RGV multi-vehicle cooperative control method and device

Abstract

The invention discloses an RGV multi-vehicle cooperative control method and device applied to the field of storage and transportation, and the method comprises a centralized vehicle group management strategy and a distributed inter-vehicle cooperative strategy. The centralized vehicle group management strategy comprises the steps that a vehicle group control center is arranged, and the vehicle group control center is responsible for task RGV selection and task RGV path planning; the distributed inter-vehicle cooperation strategy comprises setting an inter-vehicle communication module and a local control unit for each RGV; each RGV exchanges information with other RGVs through the inter-vehicle communication module so as to obtain real-time states of all the RGVs, and the RGVs are independently controlled through the local control unit to realize speed coordination, anti-collision avoidance and task path avoidance; the vehicle group control center sends information to the inter-vehicle communication module, and the local control units adjust the speed and the driving state of the corresponding RGVs according to the information received by the inter-vehicle communication module. The instantaneity of information exchange between the RGVs is enhanced, and efficient cooperative control of the RGVs is realized.

Description

Technical Field

[0001] The present invention belongs to the field of warehousing and transportation, and specifically relates to a RGV multi-vehicle collaborative control method and device. Background Art

[0002] With the development of modern industrial automation and logistics industry, Rail Guided Vehicle (RGV) plays an increasingly important role in the internal logistics system of warehouses and factories as a highly automated, fixed-path, and repetitive handling tool. However, with the increase in application demand, the challenges faced by traditional RGV systems are becoming increasingly prominent. Especially in the scenario of multi-vehicle collaborative operation, how to effectively manage the vehicle group and ensure the efficiency, safety and stability of the operation has become an urgent problem to be solved.

[0003] In the existing RGV system, a single central controller is usually relied on to dispatch and manage multiple RGVs. For example, the patent with publication number CN110817220A discloses an RGV avoidance method, which includes the following steps: providing a control unit, the control unit sends a movement instruction to the first RGV, wherein the movement instruction includes the movement direction and the target position; the control unit obtains the position information of the first RGV and the second RGV, and makes a judgment based on the information of the two RGVs to avoid interference during operation. This method can barely maintain operation in an environment with a small number of vehicles. However, with the expansion of the scale of the vehicle group, the disadvantages of centralized management gradually emerge: on the one hand, the computing pressure of the central controller increases dramatically, which is easy to become a bottleneck of system performance and affect the real-time and accuracy of the instructions; on the other hand, the high dependence on the central controller means that once it fails, the entire system will face the risk of paralysis, which seriously threatens the continuity and reliability of logistics operations.

[0004] In addition, traditional path planning algorithms are unable to cope with complex and changing logistics environments, especially when it is necessary to frequently adjust task allocation, avoid congestion or deal with emergencies, and it is difficult to make the best decision quickly. At the same time, the lack of effective direct communication between RGVs makes collaborative work inefficient, increases the risk of collision, and limits the overall transportation efficiency of the system. Summary of the invention

[0005] The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a RGV multi-vehicle collaborative control method and device.

[0006] To achieve the above object, the technical solution of the present invention is:

[0007] A RGV multi-vehicle cooperative control method, comprising:

[0008] Centralized vehicle group management strategy and distributed vehicle-to-vehicle collaboration strategy;

[0009] The centralized vehicle group management strategy includes setting up a vehicle group control center, which is responsible for selecting task RGVs and planning task RGV paths;

[0010] The distributed inter-vehicle coordination strategy includes setting an inter-vehicle communication module and a local control unit for each RGV; each RGV exchanges information with other RGVs through the inter-vehicle communication module to obtain the real-time status of all RGVs, and controls the RGV speed coordination, anti-collision avoidance and task path avoidance individually through the local control unit;

[0011] The vehicle group control center sends information to the inter-vehicle communication module, and the local control unit adjusts the speed and driving state of the corresponding RGV according to the information received by the inter-vehicle communication module.

[0012] Preferably, the vehicle group control center specifically includes the following when selecting the task RGV and planning the task RGV path: the lower-level user issues the RGV inbound or outbound task, and the upper-level vehicle group control center first selects the optimal task vehicle based on the historical data and real-time position of each vehicle, then performs path search and completes path planning, and after completing path planning, sends the destination workstation task to the task RGV.

