Unmanned aerial vehicle collaborative transportation and communication system

Abstract

The invention provides an unmanned aerial vehicle collaborative transportation and communication system, which comprises a cloud server, and is characterized in that the cloud server is connected with a transportation vehicle and an auxiliary module thereof, a transportation unmanned aerial vehicle and an auxiliary module thereof, and a storage cabinet and an auxiliary module thereof; the transport vehicle and the auxiliary module thereof comprise a transport vehicle; a communication module I, a positioning module I, a display module I, a control module I and a data processing module I are mounted on the transport vehicle; the transportation unmanned aerial vehicle and the auxiliary module thereof comprise a transportation unmanned aerial vehicle, a communication module II, a positioning module II, a control module II and a data processing module II; and the storage cabinet and the auxiliary module thereof comprise a storage cabinet, a communication module III, a positioning module III, a display module III and a data processing module III. According to the invention, the cooperative operation capability of the unmanned aerial vehicle in the transportation process can be improved, and the stability and real-time performance of the communication system can be enhanced, thereby promoting the application of the unmanned aerial vehicle technology in wider fields.

Description

Technical Field

[0001] The present invention belongs to the field of logistics and transportation technology, and specifically relates to a drone-coordinated transportation and communication system. Background Art

[0002] In recent years, drone technology has rapidly developed, finding widespread application in a variety of fields, including military, agriculture, logistics, and disaster relief. The portability, flexibility, and efficiency of drones make them a crucial tool for modern transportation and communications. In the express logistics industry in particular, drone applications offer new solutions for improving transportation efficiency and reducing operating costs. In complex environments, the operational capabilities of a single drone are limited, leading to the collaborative operation of drones and trucks becoming a research hotspot. By integrating multiple drones, transportation systems can achieve greater coverage, higher efficiency, and the ability to perform more complex transport tasks. Collaborative drone systems leverage the respective strengths of drone and truck transportation, enabling them to collaborate and divide labor based on mission requirements, thereby optimizing resource allocation and improving overall operational efficiency.

[0003] With the rapid development of e-commerce and logistics industries, the existing traditional logistics transportation methods that rely on ground transportation are easily restricted by the physical state of the ground road network in terms of ensuring the timeliness of logistics distribution. For example, logistics transport trucks can only travel on the ground road network, and once the traffic flow of the ground road network exceeds its capacity, the induced traffic congestion will slow down the efficiency and cost of vehicle transportation of goods. The drone collaborative transportation system can effectively solve this problem. As shown in the attached figure Figure 1 As shown, in areas with traffic congestion, drones can be used to transport goods to meet users' immediate needs, reduce ground traffic pressure, and reduce environmental pollution.

[0004] Communication systems play a crucial role in collaborative drone operations. Effective communication not only ensures information transfer between drones but also enables real-time interaction with ground control centers. While various drone transportation and communication solutions exist, most still lack interoperability, communication stability, and adaptability. For example, existing systems are susceptible to interference in complex environments, leading to information delays or loss, impacting mission efficiency. Furthermore, the lack of effective algorithms and mechanisms creates blind spots in task allocation and path planning for collaborative drone operations.

[0005] Therefore, developing an efficient and stable communication system is key to improving the collaborative transport capabilities of drones. This system not only improves the collaborative operation capabilities of drones during transportation, but also enhances the stability and real-time performance of the communication system, thereby promoting the application of drone technology in a wider range of fields. Summary of the Invention

[0006] The purpose of the present invention is to provide a drone-coordinated transportation and communication system to realize the transportation of goods, the receipt of goods, and the receipt of customer goods during transportation, and to transport them to other vehicles via drones to achieve fast delivery.

[0007] The purpose of the present invention is achieved through the following technical solutions:

[0008] A drone-coordinated transport and communication system includes: a cloud server, wherein the cloud server is respectively connected to a transport vehicle and its accessory modules, a transport drone and its accessory modules, and a storage cabinet and its accessory modules;

[0009] The transport vehicle and its auxiliary modules include a transport vehicle on which a communication module 1, a positioning module 1, a display module 1, a control module 1, and a data processing module 1 are installed;

[0010] The transport drone and its auxiliary modules include a transport drone, a communication module 2, a positioning module 2, a control module 2, and a data processing module 2;

[0011] The storage cabinet and its auxiliary modules include a storage cabinet, a third communication module, a third positioning module, a third display module, and a third data processing module.

[0012] Furthermore, the transport vehicle and the transport drone exchange information through the communication module 1 and the communication module 2; the position is determined through the positioning module 1 and the positioning module 2, thereby achieving positioning between the two and achieving position connection;

[0013] One of the transport vehicles is equipped with a plurality of transport drones;

[0014] The transport drone and the storage cabinet use the positioning module 2. The positioning module realizes the process of transporting goods from the transport drone to the storage cabinet. After transporting to the designated storage cabinet, the goods are placed in the storage cabinet through the communication module between the two.

[0015] The transport drone transports items from multiple storage cabinets;

[0016] The storage cabinet is used to receive items from multiple transport drones.

