digital map for the storage area through the images of the subareas in the storage area, and simultaneously acquiring and marking the position information of the storage and the charging piles from the digital map of the storage area.
Preferably, the specific analysis process of the road planning module is as follows: the method comprises the steps of firstly, reading a transportation list of a logistics trolley and the types of goods stored in each warehouse from a management database, obtaining various goods required to be transported by the logistics trolley from the transportation list of the logistics trolley, matching the goods with the types of goods stored in each warehouse to obtain the storage warehouse of the various goods required to be transported by the logistics trolley, marking the storage warehouse as each to-be-loaded warehouse, reading the position information of each to-be-loaded warehouse from a storage area digital map, positioning the position of the logistics trolley, respectively obtaining the distance from the logistics trolley to each to-be-loaded warehouse, marking the distance from the logistics trolley to each to-be-loaded warehouse, and marking the distance from the logistics trolley to each to-be-loaded warehouseWhereinRepresent the firstThe number of the individual warehouse to be loaded,。
Step two, sorting the distances from the logistics trolley to each warehouse to be loaded according to the sequence from small to large, marking the first warehouse to be loaded as a preferred warehouse, further obtaining the distance from the preferred warehouse to each warehouse to be loaded, comparing to obtain the closest warehouse to be loaded, marking the closest warehouse to the preferred warehouse as a second warehouse, sequentially analyzing and sorting the rest warehouses to be loaded according to the method of analyzing the second warehouse, and marking the rest warehouses as a third warehouse and a fourth warehouse … … th respectivelyAnd planning a driving route for the logistics trolley according to the sequence of each warehouse to be loaded, and marking the driving route as an optimal driving route.
Preferably, the specific analysis process of the road surface condition acquisition module is as follows: the method comprises the steps of firstly, dividing an optimal driving path of a logistics trolley into a plurality of equal-length road sections according to a set length, marking the equal-length road sections as each road section, acquiring images of driving road surfaces of each road section of the logistics trolley through a built-in camera, and marking the images as driving road surface images of each road section.
Secondly, extracting edge contours of cracks in the road surfaces of all road sections from the road surface images of all road sections through an edge detection technology, and respectively marking the number and the length of the edge contours as、WhereinRepresent the firstThe number of the individual road segments is set,，Represent the firstThe number of the strip cracks is given,Substituting it into formulaObtaining the cracking degree of the road surface of each road sectionWhereinIndicating a preset maximum allowable number of cracks,Indicating a set crack length reference value,A weight factor indicating the number of cracks and the length of the cracks.
Third, gray level processing is carried out on the road surface images of all road sections, pixel points of any concave part in the road surface gray level images of all road sections are taken as seed pixel points, gray level value detection is carried out on the seed pixel points and all pixel points in the road surface gray level images of all road sections respectively, and the result is recorded asWhereinRepresent the firstThe number of the individual pixels is determined,By the formulaObtaining gray differences of the same sub-pixel points of each pixel point in the gray images of the road surfaces of each road section, comparing the gray differences with a preset gray difference range, screening out the pixel points of which the gray differences of all the same sub-pixel points belong to the preset gray difference range, recording as the number of concave pixel points of the gray images of the road surfaces of each road section, simultaneously extracting the total number of the pixel points of the gray images of the road surfaces of each road section, dividing the number of the concave pixel points of the gray images of the road surfaces of each road section by the total number of the pixel points of the gray images of the road surfaces of each road section to obtain the concave degree of the road surfaces of each road section, recording as the concave degree of the road surfaces of each road section。
Preferably, the specific analysis process of the motion control module is as follows: the first step, the cracking degree of the road surface of each road section is respectively readDegree of dishingSubstituting it into formulaObtaining the road surface flatness of the road surface of each road sectionWhereinWeight factors respectively representing the set cracking degree and the set dishing degree,Is a natural constant.
And secondly, extracting the logistics vehicle speed corresponding to the preset road surface flatness range from the management database, and matching the logistics vehicle speed with the road surface flatness of the road surface of each road section to obtain the logistics vehicle speed corresponding to the road surface flatness of the road surface of each road section, so as to regulate and control the speed of each road section of the logistics trolley.