[0013] Preferably, the path planning uses an Astar path algorithm to search for the driving path of the RGV.

[0014] Preferably, the Astar path algorithm adopts a dual parallel search, searching from the starting point and the end point simultaneously toward each other, and terminating the search in advance if an overlapping point is encountered, otherwise the search continues until the target point is found.

[0015] Preferably, it also includes a distributed inter-vehicle coordination strategy, which is not controlled by the vehicle group control center, but is directly circulated locally between each RGV, and communicates with the wireless vehicle-to-vehicle communication module of the RGV through the local inter-vehicle communication network to achieve automatic avoidance, speed control, and state control of the entire vehicle group.

[0016] Preferably, the local control unit stores the RGV number, real-time working status, real-time position, real-time speed and workstation occupancy in the form of standard status data blocks, and each RGV can directly read the status data blocks of other RGVs through the wireless inter-vehicle communication module to obtain the real-time status of all RGVs.

[0017] The present invention also provides an RGV multi-vehicle cooperative control device, and the RGV multi-vehicle cooperative control method as described above is applied when the RGV multi-vehicle cooperative control device is working.

[0018] Preferably, the device further comprises:

[0019] Three-dimensional shelves for stacking boxes;

[0020] Warehouse robots for transporting containers;

[0021] Inbound conveyor line, the conveyor line for warehouse entry to three-dimensional shelves;

[0022] Outbound conveyor line, the outbound conveyor line leaving the three-dimensional shelf;

[0023] The detection module is used to detect the information of the material box.

[0024] After adopting the above technical solution, the RGV multi-vehicle cooperative control method and device provided by the present invention has the following beneficial effects compared with the prior art.

[0025] (1) By setting up a swarm control center and configuring an inter-vehicle communication module and a local control unit for each RGV, this method achieves efficient collaborative control of RGVs. This structure not only enhances the immediacy of information exchange between RGVs, but also enables each RGV to respond quickly according to real-time road conditions and other RGV states through dynamic adjustment of the local control unit, significantly improving the flexibility and safety of system operation. The centralized planning and task allocation capabilities of the swarm control center effectively optimize resource utilization, avoid the bottleneck problem caused by traditional reliance on a single central controller, and improve overall operational efficiency.

[0026] (2) By combining the centralized vehicle group management strategy with the distributed vehicle-to-vehicle collaboration strategy, the coordinated scheduling and control of the vehicle group control center and the vehicle local control unit are realized, and the operating efficiency and system robustness are greatly improved.

[0027] (3) Through the storage and sharing of standardized status data blocks, each RGV can grasp the working status of the entire fleet in real time and achieve information transparency. This mechanism simplifies the information exchange process, improves the efficiency of data exchange, and provides a real-time and accurate basis for the RGV's autonomous avoidance and speed control, thereby enhancing the collaborative work efficiency and safety of the entire cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings are part of the present invention and are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but do not constitute an improper limitation of the present invention. Obviously, the drawings described below are only some embodiments. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the accompanying drawings:

[0029] Figure 1It is a structural diagram of the control method of the present invention;

[0030] Figure 2 This is a schematic diagram of the double parallel search situation I of the present invention;

[0031] Figure 3 This is a schematic diagram of the double parallel search situation II of the present invention;

[0032] Figure 4 is a first schematic diagram of the RGV body structure of the present invention;

[0033] Figure 5 is a second schematic diagram of the RGV body structure of the present invention;

[0034] Figure 6 is a third schematic diagram of the RGV vehicle body structure of the present invention;

[0035] Figure 7 is a flow chart of the distributed vehicle-to-vehicle collaboration strategy of the present invention;

[0036] Figure 8 It is a schematic diagram of the vehicle speed self-control process of multi-vehicle cooperation of the present invention;

[0037] Fig. 9 This is a curve diagram before the start-stop speed optimization of the present invention;

[0038] Fig.10 This is a curve diagram after the start-stop speed is optimized in the present invention;

[0039] Fig.11 This is a simplified calculation principle diagram of the double S-shaped flexible control motion distance of the present invention;

[0040] Fig.12 is a schematic diagram of the RGV system of the present invention;

[0041] Fig.13 is a schematic diagram of a shape detection sensor bracket of the present invention;

[0042] Fig.14 It is a schematic diagram of the layout of the shape detection sensor of the present invention.