[0017] When the goods are placed in the storage cabinet, information can be sent to the customer's related equipment to receive the information, and then the customer can receive the goods stored in the storage cabinet; the customer sends the receiving information through the cloud server, and then goes to the storage cabinet to fill in the corresponding information or open the storage cabinet through the communication mode, thereby realizing the process of picking up the goods.

[0018] Furthermore, the method of using the system to transport items includes: a vehicle transportation process, a drone pickup process, a drone delivery process, and a customer pickup process;

[0019] The vehicle transportation process is a process in which the transport vehicle receives the corresponding information from the cloud server and then transports the items picked up from the storage and transportation center to the storage cabinet corresponding to its planned path;

[0020] The drone picking process is to place the transport drone on the transport vehicle and pick up the items in the transport vehicle. At this time, the data sent by the transport vehicle is used to grab the items in the transport vehicle and put them into the picking claw of the transport drone;

[0021] The drone delivery process is to grab the items to be transported by the picking claw, and then transport them to the corresponding storage cabinet through the data in the transport vehicle. The transport drone can transport items multiple times and can transport items to multiple different storage cabinets.

[0022] The customer picks up the goods in the process of sending a receipt message through the cloud server, and then goes to the storage cabinet to fill in the corresponding information or open the storage cabinet through the communication mode to pick up the goods.

[0023] The customer should have equipment with communication module, control module and display module to realize the process of picking up the goods.

[0024] Furthermore, a method for receiving and transporting items using the system includes: a process of receiving and transporting items in coordination with drones, which includes a process of a first customer placing goods in a first storage cabinet; a process of using a first transport drone to pick up the goods from the first storage cabinet; a process of the first transport drone transporting the goods to a transport vehicle; a process of a second transport drone transporting the goods to a second storage cabinet; a process of a second customer picking up the goods from the second storage cabinet; a process of a second transport drone picking up the goods from the transport vehicle; a process of the second transport drone transporting the goods to a second storage cabinet; and a process of a second customer picking up the goods from the second storage cabinet.

[0025] The first customer places the goods in the first storage cabinet. The cloud server receives the corresponding information and sends it to a nearby transport vehicle. The transport vehicle then sends the first transport drone to the first storage cabinet to pick up the goods. After the goods are picked up, the first transport drone returns to the transport vehicle, completing the transportation process.

[0026] The first customer places the goods in the first storage cabinet. The cloud server receives the corresponding information data and sends the information to the nearby transport vehicle that has pre-delivered the goods to the delivery address. The transport vehicle can then pick up the goods and transport them to the corresponding delivery address.

[0027] Furthermore, a method for receiving goods in transit using the system includes: a drone-assisted transport process for receiving goods in transit, wherein during vehicle transport, a first customer pre-transports the goods to a storage cabinet far away from the location, and the cloud server receives the information, and then the cloud server sends the information to a first transport vehicle located nearby, that is, the first transport vehicle dispatches a first transport drone to a safe location near the first customer to pick up the goods, and after the goods are picked up, the first transport drone transports the goods to the transport vehicle, and dispatches a second transport drone at a certain location to transport the goods to the second transport vehicle; at this time, the second transport vehicle pre-delivers the goods to the location where the first customer transported the goods, and after receiving the goods, it transports them, and after arriving near the transport location, dispatches a transport drone to transport the goods to the storage cabinet, that is, the first customer completes the delivery of the goods to the second customer, thereby realizing the rapid transportation of the customers' goods;

[0028] Among them, the first customer sends a message to transport goods. At this time, the cloud server receives this message. At this time, the first transport vehicle located near the first customer rushes to the vicinity of the first customer and dispatches the first transport drone to the first customer to receive the goods. After receiving the customer, the first transport drone transports the first customer's goods to the first transport vehicle. At this time, the previous transport route of the goods is continued. According to the calculation rules of the cloud server, after arriving at a certain location, the second transport drone is dispatched to transport the goods to the second transport vehicle. At this time, the customer's goods can be transported to a location near the second target customer by the second transport vehicle, and the third transport drone is dispatched to transport the goods to the storage cabinet. At this time, the second customer can go to the storage cabinet to pick up the goods, thus realizing the ability of fast delivery throughout the process.

[0029] After the first customer sends the shipping information, the cloud server receives the corresponding information data and sends the information to the nearby transport vehicle that has pre-delivered the goods to the delivery address. The transport vehicle can then pick up the goods and transport them to the corresponding delivery address.

[0030] Furthermore, during the UAV transportation process, the system obtains the three-dimensional position coordinates (x, y) and flight altitude (h) data in real time through the GPS module and barometer integrated in the transport UAV; at the same time, the communication module 2 carried by the UAV periodically accesses the airspace database maintained by the cloud server to download and update the no-fly zone coordinate range, altitude threshold (hmin ,h max ) and the scope, restricted time and altitude constraint dynamic information of temporary traffic control areas. These real-time acquired position, altitude and airspace control information constitute the core input of path planning;

[0031] Path planning adopts a hierarchical strategy and is collaboratively executed by the transport drone's data processing module and / or cloud server.