Preferably, the specific analysis process of the obstacle module is as follows: the first step, ultrasonic wave is sent to the advancing direction by utilizing an ultrasonic sensor arranged in the logistics trolley, and the time length from the ultrasonic wave to the logistics trolley is recorded, and the time length is recorded as the ultrasonic wave round trip time lengthExtracting ultrasonic unit speed from management database, and recording asBy means ofObtaining the distance from the logistics trolley to the obstacleSimultaneously, the camera acquires images of the obstacles, the edge detection technology detects the edges of the obstacles in the obstacle images, and the width of the obstacles is extracted from the edge contours of the obstaclesComparing the distance between the logistics trolley and the obstacle with a set logistics trolley safety distance threshold value, if the distance between the logistics trolley and the obstacle is larger than the set logistics trolley safety distance threshold value, indicating that the distance between the logistics trolley and the obstacle is longer, avoiding the obstacle is not needed, and if the distance between the logistics trolley and the obstacle is smaller than or equal to the set logistics trolley safety distance threshold value, controlling the logistics trolley to execute the obstacle avoidance function, and recording the distance between the logistics trolley and the obstacle as when the logistics trolley executes the obstacle avoidance function。
Second, through the formulaObtaining the steering angle of the logistics trolleySimultaneously, the pressure sensors are used for respectively detecting the pressure of each wheel of the logistics trolley in the obstacle avoidance process, and the average value is obtained to obtain the pressure of the wheel, which is recorded as。
Preferably, the specific analysis process of the obstacle avoidance safety of the logistics trolley is as follows:
The first step, the distance from the logistics trolley to the obstacle when the logistics trolley executes the obstacle avoidance function is respectively read Steering angle of logistics trolleyWheel pressure，Obtain obstacle avoidance safety of logistics trolleyWhereinRespectively representing the reference values of the set optimal obstacle avoidance distance, the optimal steering angle and the wheel pressure,The weight factors of the set distance, steering angle and wheel pressure are respectively represented.
And secondly, comparing the obstacle avoidance safety of the logistics trolley with a preset obstacle avoidance safety threshold, if the obstacle avoidance safety of the logistics trolley is greater than or equal to the preset obstacle avoidance safety threshold, indicating that the logistics trolley is risk-free, otherwise, indicating that the logistics trolley is risk-free, and regulating and controlling the posture data of the logistics trolley when the follow-up logistics trolley encounters the obstacle.
Preferably, the specific analysis method of the obstacle avoidance analysis module comprises the following steps: by the formulaObtaining the optimal obstacle avoidance distance difference of the logistics trolleyMeanwhile, according to the method of analyzing the optimal obstacle avoidance distance difference of the logistics trolley, the steering angle of the logistics trolley is analyzed to obtain the optimal steering angle difference of the logistics trolley, and the optimal steering angle difference is recorded asAnd then the obstacle avoidance distance and the steering angle of the subsequent logistics trolley when the subsequent logistics trolley touches the obstacle are regulated and controlled.
Preferably, the specific analysis method of the predicted endurance mileage of the logistics trolley comprises the following steps: reading the maximum electric quantity and the driving mileage of the battery of the logistics trolley, and respectively recording asMeanwhile, the battery electric quantity of the logistics trolley is monitored in real time, and the current electric quantity is recorded as the residual battery electric quantitySubstituting it into formulaObtaining the predicted endurance mileage of the logistics trolley。
Preferably, the specific analysis method of the electric quantity supplementing module comprises the following steps: the first step, the whole journey mileage of the driving route of the logistics trolley is read from a management database and recorded asBy the formulaObtaining the target endurance mileage of the logistics trolleyAnd comparing the predicted range of the logistics trolley with the target range, if the predicted range of the logistics trolley is greater than or equal to the target range, indicating that the residual electric quantity of the logistics trolley is enough, and not needed to be supplemented, otherwise, indicating that the residual electric quantity of the logistics trolley is insufficient, and executing the second step.
And secondly, acquiring the position information of each charging pile from a digital map of a storage area, positioning the logistics trolley, taking the current position of the logistics trolley as the center of a circle, taking the predicted cruising range of the logistics trolley as the radius, constructing an electric quantity supplementing area of the logistics trolley, screening out each charging pile positioned in the electric quantity supplementing area of the logistics trolley from the position information of each charging pile, recording the electric quantity supplementing area as each alternative charging pile, calculating the distance from the logistics trolley to each alternative charging pile, sequencing the distances according to the sequence from small to large, taking the alternative charging pile corresponding to the first distance as the optimal charging pile, and controlling the trolley to carry out electric quantity supplementing to the optimal charging pile.
Compared with the prior art, the invention has the following beneficial effects: 1. according to the invention, the storage area digital map is constructed to acquire the position information of each warehouse and each charging pile, so that the optimal driving path is planned for the logistics trolley, the intelligent path planning and scheduling decision is realized, the driving time of the logistics trolley in the storage area is reduced, and the logistics efficiency is improved.
2. According to the invention, the road surface flatness of the road surface of each road section is obtained by analyzing the cracking degree and the sinking degree of the road surface of each road section, so that the speed of each road section of the logistics trolley is regulated and controlled, the speed of the logistics trolley can be increased on a good road surface, and meanwhile, the speed of the logistics trolley is reduced on a road section with poor road surface quality, so that safe and stable running is ensured, the transportation efficiency is improved, and the transportation time is shortened.
3. According to the invention, the obstacle avoidance safety of the logistics trolley is obtained by analyzing the gesture data of the logistics trolley, and the gesture data of the subsequent logistics trolley when the logistics trolley is used for avoiding the same obstacle is regulated and controlled, so that the collision is effectively avoided, the running safety of the logistics trolley is improved, and the logistics efficiency is improved.