[0043] In the figure: 1. Three-dimensional shelf; 2. Warehouse robot; 3. Warehouse conveyor line; 4. RGV; 5. RGV maintenance platform; 6. Weighing sensor; 7. Warehouse entry and exit platform; 8. Laser unmanned forklift; 9. Fixed barcode scanner; 10. Shape detection sensor; 11. Warehouse conveyor line; 12. Shape detection sensor bracket; 13. Warning light; 14. Over-height detection photoelectric sensor; 15. Left over-width detection photoelectric sensor; 16. Right over-width detection photoelectric sensor; 17. First over-length detection photoelectric sensor Sensor; 18. Second over-length detection photoelectric sensor; 19. Detection trigger diffuse reflection photoelectric sensor; 20. First cargo protection photoelectric sensor; 21. Laser addressing sensor; 22. Lower incoming goods in place photoelectric sensor; 23. Barcode addressing sensor; 24. Slot deceleration trigger sensor; 25. Inter-vehicle communication module; 26. Upper incoming goods in place photoelectric sensor; 27. Mechanical anti-collision foam; 28. Second cargo protection photoelectric sensor; 29. ​​Motor rotary encoder; 30. Local control unit.

[0044] It should be noted that these drawings and textual descriptions are not intended to limit the conceptual scope of the present invention in any way, but are intended to illustrate the concept of the present invention for those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The following embodiments are used to illustrate the present invention but are not used to limit the scope of the present invention.

[0046] In the description of the present invention, it should be noted that the directions or positional relationships indicated by terms such as “upper”, “lower”, “front”, “back”, “left”, “right”, “vertical”, “inside” and “outside” are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention.

[0047] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0048] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0049] Embodiment 1

[0050] like Figure 1 As shown, the present invention provides an RGV multi-vehicle cooperative control method, including: a centralized vehicle group management strategy and a distributed vehicle-to-vehicle cooperative strategy; the centralized vehicle group management strategy includes setting up a vehicle group control center, and the vehicle group control center is responsible for the selection of task RGVs and the planning of task RGV paths; the distributed vehicle-to-vehicle cooperative strategy includes setting up an inter-vehicle communication module 25 and a local control unit for each RGV4; each RGV4 exchanges information with other RGV4 through the inter-vehicle communication module 25 to obtain the real-time status of all RGV4s, and controls the RGV4 speed coordination, anti-collision avoidance and task path avoidance individually through the local control unit; the vehicle group control center sends information to the inter-vehicle communication module 25, and the local control unit adjusts the speed and driving status of the corresponding RGV4 according to the information received by the inter-vehicle communication module 25.

[0051] Specifically, the upper vehicle group control center selects the best task vehicle and sends the destination workstation to the task vehicle; during local collaboration, the local control unit adjusts the speed and driving state of the corresponding RGV4 according to the information received by the inter-vehicle communication module 25. Finally, each vehicle adjusts its own speed and driving state by the local control unit according to the information from the vehicle group control center and the inter-vehicle network.

[0052] By setting up a swarm control center and configuring a vehicle-to-vehicle communication module 25 and a local control unit for each RGV4, this method achieves efficient collaborative control of RGV4. This structure not only enhances the immediacy of information exchange between RGV4s, but also enables each RGV4 to respond quickly according to real-time road conditions and other RGV4 states through dynamic adjustment of the local control unit, significantly improving the flexibility and safety of system operation. The centralized planning and task allocation capabilities of the swarm control center effectively optimize resource utilization, avoid the bottleneck problem caused by traditional reliance on a single central controller, and improve overall operational efficiency.

[0053] Furthermore, if Figure 1 As shown, the RGV multi-vehicle cooperative control method also includes a centralized vehicle group management strategy and a distributed vehicle-to-vehicle cooperative strategy.