[0032] Furthermore, the upper-level global planning of the path planning is based on the starting and ending coordinates of the transportation task. The starting point based on the transportation task includes the transportation vehicle location, the storage cabinet location, and the customer location. Combined with the topography and airspace control static data obtained from the airspace database, a three-dimensional passable map is constructed through the grid method, and an improved ant colony algorithm is used on the map to generate a global optimal path framework.

[0033] Furthermore, the improved ant colony algorithm includes:

[0034] (1) Differentiated pheromone initialization: When the algorithm is initialized, different weight coefficients λ are set according to the road grade associated with the grid cells in the digital map, and the initial pheromone concentration τ ij (0) is calculated by formula (1):

[0035]

[0036] Among them, L max is the estimated global longest path distance, d ij is the Euclidean distance from node i to node j, and ε is a small constant to prevent zero;

[0037] (2) Dynamic path cost function: When the planned path approaches or enters a no-fly zone / restricted altitude zone, the system dynamically constructs a three-dimensional avoidance weight matrix W(x, y, h). The core function of this matrix is

[0038]

[0039] Among them, α is the penalty coefficient of the restricted area. The larger the value, the stricter the requirement for avoiding the restricted area. β is the height sensitivity factor. The control weight increases with the height deviation from the minimum allowed height h. m；n The decay rate of (x,y); h m；n (x,y) is the minimum flight altitude allowed at the current coordinate point (x,y) obtained from the airspace database;

[0040] When choosing a path, the expected value or heuristic information of an ant moving from node i to node j;

[0041] Pheromone concentration from node i to j is the reciprocal of the distance

[0042]

[0043] The improved path total cost function is updated as follows:

[0044]

[0045] Where η is the pheromone heuristic factor, which controls the influence of pheromone concentration on path selection; W ij is the avoidance weight W(x j ,y j ,h j ); μ is the no-fly avoidance factor, which controls the influence of the avoidance weight on path selection;

[0046] The larger the μ value, the more the algorithm tends to choose paths that are far away from restricted areas or meet height requirements;

[0047] (3) Highly layered reward: To further guide the drone to fly at a safe altitude, a highly layered reward function is introduced.

[0048]

[0049] Among them, k is the steep factor of the Sigmoid function; h safe It is the reference value of the set safe cruising altitude;

[0050] In the path evaluation stage (such as when calculating the total length or cost of the path), the R(h) function value is superimposed on the path evaluation index, and the total cost is multiplied by the average R(h) or the minimum R(h); R(h) is close to h safe is close to 1 when h is much lower or much higher than h safe When the temperature is close to 0, the guidance for safe altitude flight is strengthened;

[0051] (4) Local obstacle avoidance in the lower layer of path planning: When the transport UAV flies according to the global path planned in the upper layer, its onboard visual camera scans the flight path ahead in real time. Once it detects a sudden obstacle or a dynamic risk invading the preset safety boundary, it immediately triggers a local obstacle avoidance algorithm based on the artificial potential field method. This algorithm regards the target point, i.e., the next path point, as the source of attraction and the obstacle as the source of repulsion.

[0052] The gravitational field function is

[0053]

[0054] The repulsive field function is

[0055]

[0056] If ρ obs(q)≤ρ0Calculate U according to the above formula rep (q), otherwise U rep (q) is 0;

[0057] Among them, q is the current position of the UAV, ρ goal (q) is the distance to the target point, ρ obs (q) is the distance to the nearest obstacle, ρ0 is the obstacle influence distance threshold, ξ and η are gain coefficients;

[0058] The direction of the resultant force on the drone is the obstacle avoidance direction, as shown in formula (8).

[0059]

[0060] According to the direction of the resultant force, the control module 2 dynamically adjusts the flight attitude of the transport UAV and generates new local waypoint coordinates through the PID controller to achieve instant detour;

[0061] After obstacle avoidance is completed, the transport drone automatically returns to the latest global path planned by the upper layer or requests a new path update.

[0062] The beneficial effects of the present invention are:

[0063] The present invention realizes the joint delivery of goods by drones and vehicles through the collaboration of drones; transports and receives goods through drones; realizes that during the transportation process, drones can receive goods, thereby realizing rapid delivery and improving transportation efficiency; realizes various forms of collaborative transportation through cloud servers. Since each device has a built-in communication module, information can be transmitted between each other; the positioning module can realize positioning between projects, thereby quickly reaching the location of the corresponding device and realizing accurate transportation of goods; the data processing modules on the vehicle and cloud server side can realize rapid data processing, and the processing module built into the vehicle can realize rapid data exchange with the cloud server side. It can also realize rapid data processing between vehicles and drones; the display module can view the location information of the transport drone in real time, and the customer's device can view the transportation information of the goods; the storage cabinet can display whether the goods have been picked up.

[0064] The transport vehicles and transport drones of the present invention are both equipped with built-in control modules, that is, the vehicle can control its onboard drone. When the drone of another vehicle is needed, a temporary instruction can be issued to the other transport vehicle to control the drone of the other vehicle to land and deliver the goods to the vehicle; the transport drone can control the storage cabinet, open the storage cabinet, place the goods, and then control the closing of the storage cabinet.