4. According to the method, the estimated endurance mileage of the logistics trolley is obtained according to the residual electric quantity analysis of the logistics trolley, and then the electric quantity is supplemented for the logistics trolley by combining the position information of each charging pile, so that interruption or delay caused by insufficient electric quantity is avoided, and the operation efficiency of the logistics trolley is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram illustrating a system module connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a system for controlling running track of a warehouse AGV logistics trolley includes a digital map construction module, a road planning module, a road surface condition acquisition module, a motion control module, an obstacle avoidance analysis module, an electric quantity supplementing module, and a management database.
The management database is connected with the road planning module, the obstacle avoidance analysis module, the obstacle avoidance module, the motion control module and the electric quantity supplementing module, the digital map building module is connected with the road planning module and the electric quantity supplementing module, the road surface condition acquisition module is connected with the obstacle avoidance module and the motion control module, and the obstacle avoidance module is connected with the obstacle avoidance analysis module.
The digital map construction module is used for acquiring images of all subareas of the storage area through the camera, constructing a digital map by taking the images as the storage area, and acquiring the position information of all the storages and all the charging piles.
The specific analysis method of the digital map construction module comprises the following steps: dividing the storage area into a plurality of subareas with equal areas, acquiring images of the subareas through cameras in the storage area, recording the images as images of the subareas of the storage area, constructing a digital map for the storage area through the images of the subareas of the storage area, and simultaneously acquiring the position information of the storages and the charging piles from the digital map of the storage area and marking the position information; through the establishment of the digital map, automatic equipment such as AGVs can more accurately position the target position, optimize path planning, and therefore conveying efficiency and accuracy are improved.
And the road planning module is used for acquiring a transportation list of the logistics trolley and planning an optimal driving path for the logistics trolley by combining the position information of each warehouse.
The specific analysis process of the road planning module is as follows: the method comprises the steps of firstly, reading a transportation list of a logistics trolley and the types of goods stored in each warehouse from a management database, obtaining various goods required to be transported by the logistics trolley from the transportation list of the logistics trolley, matching the goods with the types of goods stored in each warehouse to obtain the storage warehouse of the various goods required to be transported by the logistics trolley, marking the storage warehouse as each to-be-loaded warehouse, reading the position information of each to-be-loaded warehouse from a storage area digital map, positioning the position of the logistics trolley, respectively obtaining the distance from the logistics trolley to each to-be-loaded warehouse, marking the distance from the logistics trolley to each to-be-loaded warehouse, and marking the distance from the logistics trolley to each to-be-loaded warehouseWhereinRepresent the firstThe number of the individual warehouse to be loaded,; According to the storage area digital map and the positioning information of the position of the logistics trolley, the position information and the distance of each to-be-loaded warehouse are combined, the route from the logistics trolley to each to-be-loaded warehouse can be optimally planned, no-load running and energy consumption are reduced, and accordingly transportation efficiency is improved.
Step two, sorting the distances from the logistics trolley to each warehouse to be loaded according to the sequence from small to large, marking the first warehouse to be loaded as a preferred warehouse, further obtaining the distance from the preferred warehouse to each warehouse to be loaded, comparing to obtain the closest warehouse to be loaded, marking the closest warehouse to the preferred warehouse as a second warehouse, sequentially analyzing and sorting the rest warehouses to be loaded according to the method of analyzing the second warehouse, and marking the rest warehouses as a third warehouse and a fourth warehouse … … th respectivelyThe warehouses plan driving routes for the logistics trolleys according to the ordering of the warehouses to be loaded, and record the driving routes as optimal driving routes; by gradually selecting the warehouse to be loaded closest to the warehouse as the next destination, the planning of the optimal driving path is realized, unnecessary surrounding and repeated driving are avoided, the route of the logistics trolley is optimized, and the logic and high efficiency of the route are improved.
The road surface condition acquisition module is used for acquiring images of the road surfaces of all road sections of the logistics trolley through the built-in cameras, and further analyzing and obtaining the cracking degree and the sinking degree of the road surfaces of all road sections.
The specific analysis process of the road surface condition acquisition module is as follows: dividing an optimal driving path of the logistics trolley into a plurality of equal-length road sections according to a set length, marking the equal-length road sections as road sections, acquiring images of driving road surfaces of the road sections of the logistics trolley through built-in cameras, and marking the images as driving road surface images of the road sections; by acquiring the road surface images of the road sections, the road surface condition can be monitored in real time, the road surface problem can be found in time, countermeasures can be taken, and the running safety of the logistics trolley is ensured.