[0054] The vehicle group control center specifically includes the following when selecting the task RGV and planning the task RGV path: the lower-level user issues the RGV inbound or outbound task, and the upper-level vehicle group control center first selects the optimal task vehicle based on the historical data and real-time position of each vehicle, then performs path search and completes path planning, and after completing path planning, sends the destination workstation task to the task RGV.

[0055] Because path planning and vehicle management involve a large amount of data and calculations, the selection of task vehicles and the planning of task paths are managed uniformly by the upper-level vehicle group control center. When the lower-level user issues a warehousing or outbound task, the upper-level vehicle group control center calculates the optimal task vehicle based on factors such as the historical fatigue load strength of each RGV4, the distance to the pickup station, and the obstruction of the running path. The upper-level vehicle group control center then issues the destination station task to the task vehicle.

[0056] Preferably, the path planning of the centralized vehicle group management strategy uses the Astar path algorithm to search for the driving path of the RGV4. Furthermore, the search method of the Astar path algorithm adopts a dual parallel search, searching from the starting point and the end point simultaneously to each other, and terminating the search in advance if an overlapping point is encountered, otherwise, the search continues until the target point is found.

[0057] Preferably, the distributed inter-vehicle coordination strategy is not controlled by the vehicle group control center, but is directly circulated locally between each RGV4, and communicates with the wireless inter-vehicle communication module 25 of RGV4 through the local inter-vehicle communication network to achieve automatic avoidance, speed control, and state control of the entire vehicle group.

[0058] Preferably, the local control unit stores the number, real-time working status, real-time position, real-time speed and target station occupancy of RGV4 in the form of standard status data blocks, and a wireless inter-vehicle communication module 25 is designed for each RGV4, so each RGV4 can directly read the status data blocks of other RGV4 through the wireless inter-vehicle communication module 25 to obtain the real-time status of all RGV4. This communication method does not pass through the vehicle group control center, but directly circulates locally between each RGV4 vehicle, ensuring the real-time, reliability and stability of the data. Through these data, the RGV4 vehicle group can realize the deceleration of the safe distance, the early avoidance of the vehicle on the planned path, the automatic speed control following, the emergency anti-collision braking and other scheduling and safety measures.

[0059] By adopting a cluster management method that combines a centralized swarm management strategy with a distributed vehicle-to-vehicle collaboration strategy, the coordinated scheduling and control of the swarm control center and the vehicle local control unit is achieved, greatly improving the operating efficiency and system robustness.

[0060] Embodiment 2

[0061] like Figure 1-6 As shown, based on the first embodiment, the centralized vehicle group management strategy is mainly implemented in the overall vehicle group. According to the planned operation path, the historical operation data of each vehicle, and the real-time operation data, the optimal task vehicle and task path are calculated and selected to achieve the balance of vehicle group load and the optimization of task path.

[0062] The basic process of the traditional Astar path algorithm (i.e., A-Star algorithm, a conventional algorithm in this field, which will not be described in detail here) is to expand outward from the starting point in sequence until a continuous coordinate path that can reach the target location is searched, which has extremely strong adaptability.

[0063] Based on the traditional Astar path algorithm, it is improved to a dual parallel search, that is, searching from the starting point and the end point simultaneously. If an overlapping point is encountered, the search is terminated in advance, otherwise the target point is searched. At the same time, due to the immutability and unidirectionality of the RGV track path, the RGV occlusion cost factor, RGV avoidance cost factor and task path overlap cost factor are introduced on the basis of the traditional search path, and the search path continues to maintain the optimal convergence to the target point. In the actual search, the starting point is defined as the highest priority of the traversal set, and the priority of the nth node in the points to be traversed can be expressed as:

[0064] f(n)=g(n)+h(n)+o(n)+a(n)+l(n)

[0065] Among them: f(n) is the comprehensive priority of node n. When the system selects the next node to be traversed, it will select the node with the highest comprehensive priority; g(n) is the cost of node n from the starting point; h(n) is the estimated cost of node n from the end point, that is, the heuristic function of path traversal; o(n) is the RGV occlusion cost of node n. This factor represents the waiting cost when the node has a working RGV; a(n) is the RGV avoidance cost of node n. This factor represents the avoidance cost of the standby RGV when the node has a standby RGV; l(n) is the task path overlap cost of node n. This factor represents the queuing passage cost when the node overlaps with other task paths.