[0065] The present invention improves the convergence speed by performing global path planning through improving the ant colony path planning algorithm, enhances the directionality of path search by introducing a guiding function, and improves the initial concentration distribution method and pheromone concentration update strategy of pheromones. The idea of ​​survival of the fittest is incorporated into the ant colony algorithm, which strengthens the influence of the optimal path as a whole and prevents the UAV from falling into a local optimal solution.

[0066] The present invention uses multi-sensor collaborative control technology to achieve multi-dimensional status monitoring and dynamic control of drones, formulate intelligent solutions for emergencies that may occur during flight, and effectively ensure the safety and reliability of drone transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Attachment Figure 1 It is a schematic diagram of a pure truck transportation system and a drone collaborative transportation system in the background technology.

[0068] Attachment Figure 2 It is a structural schematic diagram of the transport vehicle and its auxiliary modules of the present invention.

[0069] Attachment Figure 3 It is a structural schematic diagram of the transport UAV and its auxiliary modules of the present invention.

[0070] Attachment Figure 4 It is a structural diagram of the storage cabinet and its auxiliary modules of the present invention.

[0071] Attachment Figure 5 This is a schematic diagram of the article transportation process coordinated by drones of the present invention.

[0072] Attachment Figure 6 This is the process intention of receiving and transporting items coordinated by the drone of the present invention.

[0073] Attachment Figure 7 This is the intention of the drone collaborative transportation process of receiving goods during transportation in the present invention.

[0074] In the accompanying drawings: 1. Cloud server;

[0075] 2. Transport vehicle and its auxiliary modules, 2-1. Transport vehicle, 2-2. Communication module 1, 2-3. Positioning module 1, 2-4. Display module 1, 2-5. Control module 1, 2-6. Data processing module 1;

[0076] 3. Transport UAV and its auxiliary modules, 3-1. UAV, 3-2. Communication module 2, 3-3. Positioning module 2, 3-4. Control module 2, 3-5. Data processing module 2;

[0077] 4. Storage cabinet and its auxiliary modules, 4-1. Storage cabinet, 4-2. Communication module 3, 4-3. Positioning module 3, 4-4. Display module 3, 4-5. Data processing module 3;

[0078] 5. Customers. DETAILED DESCRIPTION

[0079] The present invention will be further described below with reference to the accompanying drawings.

[0080] The present invention provides a UAV-coordinated transportation and communication system, as shown in the attached Figure 2-4 As shown, it includes: a cloud server 1, which is respectively connected to a transport vehicle and its accessory module 2, a transport drone and its accessory module 3, and a storage cabinet and its accessory module 4;

[0081] As attached Figure 2 As shown, the transport vehicle and its accessory modules 2 include a transport vehicle 2-1, which is equipped with a communication module 2-2, a positioning module 2-3, a display module 2-4, a control module 2-5, and a data processing module 2-6. The communication module 2-2 can realize communication functions with transport drones, cloud servers, storage cabinets, other transport vehicles, etc. The positioning module 2-3 can locate the vehicle's position information and accurately determine the position during information exchange. The display module 2-4 can view relevant display information in real time, such as the flight position of the transport drone and the positioning information of other vehicles. The control module 2-5 can realize control of the transport drone and related vehicle controls. The data processing module 2-6 can realize rapid data processing, such as information such as receiving goods during transportation.

[0082] The transport vehicle 2-1 can be loaded with a simple magnetic charging plate, which can automatically absorb and charge the drone when it lands.

[0083] The transport drone and its accessory modules 3 include a transport drone 3-1, a communication module 3-2, a positioning module 3-3, a control module 3-4, and a data processing module 3-5. The communication module 3-2 enables communication with transport vehicles, cloud servers, storage cabinets, and other transport vehicles. The positioning module 3-3 locates the drone's position, enabling precise location determination during information exchange. The control module 3-4 controls the storage cabinets and drone-related permissions. The data processing module 3-5 rapidly processes data, such as information on cargo received during transport.

[0084] In this embodiment, the drone's sensor module is integrated for local obstacle avoidance. When an obstacle is detected intruding into the safety boundary, an emergency avoidance strategy based on an artificial potential field algorithm is triggered to ensure the feasibility of the transport mission. The structure of the transport vehicle and storage cabinet is optimized to meet the requirements of the drone transport mission, effectively improving the efficiency of drone transport mission execution.

[0085] The storage cabinet and its accessory modules 4 include a storage cabinet 4-1, a communication module 4-2, a positioning module 4-3, a display module 4-4, and a data processing module 4-5. The communication module 4-2 enables communication with transport drones, cloud servers, and clients. The positioning module 4-3 locates the cabinet's location, enabling precise location determination during information exchange. The display module 4-4 allows real-time viewing of relevant information, such as whether goods have been picked up and the cabinet's vacancy status. The data processing module 4-5 enables rapid data processing, such as obtaining pickup information, cabinet vacancy information, and the placement location of received goods.

[0086] The storage cabinet 4-1 and the unloading process of the drone can adopt a modular design and a standard interface design to adapt to different cargo requirements. It supports the rapid loading and unloading of standard express boxes and improves transportation efficiency.