Secondly, extracting edge contours of cracks in the road surfaces of all road sections from the road surface images of all road sections through an edge detection technology, and respectively marking the number and the length of the edge contours as、WhereinRepresent the firstThe number of the individual road segments is set,，Represent the firstThe number of the strip cracks is given,Substituting it into formulaObtaining the cracking degree of the road surface of each road sectionWhereinIndicating a preset maximum allowable number of cracks,Indicating a set crack length reference value,A weight factor indicating the number of cracks and the length of the cracks; in the running process of the logistics trolley, road cracks can lead to jolt and instability of the vehicle and even cause accidents, potential safety hazards can be found in advance by monitoring road crack conditions and calculating cracking degree, and the running safety of the logistics trolley is ensured by adopting targeted maintenance measures.
It should be noted that, in one embodiment,It may be set to 0.5,The crack length represents the length of a single crack on the road surface, and longer cracks are more likely to generate water erosion and looseness, so that the road surface is damaged, and the weight corresponding to the number of the cracks and the crack length is equal.
Third, gray level processing is carried out on the road surface images of all road sections, pixel points of any concave part in the road surface gray level images of all road sections are taken as seed pixel points, gray level value detection is carried out on the seed pixel points and all pixel points in the road surface gray level images of all road sections respectively, and the result is recorded asWhereinRepresent the firstThe number of the individual pixels is determined,By the formulaObtaining gray differences of the same sub-pixel points of each pixel point in the gray images of the road surfaces of each road section, comparing the gray differences with a preset gray difference range, screening out the pixel points of which the gray differences of all the same sub-pixel points belong to the preset gray difference range, recording as the number of concave pixel points of the gray images of the road surfaces of each road section, simultaneously extracting the total number of the pixel points of the gray images of the road surfaces of each road section, dividing the number of the concave pixel points of the gray images of the road surfaces of each road section by the total number of the pixel points of the gray images of the road surfaces of each road section to obtain the concave degree of the road surfaces of each road section, recording as the concave degree of the road surfaces of each road section; Detecting the degree of the concave part of the road surface can help to timely identify the damage condition of the road surface, reduce the risks of jolt, instability and even accidents of the vehicle caused by the concave part of the road surface, and improve the running safety of the logistics trolley.
And the motion control module is used for analyzing the road surface flatness of the road surface of the road section according to the cracking degree and the dent degree of the road surface of the road section of the road, and further regulating and controlling the speed of each road section of the logistics trolley.
The specific analysis process of the motion control module is as follows: the first step, the cracking degree of the road surface of each road section is respectively readDegree of dishingSubstituting it into formulaObtaining the road surface flatness of the road surface of each road sectionWhereinWeight factors respectively representing the set cracking degree and the set dishing degree,Is a natural constant; road surface flatness is crucial to the running efficiency of the logistics trolley, the jolt of the vehicle in the running process can be reduced through reasonable evaluation of the road surface flatness, the safe transportation of goods is improved, the transportation time is shortened, and the transportation efficiency is improved.
It should be noted that, in one embodiment,It may be set to 0.5,The cracking degree can be set to 0.5, because the cracking degree is one of the important indexes in evaluating the quality of the pavement, because the cracking can directly affect the structural integrity and the service life of the pavement, the larger and deeper cracking can lead to the breakage and damage of the pavement, the carrying capacity of the pavement is reduced, the discomfort and the danger of running are increased, the sinking degree usually reflects the pothole and the sinking condition of the pavement, the sinking can increase the bumping sensation of driving, the impact to the vehicle can be generated, the driving comfort is reduced, the abrasion and the damage are increased, meanwhile, the larger sinking can accumulate water, the pavement becomes greasy, the potential safety hazard is increased, and the weights corresponding to the cracking degree and the sinking degree are equal.
Secondly, extracting the logistics vehicle speed corresponding to the preset road surface flatness range from the management database, and matching the logistics vehicle speed with the road surface flatness of the road surface of each road section to obtain the logistics vehicle speed corresponding to the road surface flatness of the road surface of each road section, so as to regulate and control the speed of each road section of the logistics trolley; the logistics vehicle speed corresponding to the road surface flatness of each road section is obtained through matching and regulated, so that the accident occurrence probability caused by the excessively high speed at the uneven road surface can be effectively reduced, the driving safety is improved, and the safety of goods and personnel is ensured.
The obstacle avoidance module is used for detecting obstacles in the driving process of the logistics trolley, so as to control the logistics trolley to avoid the obstacle, and simultaneously detect the gesture data of the logistics trolley during obstacle avoidance, wherein the gesture data of the trolley comprise the distance to the obstacles, the steering angle and the wheel pressure when the obstacle avoidance function is executed.