[0066] For the heuristic function h(n), in the extreme case, when its value is always 0, the priority of traversing point n will be determined by g(n) and environmental factors, and the algorithm becomes the Dijkstra algorithm; if h(n) is always less than or equal to the cost from node n to the end point, the traversal process can definitely traverse the shortest path, but the algorithm will traverse more nodes, resulting in increased time; if h(n) is exactly equal to the cost from node n to the end point, the traversal process will take the least time to find the best path, but because it is difficult to accurately calculate the distance from the end point in the optimal path in advance, this is not possible in all scenarios; if the value of h(n) is greater than the cost from node n to the end point, the traversal process cannot guarantee the shortest path, but the traversal time will be shortened; in another extreme case, if h(n) is much larger than g(n), h(n) is dominant at this time, which becomes the best priority search algorithm. Therefore, in actual scenarios, the speed and accuracy of the algorithm can be controlled by adjusting the heuristic function, which can be more flexible to adapt to different project requirements.

[0067] There are two main situations in dual parallel search, such as Figure 2 and Figure 3 As shown:

[0068] Ⅰ. When there is a unique optimal path between the starting point and the end point, if the starting point of the path is defined as a and the end point is b, then the path planning problem is to find the expression of S(a,b) in the map. When the coincidence point during parallel search is C, then case Ⅰ is:

[0069] S(a,b)=S(a,C)+S(C,b)

[0070] In this case, each end only needs to search half of the path, which will result in overlapping points, eliminating the time of searching S(a, C) or S(C, b) separately, significantly reducing the search time.

[0071] Ⅱ. When there is more than one equivalent optimal path between the starting point and the end point, each end of the dual parallel search may not necessarily search the same optimal path. There is a certain probability of searching two independent optimal paths. Define case Ⅱ: the feasible points of path 1 include D, and the feasible points of path 2 include E. Then case Ⅱ is:

[0072] S(a,b)=S(a,D)+S(D,b)=S(a,E)+S(E,b)

[0073] In this case, the parallel search at both ends has a certain probability and will not produce overlapping points, and the path search time is similar to that of the traditional Astar path algorithm. Therefore, the improved dual parallel search can make full use of more computing resources and reduce the search time while maintaining the calculation quality.

[0074] After the map changes, you only need to modify the working coordinate system according to the map changes, such as adding new feasible points, feasible lines and other new map elements, and then you can use the same Astar algorithm to plan the path on the new map without adjusting the structure of the cluster scheduling algorithm. Find the optimal path or reach a given number of iterations, that is, output the optimal solution or near-optimal solution. On this basis, for different environmental features, you only need to add or subtract new constraints when the Astar algorithm searches for paths to maintain the judgment of the new environment. The algorithm is highly applicable and universal to different maps.

[0075] Embodiment 3

[0076] like Figure 1-6 As shown, based on the first embodiment, the distributed inter-vehicle coordination strategy mainly realizes automatic avoidance, speed control, and state control of the entire vehicle group through the local inter-vehicle communication network of RGV after receiving the task vehicle information from the vehicle group control center.

[0077] The inter-vehicle communication network between RGV vehicles is established. By designing a standard data block for data exchange in each RGV controller and cooperating with the inter-vehicle communication module, the vehicle data can be directly communicated in the inter-vehicle communication network. Each RGV is assigned a unique ID for identification. The schematic diagram of the RGV vehicle body is shown in the figure. Figure 4-6 As shown, the first cargo protection photoelectric sensor 20 and the second cargo protection photoelectric sensor 28 protect the material box from exceeding the boundaries on both sides during transportation, ensuring the safety of transportation; the laser addressing sensor 21 can accurately detect the distance of the front vehicle, and the barcode addressing sensor 23 realizes positioning by real-time scanning of the two-dimensional code on the track. The two sensors cooperate to realize the double closed-loop positioning of the RGV vehicle position; the motor rotary encoder 29 and the barcode addressing sensor 23 cooperate to realize the double closed-loop detection of the RGV vehicle speed; the groove deceleration trigger sensor 24 realizes the automatic deceleration of the RGV vehicle when turning; the inter-vehicle communication module 25 builds an inter-vehicle communication network to connect each RGV individual, and also connects the vehicle group control center and the RGV individual; the lower incoming goods in place photoelectric sensor 22 and the upper incoming goods in place photoelectric sensor 26 ensure the precise and stable stop of the material box; the mechanical anti-collision foam 27 serves as the last barrier of mechanical anti-collision, and realizes the buffering of mechanical collision when the control program fails and the electrical anti-collision fails; the RGV local control unit 30 is responsible for the action control, speed control and external data interaction of the RGV unit.