[0087] In this embodiment, the transport vehicle 2-1 and the transport drone 3-1 exchange information through the communication module 1 2-2 and the communication module 2 3-2. In this process, the relevant data in the transport vehicle 1 is transmitted to the transport drone 2 through the communication module, and the position is determined by the positioning module 1 2-3 and the positioning module 2 3-3, thereby achieving positioning between the two and achieving position connection;

[0088] One transport vehicle 1 is equipped with multiple transport drones 2; the two can realize mutual positioning and transportation through the communication module and positioning module;

[0089] When encountering an area with unstable or poor signal, a special transport vehicle 1 equipped with a relay base station can be used to achieve signal output with the unmanned transport aircraft 3;

[0090] The transport drone 3-1 and the storage cabinet 4-1 are connected via the positioning module 2 3-3 and the positioning module 4-3 to realize the process of transporting goods from the transport drone 3-1 to the storage cabinet 4-1. After transporting to the designated storage cabinet 4-1, the goods are placed in the storage cabinet 4-1 through the communication module between the two.

[0091] The transport drone 3-1 transports items from multiple storage cabinets 4-1;

[0092] The storage cabinet 4 - 1 can also receive items from multiple transport drones 2 .

[0093] When the goods are placed in the storage cabinet 3, information can be sent to the relevant equipment of the customer 5 to realize the reception of the information, and then the customer 5 can receive the goods stored in the storage cabinet 4-1; wherein the customer 5 sends the receiving information through the cloud server 1, and goes to the storage cabinet 4-1 to fill in the corresponding information or open the storage cabinet 4-1 through the communication mode, thereby realizing the process of picking up the goods.

[0094] As attached Figure 5 As shown, the method of using the system to transport items includes: vehicle transportation process, drone pickup process, drone delivery process, and customer pickup process;

[0095] The vehicle transportation process is a process in which the transport vehicle 2-1 receives the corresponding information from the cloud server 1 and then transports the items picked up from the storage and transportation center to the storage cabinet corresponding to its planned path;

[0096] The drone picking process is to place the transport drone 3-1 on the transport vehicle 2-1 and pick up the items in the transport vehicle 2-1. At this time, the data sent by the transport vehicle 2-1 is used to grab the items in the transport vehicle 2-1 and put them into the picking claw of the transport drone 3-1. Among them, the transport vehicle 2-1 can realize charging, control, and information processing of the transport drone 3-1, and the transport vehicle 2-1 can be equipped with multiple transport drones 3-1.

[0097] The drone delivery process is to grab the item to be transported by the picking claw and then transport it to the corresponding storage cabinet 4-1 through the data in the transport vehicle 2-1. The transport drone 3-1 can transport items multiple times and can transport items to multiple different storage cabinets 4-1. If the fixed position remains unchanged, the position can be located by the cloud server, and the positioning module is not required.

[0098] The customer pick-up process is that the customer 5 receives information sent by the cloud server 1, and then goes to the storage cabinet 4-1 to fill in the corresponding information or open the storage cabinet 4-1 through the communication mode, thereby realizing the process of picking up the goods;

[0099] Among them, customer 4 should have equipment with a communication module, a control module, and a display module to realize the process of picking up the goods.

[0100] As attached Figure 6As shown, the method for receiving and transporting items using the system includes: a process of receiving and transporting items in cooperation with drones, which includes a process of a first customer placing goods in a first storage cabinet 4-1; a process of using a first transport drone 3-1 to pick up goods from the first storage cabinet 4-1; a process of the first transport drone 3-1 transporting goods to a transport vehicle 2-1; a process of a second transport drone 3-1 transporting goods to a second storage cabinet 4-1; a process of a second customer 5 picking up goods from the second storage cabinet 4-1; a process of a second transport drone 3-1 picking up goods from the transport vehicle 2-1; a process of the second transport drone 3-1 transporting goods to the second storage cabinet 4-1; a process of a second customer 5 picking up goods from the second storage cabinet 4-1;

[0101] Among them, the first customer 5 places the goods in the first storage cabinet 4-1. At this time, the cloud server 1 receives the corresponding information and sends it to the nearby transport vehicle. At this time, the transport vehicle sends the first transport drone 3-1 to the first storage cabinet 4-1 to pick up the goods. After the goods are picked up, the first transport drone 3-1 returns to the transport vehicle 2-1, completing the transportation process;

[0102] The first customer 5 places the goods in the first storage cabinet 4-1, and the cloud server 1 receives the corresponding information data. At this time, the information is sent to the nearby transport vehicle 2-1 that has pre-delivered the goods to the delivery address of the goods. The transport vehicle 2-1 can then pick up the goods and then transport the goods to the corresponding delivery address.