The specific analysis process of the obstacle module is as follows: the first step, ultrasonic wave is sent to the advancing direction by utilizing an ultrasonic sensor arranged in the logistics trolley, and the time length from the ultrasonic wave to the logistics trolley is recorded, and the time length is recorded as the ultrasonic wave round trip time lengthExtracting ultrasonic unit speed from management database, and recording asBy means ofObtaining the distance from the logistics trolley to the obstacleSimultaneously, the camera acquires images of the obstacles, the edge detection technology detects the edges of the obstacles in the obstacle images, and the width of the obstacles is extracted from the edge contours of the obstaclesComparing the distance between the logistics trolley and the obstacle with a set logistics trolley safety distance threshold value, if the distance between the logistics trolley and the obstacle is larger than the set logistics trolley safety distance threshold value, indicating that the distance between the logistics trolley and the obstacle is longer, avoiding the obstacle is not needed, and if the distance between the logistics trolley and the obstacle is smaller than or equal to the set logistics trolley safety distance threshold value, controlling the logistics trolley to execute the obstacle avoidance function, and recording the distance between the logistics trolley and the obstacle as when the logistics trolley executes the obstacle avoidance function; Utilize ultrasonic sensor and camera technique, the commodity circulation dolly can the real-time perception the distance of place ahead barrier to acquire the width of barrier through edge detection technique, thereby realize intelligent obstacle avoidance function, let the commodity circulation dolly can avoid the barrier in the travel, improve driving safety.
Second, through the formulaObtaining the steering angle of the logistics trolleySimultaneously, the pressure sensors are used for respectively detecting the pressure of each wheel of the logistics trolley in the obstacle avoidance process, and the average value is obtained to obtain the pressure of the wheel, which is recorded as; The steering angle of the logistics trolley is calculated through a formula, the running direction of the vehicle can be adjusted according to specific conditions, so that the logistics trolley can avoid obstacles more flexibly, collision risk is reduced, obstacle avoidance efficiency is improved, the pressure of each wheel of the logistics trolley is detected through a pressure sensor, the average pressure value of the wheels is calculated, stability and balance in the running process of the vehicle are monitored, possible air leakage or other problems can be found and corrected in time, and safe running of the vehicle is guaranteed.
The obstacle avoidance analysis module is used for analyzing and obtaining the obstacle avoidance safety of the logistics trolley according to the gesture data of the logistics trolley, and further regulating and controlling the gesture data of the subsequent logistics trolley when the logistics trolley avoids the same obstacle.
The specific analysis process of the obstacle avoidance safety of the logistics trolley is as follows: the first step, the distance from the logistics trolley to the obstacle when the logistics trolley executes the obstacle avoidance function is respectively readSteering angle of logistics trolleyWheel pressure，Obtain obstacle avoidance safety of logistics trolleyWhereinRespectively representing the reference values of the set optimal obstacle avoidance distance, the optimal steering angle and the wheel pressure,Weight factors respectively representing the set distance, steering angle and wheel pressure; the obstacle avoidance safety of the logistics trolley can be analyzed, the obstacle avoidance behavior of the logistics trolley can be monitored and adjusted, and the obstacle avoidance behavior is ensured to accord with the set safety standard.
It should be noted that, in one embodiment,It may be set to 0.4,It may be set to 0.3,The obstacle avoidance distance can be set to be 0.3, and refers to the distance required to be kept when the logistics trolley encounters an obstacle so as to ensure safety and timely avoidance, and the larger obstacle avoidance distance can provide more reaction time and operation space for the trolley, so that collision and accident are reduced, and the weight corresponding to the obstacle avoidance distance is larger.
And secondly, comparing the obstacle avoidance safety of the logistics trolley with a preset obstacle avoidance safety threshold, if the obstacle avoidance safety of the logistics trolley is greater than or equal to the preset obstacle avoidance safety threshold, then indicating that the logistics trolley is free of risks, otherwise indicating that the logistics trolley is at risk of obstacle avoidance, and regulating and controlling gesture data of the logistics trolley when the follow-up logistics trolley encounters the obstacle, so that the obstacle avoidance risks are found and processed in time, pause or delay caused by obstacle avoidance difficulty of the logistics trolley can be avoided, and the logistics transportation efficiency and punctuality are improved.
The specific analysis method of the obstacle avoidance analysis module comprises the following steps: by the formulaObtaining the optimal obstacle avoidance distance difference of the logistics trolleyMeanwhile, according to the method of analyzing the optimal obstacle avoidance distance difference of the logistics trolley, the steering angle of the logistics trolley is analyzed to obtain the optimal steering angle difference of the logistics trolley, and the optimal steering angle difference is recorded asFurther, the obstacle avoidance distance and the steering angle of the subsequent logistics trolley when the subsequent logistics trolley touches the obstacle are regulated and controlled; the optimal obstacle avoidance distance difference of the logistics trolley is obtained through formula calculation, the optimal distance difference of the logistics trolley when avoiding the obstacle can be determined, the logistics trolley is helped to adjust the obstacle avoidance distance according to specific conditions, the obstacle is avoided more effectively, the accuracy and efficiency of obstacle avoidance are improved, the optimal steering angle difference of the logistics trolley can guide the logistics trolley to adjust the steering angle when encountering the obstacle, so that the obstacle is avoided to the greatest extent, safe passing is ensured, and the intellectualization and the accuracy of obstacle avoidance are improved.