[0078] like Figure 7As shown in the figure, when the vehicle group control center generates the task vehicle information, the RGV individual controller will determine whether it is a blocking vehicle. At this time, the RGVs in the vehicle group can be divided into three categories: task RGV, working RGV, and standby RGV. The task RGV realizes dual closed-loop positioning based on the laser addressing sensor and the barcode addressing sensor, and obtains the operation data of other vehicles in real time based on the vehicle-to-vehicle network communication, and realizes localized operation mode control and multi-stage warning for collision prevention based on the data of other vehicles. The working RGV relies on the vehicle-to-vehicle network communication to sort the waiting time of all tasks in the cluster and create task priorities; when running to the intersection where there is a conflict, it queues up and passes in turn according to the task priority; secondly, relying on the vehicle-to-vehicle network communication, the task coordinates along the way are segmented for overlap analysis, and the order of passing is determined locally based on the overlapping segments and the task priority and arrival time. The standby RGV mainly performs the avoidance task. After receiving the coordinates along the task route, the standby RGV first determines whether its current position is within its range; if it is within its range, the local control unit of the standby RGV starts to run the dockable coordinate selection program; the program first counts the unoccupied buffer coordinates (forks without task coordinate binding) and the non-task coordinates of the target rear workstation, and selects the optimal dockable coordinates from near to far; then, the avoidance task along the route coordinate binding is generated according to the docking coordinates. If there are other RGV vehicles along the task route, the processing flow is as described above; at the same time, the avoidance task priority is lower than the work task.

[0079] Distributed inter-vehicle collaboration strategies can realize localized scheduling of vehicles during operation. They are not completely dependent on the vehicle group control center and can realize normal operation of some system functions when the server fails, greatly improving the robustness of the overall system.

[0080] like Figure 8 As shown in the figure, the speed of each RGV is distributedly controlled by its independent controller, and the sources of speed instructions mainly include instructions from the vehicle group control center connected through industrial Ethernet and local operation data of other RGV vehicles connected to the inter-vehicle network communication module.

[0081] The vehicle group control center calculates and sends the vehicle number of the RGV to perform the task. After receiving the execution command, the task RGV first realizes the flexible start of the whole machine mechanical system with double S-shaped flexible start speed 1; the bar code addressing sensor and laser addressing sensor are used to realize the double closed-loop positioning of the real-time position and speed of each RGV; when the double closed-loop positioning detects that the distance between the front and rear vehicles is shortened to the "safe distance" range, the RGV controller controls the vehicle speed to reduce to the safe following speed 4, where the safe following speed 4 is equal to the current real-time dynamic speed of the front vehicle; when the distance between the two vehicles is further reduced to the "collision threshold When the distance between the front and rear vehicles is greater than the "safe distance", the RGV controller controls the vehicle speed to reduce to the emergency braking avoidance speed 5; on the other hand, when the double closed-loop positioning detects that the distance between the front and rear vehicles is greater than the "safe distance", the RGV controller controls the vehicle speed to run at a straight uniform speed 2; in this case, if the slot deceleration sensor is triggered, the RGV controller controls the vehicle speed to run at the preset cornering speed 3; when the double closed-loop positioning detects that the task vehicle has arrived near the target workstation, the RGV controller will adjust all speed modes to the double S-shaped flexible stop speed 6, so as to achieve flexible and precise stopping of the entire mechanical system.