[0103] As attached Figure 7 As shown, the method of using the system to receive goods during transportation includes: a drone collaborative transportation process for receiving goods during transportation, during the vehicle transportation process, at this time, the first customer 5 pre-transports the goods to a storage cabinet 4-1 far away from the location, at this time the cloud server 1 receives the information, and then the cloud server 1 sends the information to the first transportation vehicle 2-1 located nearby, that is, the first transportation vehicle 2-1 dispatches the first transportation drone 3-1 to a safe place near the first customer 5 to pick up the goods, after the pickup is completed, the first transportation drone 3-1 transports the goods to the transportation vehicle 2-1, and dispatches the second transportation drone 3-1 at a certain location to transport the goods to the second transportation vehicle 2-1; at this time, the second transportation vehicle 2-1 pre-delivers the goods to the place where the first customer 5 transports the goods, and after it receives the goods, it transports them, and after arriving near the transportation location, dispatches the transportation drone 3-1 to transport the goods to the storage cabinet, that is, the first customer 5 completes the transportation of the goods to the second customer 5, realizing the rapid transportation of the customers' goods;

[0104] Among them, the first customer 5 sends a message about transporting goods. At this time, the cloud server 1 receives the message. At this time, the first transport vehicle 2-1 located near the first customer 5 rushes to the vicinity of the first customer 5 and dispatches the first transport drone 3-1 to the first customer 5 to receive the goods. After receiving the customer, the first transport drone 3-1 transports the first customer 5's goods to the first transport vehicle 2-1; at this time, the previous transport route of transporting goods is continued. According to the calculation rules of the cloud server 1, after arriving at a certain location, the second transport drone 3-1 is dispatched to transport the goods to the second transport vehicle 2-1. At this time, the customer's goods can be transported to a location near the second target customer 5 by the second transport vehicle 2-1, and the third transport drone 3-1 is dispatched to transport the goods to the storage cabinet. At this time, the second customer 5 can go to the storage cabinet to pick up the goods, thereby realizing the ability of fast delivery throughout the process;

[0105] After the first customer 5 sends the shipping information, the cloud server 1 receives the corresponding information data and sends the information to the nearby transport vehicle that has pre-delivered the goods to the delivery address of the goods. The transport vehicle 2-1 can then pick up the goods and transport the goods to the corresponding delivery address.

[0106] During the transportation process of the UAV 3-1 of the present invention, the system obtains the three-dimensional position coordinates (x, y) and flight altitude (h) data in real time through the GPS module and barometer integrated in the transport UAV; at the same time, the communication module 2 3-2 carried by the UAV periodically accesses the airspace database maintained by the cloud server 1, downloads and updates the no-fly zone coordinate range, altitude threshold (h min ,h max ) and the scope, restricted time and altitude constraint dynamic information of temporary traffic control areas. These real-time acquired position, altitude and airspace control information constitute the core input of path planning;

[0107] The path planning adopts a hierarchical strategy and is collaboratively executed by the data processing module 3-5 of the transport drone 3-1 and / or the cloud server 1.

[0108] Furthermore, the upper-level global planning of the path planning is based on the starting and ending coordinates of the transportation task. The starting point of the transportation task includes the transportation vehicle location, the storage cabinet location, and the customer location. Combined with static data such as topography and airspace control (no-fly zones, restricted altitude zones) obtained from the airspace database, a three-dimensional traversable map is constructed through a grid method (the grid resolution can be set according to accuracy requirements, for example, 10m×10m). An improved ant colony algorithm is used on the map to generate a global optimal path framework.

[0109] In this embodiment, the improved ant colony algorithm includes:

[0110] (1) Differentiated pheromone initialization: When the algorithm is initialized, different weight coefficients λ are set according to the road grade associated with the grid cells in the digital map, and the initial pheromone concentration τ ij (0) is calculated by formula (1):

[0111]

[0112] Among them, L max is the estimated global longest path distance, d ij is the Euclidean distance from node i to node j, and ε is a small constant to prevent zero (such as ε = 0.01). This design makes the algorithm more inclined to explore paths above high-level roads (usually meaning more open and less disturbed airspace) in the early stage.

[0113] (2) Dynamic path cost function: When the planned path approaches or enters a no-fly zone / restricted altitude zone, the system dynamically constructs a three-dimensional avoidance weight matrix W(x, y, h). The core function of this matrix is

[0114] W(x,y,h)=1+α·exp(-β·(hh m；n (x,y)) 2 ) (2)

[0115] Among them, α is the penalty coefficient of the restricted area. The larger the value, the stricter the requirement for avoiding the restricted area. β is the height sensitivity factor. The control weight increases with the height deviation from the minimum allowed height h. m；n The decay rate of (x,y); h m；n (x,y) is the minimum flight altitude allowed at the current coordinate point (x,y) obtained from the airspace database;

[0116] When choosing a path, the expected value or heuristic information of an ant moving from node i to node j;

[0117] Pheromone concentration from node i to j is the reciprocal of the distance

[0118]

[0119] The improved path total cost function is updated as follows:

[0120]

[0121] Where η is the pheromone heuristic factor, which controls the influence of pheromone concentration on path selection; W ij is the avoidance weight W(x j ,y j ,h j ); μ is the no-fly avoidance factor, which controls the influence of the avoidance weight on path selection;

[0122] The larger the μ value, the more the algorithm tends to choose paths that are far away from restricted areas or meet height requirements;

[0123] (3) Highly layered reward: To further guide the drone to fly at a safe altitude, a highly layered reward function is introduced.