And the electric quantity supplementing module is used for analyzing the residual electric quantity of the logistics trolley to obtain the predicted endurance mileage of the logistics trolley, and further supplementing the electric quantity of the logistics trolley by combining the position information of each charging pile.
The specific analysis method of the estimated endurance mileage of the logistics trolley comprises the following steps: reading the maximum electric quantity and the driving mileage of the battery of the logistics trolley, and respectively recording asMeanwhile, the battery electric quantity of the logistics trolley is monitored in real time, and the current electric quantity is recorded as the residual battery electric quantitySubstituting it into formulaObtaining the predicted endurance mileage of the logistics trolley; Through the surplus battery electric quantity of real-time supervision commodity circulation dolly, can help in time know the electric quantity condition of commodity circulation dolly to arrange suitable charging plan or dispatch scheme, avoid because the electric quantity is not enough to cause commodity circulation transportation to break or delay.
The specific analysis method of the electric quantity supplementing module comprises the following steps: the first step, the whole journey mileage of the driving route of the logistics trolley is read from a management database and recorded asBy the formulaObtaining the target endurance mileage of the logistics trolleyComparing the predicted range of the logistics trolley with the target range, if the predicted range of the logistics trolley is greater than or equal to the target range, indicating that the residual electric quantity of the logistics trolley is enough, and not needed to be supplemented, otherwise, indicating that the residual electric quantity of the logistics trolley is insufficient, and executing the second step; by comparing the charging schedule with the target endurance mileage, whether the residual electric quantity of the logistics trolley is enough to support the completion of the whole journey can be judged in advance, so that a charging schedule is timely arranged or a driving route is timely adjusted, and transportation interruption or delay caused by insufficient electric quantity in the middle is avoided.
The second step, the position information of each charging pile is obtained from a digital map of a storage area, meanwhile, the logistics trolley is positioned, the current position of the logistics trolley is used as the center of a circle, the predicted cruising mileage of the logistics trolley is used as the radius, the electric quantity supplementing area of the logistics trolley is constructed, each charging pile positioned in the electric quantity supplementing area of the logistics trolley is screened out from the position information of each charging pile, the charging pile is recorded as each alternative charging pile, the distance from the logistics trolley to each alternative charging pile is calculated, the distances from the logistics trolley to the alternative charging piles are ordered according to the sequence from small to large, the alternative charging pile corresponding to the first distance is used as the optimal charging pile, and the trolley is controlled to conduct electric quantity supplementing to the optimal charging pile; by selecting the charging pile closest to the charging pile as the optimal charging point, the distance from the logistics trolley to the charging pile can be reduced, time is saved, charging efficiency is improved, and unnecessary time waste caused by searching the charging pile is avoided.
The management database is used for storing a transportation list of the logistics trolley, the types of goods stored in all warehouses, the logistics vehicle speed and the ultrasonic unit speed corresponding to the road surface flatness range.
The system acquires the position information of each warehouse and each charging pile through constructing a digital map, so as to plan an optimal driving path for the logistics trolley, regulates and controls the speed of each road section of the logistics trolley according to the road surface flatness of the driving road surface of each road section, obtains the obstacle avoidance safety of the logistics trolley according to the gesture data analysis of the logistics trolley, regulates and controls the gesture data of the subsequent logistics trolley, and obtains the predicted endurance mileage of the logistics trolley according to the residual electric quantity analysis of the logistics trolley, thereby carrying out electric quantity supplement on the logistics trolley, realizing the intelligent regulation and control of the logistics trolley by the system, and improving the efficiency and reliability of the whole logistics system.
While embodiments of the present invention have been shown and described above, it should be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention, which is also intended to be covered by the present invention.