[0082] Among them, the double S-type flexible start speed 1 and the double S-type flexible stop speed 6 are precisely controlled by the local control unit in conjunction with the digital frequency converter and the motor encoder, and the drive module adopts a dual-motor parallel drive. In terms of drive algorithm, the traditional trapezoidal uniform acceleration and uniform deceleration start and stop has a large impact on the mechanical system because of the mutation points in its speed curve. In order to optimize the mechanical impact problem during start and stop, this solution optimizes the speed control algorithm of the drive motor and adopts the optimized double S-type flexible start and stop control.

[0083] like Fig. 9 and Fig.10 As shown in the figure, in the traditional trapezoidal drive algorithm, there are sharp points in the speed curve, which leads to mutation points in the acceleration curve, which will cause serious mechanical vibration and impact when the RGV is moving with heavy load. Therefore, the key to optimizing the drive model is to improve the mutation points in the acceleration curve. When the speed curve is optimized to a continuously changing curve, its first-order derivative, that is, the acceleration curve, can eliminate the mutation points and become a continuous curve.

[0084] Here we assume that the double S-shaped velocity curve function is:

[0085] (t)) = at + bt 2

[0086] Then its first-order derivative is:

[0087] v′(t)=3at+2bt

[0088] Bring in the initial conditions of the start and end key points:

[0089] v(0)==0

[0090] v(A)=C

[0091] v(0)=0

[0092] v(A)=0

[0093] From this, we can find the values ​​of parameters a and b:

[0094]

[0095] Then the S-type speed curve function is:

[0096]

[0097] Then add the uniform speed segment function to obtain the final optimized double S-shaped flexible speed control function. In this way, the acceleration changes continuously without mutation points, solving the jerk problem in traditional trapezoidal speed control.

[0098] The movement distance calculation of the optimized double S-type flexible control can be obtained by integrating its speed curve over time. Since the acceleration and deceleration processes are completely symmetrical, the calculation of its movement distance can be simplified to a rectangular area such as Fig.11 As shown, the specific expression is as follows:

[0099]

[0100] In this way, the speed function and movement distance function under the double S-type flexible control mode are completely obtained. Based on this functional relationship, this scheme realizes the fast and smooth double S-type flexible start-stop control of the RGV mechanical system.

[0101] Embodiment 4

[0102] The present invention further provides an RGV multi-vehicle cooperative control device, wherein the RGV multi-vehicle cooperative control method provided in the above embodiment is applied when the RGV multi-vehicle cooperative control device is working, including:

[0103] Three-dimensional shelf 1, used for stacking boxes.

[0104] Warehouse robot 2, used for transporting boxes.

[0105] Inbound conveyor line 3, a conveyor line for warehousing into three-dimensional shelves.

[0106] The outbound conveyor line 11 is an outbound conveyor line that leaves the three-dimensional shelf.

[0107] The detection module is used to detect the information of the material box.

[0108] Specifically, the RGV cluster is mainly used in the front-end transportation part of the intelligent warehouse. Figure 12-14 As shown, it includes a three-dimensional shelf 1 for stacking material boxes; a storage robot 2 moves the material boxes from the incoming conveyor line 3 to the storage location of the three-dimensional shelf 1; a high-speed RGV 4 is looped around to realize the transfer of material boxes between the incoming conveyor line 3, the inbound and outbound platform 7, and the outbound conveyor line 11; the inbound and outbound platform 7 is equipped with a weighing sensor 6 and a shape detection sensor 10 to realize overweight detection and shape over-limit detection of the material boxes delivered by the laser unmanned forklift 8 to ensure that the specifications of the incoming materials meet the requirements and avoid safety hazards; the fixed barcode scanner 9 on the inbound and outbound platform 7 realizes the automatic generation and binding of the material flow ID of the material box, and realizes the digital traceability of the materials; and it is equipped with an independent RGV maintenance platform 5, which does not affect the operation of the entire system when a single RGV needs to be shut down for maintenance. The schematic diagram of the shape detection sensor 10 is shown as follows Fig.13 As shown, it mainly includes an over-height detection photoelectric sensor 14 to detect the over-height of the material box, a left-side over-width detection photoelectric sensor 15 to detect the over-width of the left side of the material box, and a right-side over-width detection photoelectric sensor 16 to detect the over-width of the right side of the material box; when the material box passes the detection to trigger the diffuse reflection photoelectric sensor 19, the trigger program starts timing, the first over-length detection photoelectric sensor 17 and the second over-length detection photoelectric sensor 18 together form a plane detection, detect the time when the material box passes the shape detection sensor bracket 12, and then calculate the length of the material box in combination with the transportation speed, and then realize the detection of whether the length of the material box is overlong. When any group of tests fails, the alarm light 13 will sound and light alarm, and the conveyor line will automatically return the material box. Through these sensor combinations, the automatic detection of the three-dimensional dimensions of the material box appearance can be realized to avoid the impact of the shape exceeding the limit on safe transportation.