[0124]

[0125] Among them, k is the steep factor of the Sigmoid function; h safe It is the reference value of the set safe cruising altitude;

[0126] In the path evaluation stage (such as when calculating the total length or cost of the path), the R(h) function value is superimposed on the path evaluation index, and the total cost is multiplied by the average R(h) or the minimum R(h); R(h) is close to h safe is close to 1 when h is much lower or much higher than h safe When the temperature is close to 0, the guidance for safe altitude flight is strengthened;

[0127] (4) Local obstacle avoidance at the lower level of path planning: When the transport drone 3-1 flies according to the global path planned at the upper level, its onboard visual camera scans the flight path ahead in real time. Once it detects a sudden obstacle (such as a flying bird or a temporary construction crane) or a dynamic risk (such as another drone that suddenly appears) invading the preset safety boundary (e.g., a range of 5 meters), it immediately triggers a local obstacle avoidance algorithm based on the artificial potential field method. This algorithm regards the target point, i.e., the next path point, as a source of attraction and the obstacle as a source of repulsion.

[0128] The gravitational field function is

[0129]

[0130] The repulsive field function is

[0131]

[0132] If ρ obs (q)≤ρ0Calculate U according to the above formula rep (q), otherwise U rep (q) is 0;

[0133] Among them, q is the current position of the UAV, ρ goal (q) is the distance to the target point, ρ obs (q) is the distance to the nearest obstacle, ρ0 is the obstacle influence distance threshold, ξ and η are gain coefficients;

[0134] The direction of the resultant force on the drone is the obstacle avoidance direction, as shown in formula (8).

[0135]

[0136] According to the direction of the resultant force, the control module 2 3 - 4 dynamically adjusts the flight attitude (pitch, roll, yaw angle) of the transport UAV 3 - 1 through the PID controller and generates new local waypoint coordinates to achieve instant detour;

[0137] After the obstacle avoidance is completed, the transport drone 3-1 automatically returns to the latest global path planned by the upper layer or requests a new path update.

[0138] This structure forms an intelligent path control system of "global planning (improved ant colony algorithm) generation framework - real-time monitoring by sensors - dynamic risk triggering (artificial potential field method) local response - return to the global".

[0139] The present invention constructs an intelligent dynamic task allocation mechanism in the UAV transportation system, and realizes automated task scheduling based on multi-dimensional parameters by integrating the task management platform and the UAV status monitoring module. The system first conducts a hierarchical assessment of the remaining battery power of the UAV and sets a battery power ≥ 60% as the threshold for executing long-distance tasks. When the battery power of the UAV is higher than this threshold, it is given priority to matching long-distance transportation tasks that require cross-regional flight, and the optimal task assignment plan is generated based on its current location and endurance. For emergency order scenarios, the system establishes a real-time priority queue to dynamically adjust task weights to ensure that idle UAVs (defined as devices with a battery power ≥ 30% and no tasks in transit) can be dispatched immediately for emergency tasks.

[0140] Multi-sensor monitoring is performed during drone transportation, and the drone's position is tracked in real time through GPS positioning; the battery voltage sensor triggers a low-battery alarm and automatically returns to recharge after the mission is completed; the integrated gyroscope and barometer detect the drone's attitude deviation in real time, triggering the PID controller to adjust the motor speed to ensure smooth flight, and initiate emergency landing in the event of an abnormality to avoid accidents; when the drone's battery level is less than 10% or a malfunction occurs, the cloud server automatically migrates unfinished tasks to neighboring drones and optimizes the task sequence.

[0141] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A UAV-coordinated transportation and communication system, characterized in that: include: A cloud server (1), wherein the cloud server (1) is respectively connected to a transport vehicle and its accessory module (2), a transport drone and its accessory module (3), and a storage cabinet and its accessory module (4); The transport vehicle and its auxiliary module (2) include a transport vehicle (2-1), on which a communication module (2-2), a positioning module (2-3), a display module (2-4), a control module (2-5), and a data processing module (2-6) are installed; The transport drone and its auxiliary modules (3) include a transport drone (3-1), a second communication module (3-2), a second positioning module (3-3), a second control module (3-4), and a second data processing module (3-5); The storage cabinet and its auxiliary module (4) include a storage cabinet (4-1), a communication module three (4-2), a positioning module three (4-3), a display module three (4-4), and a data processing module three (4-5).

2. The UAV-coordinated transportation and communication system according to claim 1, characterized in that: The transport vehicle (2-1) and the transport drone (3-1) exchange information via the communication module 1 (2-2) and the communication module 2 (3-2) therebetween, determine their positions via the positioning module 1 (2-3) and the positioning module 2 (3-3), and thereby achieve positioning between the two and achieve position connection; One transport vehicle (2-1) is equipped with a plurality of transport drones (3-1); The transport drone (3-1) and the storage cabinet (4-1) are connected via positioning module 2 (3-3) and positioning module (4-3) to realize the process of transporting goods from the transport drone (3-1) to the storage cabinet (4-1). After transporting to the designated storage cabinet (4-1), the goods are placed in the storage cabinet (4-1) via the communication module between the two. The transport drone (3-1) transports items from a plurality of storage cabinets (4-1); The storage cabinet (4-1) is used to receive items from multiple transport drones (3-1); When the goods are placed in the storage cabinet (4-1), information can be sent to the relevant equipment of the customer (5) to realize the reception of the information, and then the customer (5) receives the goods stored in the storage cabinet (4-1); wherein the customer (5) sends the receiving information through the cloud server (1), and enters the corresponding information at the storage cabinet (4-1) or realizes the opening of the storage cabinet (4-1) through the communication mode, thereby realizing the process of picking up the goods.