Claims (1)
1. The system for controlling the running track of the storage AGV logistics trolley is characterized by comprising the following modules:
The digital map construction module is used for acquiring images of all subareas of the storage area through the camera, constructing a digital map by taking the images as the storage area, and acquiring the position information of all the storages and all the charging piles;
The road planning module is used for acquiring a transportation list of the logistics trolley and planning an optimal driving path for the logistics trolley by combining the position information of each warehouse;
The road surface condition acquisition module is used for acquiring images of the road surfaces of all road sections of the logistics trolley through the built-in cameras, and further analyzing and obtaining the cracking degree and the sinking degree of the road surfaces of all road sections;
the motion control module is used for analyzing the pavement flatness of the road surfaces of the road sections according to the cracking degree and the sinking degree of the road surfaces of the road sections, and further regulating and controlling the speed of each road section of the logistics trolley;
The obstacle avoidance module is used for detecting obstacles in the driving process of the logistics trolley so as to control the logistics trolley to avoid the obstacle, and detecting gesture data of the logistics trolley during obstacle avoidance, wherein the gesture data of the trolley comprise the distance from the obstacle, the steering angle and the wheel pressure when the obstacle avoidance function is executed;
The obstacle avoidance analysis module is used for analyzing the attitude data of the logistics trolley to obtain the obstacle avoidance safety of the logistics trolley, and further regulating and controlling the attitude data of the subsequent logistics trolley when the logistics trolley avoids the same obstacle;
The electric quantity supplementing module is used for analyzing the residual electric quantity of the logistics trolley to obtain the predicted endurance mileage of the logistics trolley, and further supplementing the electric quantity of the logistics trolley by combining the position information of each charging pile;
The management database is used for storing a transportation list of the logistics trolley, the types of goods stored in each warehouse, the corresponding logistics vehicle speed and the ultrasonic unit speed of the road surface flatness range;
The specific analysis method of the digital map construction module comprises the following steps:
Dividing the storage area into a plurality of subareas with equal areas, acquiring images of the subareas through cameras in the storage area, recording the images as images of the subareas of the storage area, constructing a digital map for the storage area through the images of the subareas of the storage area, and simultaneously acquiring the position information of the storages and the charging piles from the digital map of the storage area and marking the position information;
the specific analysis process of the road planning module is as follows:
The method comprises the steps of firstly, reading a transportation list of a logistics trolley and the types of goods stored in each warehouse from a management database, obtaining various goods required to be transported by the logistics trolley from the transportation list of the logistics trolley, matching the goods with the types of goods stored in each warehouse to obtain the storage warehouse of the various goods required to be transported by the logistics trolley, marking the storage warehouse as each to-be-loaded warehouse, reading the position information of each to-be-loaded warehouse from a storage area digital map, positioning the position of the logistics trolley, respectively obtaining the distance from the logistics trolley to each to-be-loaded warehouse, marking the distance from the logistics trolley to each to-be-loaded warehouse, and marking the distance from the logistics trolley to each to-be-loaded warehouse WhereinRepresent the firstThe number of the individual warehouse to be loaded,；
Step two, sorting the distances from the logistics trolley to each warehouse to be loaded according to the sequence from small to large, marking the first warehouse to be loaded as a preferred warehouse, further obtaining the distance from the preferred warehouse to each warehouse to be loaded, comparing to obtain the closest warehouse to be loaded, marking the closest warehouse to the preferred warehouse as a second warehouse, sequentially analyzing and sorting the rest warehouses to be loaded according to the method of analyzing the second warehouse, and marking the rest warehouses as a third warehouse and a fourth warehouse … … th respectivelyThe warehouses plan driving routes for the logistics trolleys according to the ordering of the warehouses to be loaded, and record the driving routes as optimal driving routes;
The specific analysis process of the road surface condition acquisition module is as follows:
dividing an optimal driving path of the logistics trolley into a plurality of equal-length road sections according to a set length, marking the equal-length road sections as road sections, acquiring images of driving road surfaces of the road sections of the logistics trolley through built-in cameras, and marking the images as driving road surface images of the road sections;
Secondly, extracting edge contours of cracks in the road surfaces of all road sections from the road surface images of all road sections through an edge detection technology, and respectively marking the number and the length of the edge contours as 、WhereinRepresent the firstThe number of the individual road segments is set,，Represent the firstThe number of the strip cracks is given,Substituting it into formulaObtaining the cracking degree of the road surface of each road sectionWhereinIndicating a preset maximum allowable number of cracks,Indicating a set crack length reference value,A weight factor indicating the number of cracks and the length of the cracks;
Third, gray level processing is carried out on the road surface images of all road sections, pixel points of any concave part in the road surface gray level images of all road sections are taken as seed pixel points, gray level value detection is carried out on the seed pixel points and all pixel points in the road surface gray level images of all road sections respectively, and the result is recorded as WhereinRepresent the firstThe number of the individual pixels is determined,By the formulaObtaining gray differences of the same sub-pixel points of each pixel point in the gray images of the road surfaces of each road section, comparing the gray differences with a preset gray difference range, screening out the pixel points of which the gray differences of all the same sub-pixel points belong to the preset gray difference range, recording as the number of concave pixel points of the gray images of the road surfaces of each road section, simultaneously extracting the total number of the pixel points of the gray images of the road surfaces of each road section, dividing the number of the concave pixel points of the gray images of the road surfaces of each road section by the total number of the pixel points of the gray images of the road surfaces of each road section to obtain the concave degree of the road surfaces of each road section, recording as the concave degree of the road surfaces of each road section；