[0109] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0110] The above description is only a preferred embodiment of the present invention, and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technician familiar with this patent can make some changes or modifications to equivalent embodiments of equivalent changes by using the technical content suggested above without departing from the scope of the technical solution of the present invention. The implementation scheme in the above embodiment can also be further combined or replaced. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of the solution of the present invention.

Claims

1. A RGV multi-vehicle cooperative control method, characterized in that: include: Centralized vehicle group management strategy and distributed vehicle-to-vehicle collaboration strategy; The centralized vehicle group management strategy includes setting up a vehicle group control center, which is responsible for selecting task RGVs and planning task RGV paths; The distributed inter-vehicle coordination strategy includes providing an inter-vehicle communication module (25) and a local control unit for each RGV (4); each RGV (4) exchanges information with other RGVs (4) through the inter-vehicle communication module (25) to obtain the real-time status of all RGVs (4), and controls the speed coordination, anti-collision avoidance and task path avoidance of the RGVs (4) individually through the local control unit; The vehicle group control center sends information to the inter-vehicle communication module (25), and the local control unit adjusts the speed and driving state of the corresponding RGV (4) according to the information received by the inter-vehicle communication module (25).

2. The RGV multi-vehicle cooperative control method according to claim 1 is characterized in that: The vehicle group control center specifically includes the following when selecting the task RGV (4) and planning the task RGV (4) path: the lower-level user issues the RGV (4) inbound or outbound task, and the upper-level vehicle group control center first selects the optimal task vehicle based on the historical data and real-time position of each vehicle, then performs path search and completes path planning, and after completing path planning, sends the destination workstation task to the task RGV (4).

3. The RGV multi-vehicle cooperative control method according to claim 2 is characterized in that: The path planning uses the Astar path algorithm to search for the driving path of the RGV (4).

4. The RGV multi-vehicle cooperative control method according to claim 3 is characterized in that: The Astar path algorithm adopts a dual parallel search method, searching from the starting point and the end point simultaneously toward each other. If an overlapping point is encountered, the search is terminated in advance, otherwise, the search is continued until the target point is found.

5. The RGV multi-vehicle cooperative control method according to claim 1 is characterized in that: The distributed inter-vehicle coordination strategy is not controlled by the vehicle group control center, but is directly circulated locally between each RGV (4), and communicates with the wireless inter-vehicle communication module (25) of the RGV (4) through the local inter-vehicle communication network to achieve automatic avoidance, speed control, and state control of the entire vehicle group.

6. The RGV multi-vehicle cooperative control method according to claim 5 is characterized in that: The local control unit stores the number, real-time working status, real-time position, real-time speed and workstation occupancy status of the RGV (4) in the form of a standard status data block, and each RGV (4) can directly read the status data blocks of other RGVs (4) through the wireless inter-vehicle communication module (25) to obtain the real-time status of all RGVs (4).

7. An RGV multi-vehicle cooperative control device, characterized in that: When the device is working, an RGV multi-vehicle collaborative control method as described in any one of claims 1-6 is applied.

8. The RGV multi-vehicle cooperative control device according to claim 7, characterized in that: Also includes: Three-dimensional shelf (1), used for stacking material boxes; Warehouse robot (2), used for transporting boxes; A storage conveyor line (3), a conveyor line for storing goods into the three-dimensional shelf (1); An outbound conveyor line (11), an outbound conveyor line (11) that leaves the three-dimensional shelf (1); The detection module is used to detect the information of the material box.

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