The specific analysis process of the motion control module is as follows:
the first step, the cracking degree of the road surface of each road section is respectively read Degree of dishingSubstituting it into formulaObtaining the road surface flatness of the road surface of each road sectionWhereinWeight factors respectively representing the set cracking degree and the set dishing degree,Is a natural constant;
secondly, extracting the logistics vehicle speed corresponding to the preset road surface flatness range from the management database, and matching the logistics vehicle speed with the road surface flatness of the road surface of each road section to obtain the logistics vehicle speed corresponding to the road surface flatness of the road surface of each road section, so as to regulate and control the speed of each road section of the logistics trolley;
The specific analysis process of the obstacle avoidance module is as follows:
The first step, ultrasonic wave is sent to the advancing direction by utilizing an ultrasonic sensor arranged in the logistics trolley, and the time length from the ultrasonic wave to the logistics trolley is recorded, and the time length is recorded as the ultrasonic wave round trip time length Extracting ultrasonic unit speed from management database, and recording asBy means ofObtaining the distance from the logistics trolley to the obstacleSimultaneously, the camera acquires images of the obstacles, the edge detection technology detects the edges of the obstacles in the obstacle images, and the width of the obstacles is extracted from the edge contours of the obstaclesComparing the distance between the logistics trolley and the obstacle with a set logistics trolley safety distance threshold value, if the distance between the logistics trolley and the obstacle is larger than the set logistics trolley safety distance threshold value, indicating that the distance between the logistics trolley and the obstacle is longer, avoiding the obstacle is not needed, and if the distance between the logistics trolley and the obstacle is smaller than or equal to the set logistics trolley safety distance threshold value, controlling the logistics trolley to execute the obstacle avoidance function, and recording the distance between the logistics trolley and the obstacle as when the logistics trolley executes the obstacle avoidance function；
Second, through the formulaObtaining the steering angle of the logistics trolleySimultaneously, the pressure sensors are used for respectively detecting the pressure of each wheel of the logistics trolley in the obstacle avoidance process, and the average value is obtained to obtain the pressure of the wheel, which is recorded as；
The specific analysis process of the obstacle avoidance safety of the logistics trolley is as follows:
The first step, the distance from the logistics trolley to the obstacle when the logistics trolley executes the obstacle avoidance function is respectively read Steering angle of logistics trolleyWheel pressure，Obtain obstacle avoidance safety of logistics trolleyWhereinRespectively representing the reference values of the set optimal obstacle avoidance distance, the optimal steering angle and the wheel pressure,Weight factors respectively representing the set distance, steering angle and wheel pressure;
Secondly, comparing the obstacle avoidance safety of the logistics trolley with a preset obstacle avoidance safety threshold, if the obstacle avoidance safety of the logistics trolley is greater than or equal to the preset obstacle avoidance safety threshold, indicating that the logistics trolley is free of risk, otherwise, indicating that the logistics trolley is at risk of obstacle avoidance, and regulating and controlling the posture data of the logistics trolley when the follow-up logistics trolley touches the obstacle;
the specific analysis method of the obstacle avoidance analysis module comprises the following steps:
By the formula Obtaining the optimal obstacle avoidance distance difference of the logistics trolleyMeanwhile, according to the method of analyzing the optimal obstacle avoidance distance difference of the logistics trolley, the steering angle of the logistics trolley is analyzed to obtain the optimal steering angle difference of the logistics trolley, and the optimal steering angle difference is recorded asFurther, the obstacle avoidance distance and the steering angle of the subsequent logistics trolley when the subsequent logistics trolley touches the obstacle are regulated and controlled;
The specific analysis method of the estimated endurance mileage of the logistics trolley comprises the following steps:
reading the maximum electric quantity and the driving mileage of the battery of the logistics trolley, and respectively recording as Meanwhile, the battery electric quantity of the logistics trolley is monitored in real time, and the current electric quantity is recorded as the residual battery electric quantitySubstituting it into formulaObtaining the predicted endurance mileage of the logistics trolley；
The specific analysis method of the electric quantity supplementing module comprises the following steps:
the first step, the whole journey mileage of the driving route of the logistics trolley is read from a management database and recorded as By the formulaObtaining the target endurance mileage of the logistics trolleyComparing the predicted range of the logistics trolley with the target range, if the predicted range of the logistics trolley is greater than or equal to the target range, indicating that the residual electric quantity of the logistics trolley is enough, and not needed to be supplemented, otherwise, indicating that the residual electric quantity of the logistics trolley is insufficient, and executing the second step;
And secondly, acquiring the position information of each charging pile from a digital map of a storage area, positioning the logistics trolley, taking the current position of the logistics trolley as the center of a circle, taking the predicted cruising range of the logistics trolley as the radius, constructing an electric quantity supplementing area of the logistics trolley, screening out each charging pile positioned in the electric quantity supplementing area of the logistics trolley from the position information of each charging pile, recording the electric quantity supplementing area as each alternative charging pile, calculating the distance from the logistics trolley to each alternative charging pile, sequencing the distances according to the sequence from small to large, taking the alternative charging pile corresponding to the first distance as the optimal charging pile, and controlling the trolley to carry out electric quantity supplementing to the optimal charging pile.
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| CN109344928A (en) * | 2018-09-19 | 2019-02-15 | 中国科学院信息工程研究所 | The accurate checking method of cargo and system based on unmanned plane in a kind of bulk storage plant |
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| CN109344928A (en) * | 2018-09-19 | 2019-02-15 | 中国科学院信息工程研究所 | The accurate checking method of cargo and system based on unmanned plane in a kind of bulk storage plant |
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