3. The UAV-coordinated transportation and communication system according to claim 1 or 2, characterized in that: Methods for transporting items using the system include: vehicle transport process, drone pickup process, drone delivery process, and customer pickup process; The vehicle transportation process is a process in which the transport vehicle (2-1) receives corresponding information from the cloud server (1) and then transports the items picked up from the storage and transportation center to the storage cabinet corresponding to its planned path; The drone picking process is to place the transport drone (3-1) on the transport vehicle (2-1) and pick up the items in the transport vehicle (2-1). At this time, the data sent by the transport vehicle (2-1) is used to grab the items in the transport vehicle (2-1) to the picking claw of the transport drone (3-1). The drone delivery process is to grab the items to be transported by the picking claw, and then transport them to the corresponding storage cabinet (4-1) through the data in the transport vehicle (2-1), wherein the transport drone (3-1) can transport multiple items, and the transport drone (3-1) can transport items to multiple different storage cabinets (4-1); The process of picking up goods by the customer (5) is that the customer (5) receives the information sent by the cloud server (1), and then goes to the storage cabinet (4-1) to fill in the corresponding information or open the storage cabinet (4-1) through the communication mode, thereby realizing the process of picking up the goods; The customer (5) should have a device with a communication module, a control module, and a display module to realize the process of picking up the goods.

4. The UAV-coordinated transportation and communication system according to claim 1 or 2, characterized in that: The method for receiving and transporting items using the system includes: a process of receiving and transporting items in cooperation with drones, which includes a process of placing goods from a first customer to a first storage cabinet (4-1); a process of using a first transport drone (3-1) to pick up goods from the first storage cabinet (4-1); a process of the first transport drone (3-1) transporting goods to a transport vehicle (2-1); a process of the second transport drone (3-1) transporting goods to a second storage cabinet (4-1); a process of the second customer (5) picking up goods from the second storage cabinet (4-1); a process of the second transport drone (3-1) picking up goods from the transport vehicle (2-1); a process of the second transport drone (3-1) transporting goods to the second storage cabinet (4-1); and a process of the second customer (5) picking up goods from the second storage cabinet (4-1). Among them, the first customer (5) places the goods in the first storage cabinet (4-1). At this time, the cloud server (1) receives the corresponding information and sends it to the nearby transport vehicle. At this time, the transport vehicle sends the first transport drone (3-1) to the first storage cabinet (4-1) to pick up the goods. After picking up the goods, the first transport drone (3-1) returns to the transport vehicle (2-1), completing the transportation process; The first customer (5) places the goods in the first storage cabinet (4-1), and the cloud server (1) receives the corresponding information data. At this time, the information is sent to the nearby transport vehicle (2-1) that has pre-delivered the goods to the delivery address of the goods. The transport vehicle (2-1) can then pick up the goods and transport them to the corresponding delivery address.

5. The UAV-coordinated transportation and communication system according to claim 1 or 2, characterized in that: The method for receiving goods during transportation using the system includes: a drone-assisted transportation process for receiving goods during transportation, during the vehicle transportation process, the first customer (5) pre-transports the goods to a storage cabinet (4-1) far away from the location, and the cloud server (1) receives the information, and then the cloud server (1) sends the information to the first transportation vehicle (2-1) located nearby, that is, the first transportation vehicle (2-1) dispatches the first transportation drone (3-1) to a safe location near the first customer (5) to pick up the goods, after the first transportation drone (3-1) transports the goods to the transportation vehicle (2-1), and dispatches the second transportation drone (3-1) at a certain location to transport the goods to the second transportation vehicle (2-1); at this time, the second transportation vehicle (2-1) pre-delivers the goods to the location where the first customer (5) transported the goods, and after receiving the goods, it transports them, and after arriving near the transportation location, dispatches the transportation drone (3-1) to transport the goods to the storage cabinet, that is, the first customer (5) completes the transportation of the goods to the second customer (5), realizing the rapid transportation of the customer's goods; Among them, the first customer (5) sends a message about transporting goods, and the cloud server (1) receives the message. At this time, the first transport vehicle (2-1) located near the first customer (5) rushes to the vicinity of the first customer (5) and dispatches the first transport drone (3-1) to the first customer (5) to receive the goods. After receiving the customer, the first transport drone (3-1) transports the goods of the first customer (5) to the first transport vehicle (2-1); at this time, the transport path of the previous transport of goods is continued. According to the calculation rules of the cloud server (1), after arriving at a certain location, the second transport drone (3-1) is dispatched to transport the goods to the second transport vehicle (2-1). At this time, the customer's goods can be transported to a location near the second target customer (5) by the second transport vehicle (2-1), and the third transport drone (3-1) is dispatched to transport the goods to the storage cabinet. At this time, the second customer (5) can go to the storage cabinet to pick up the goods, so as to realize the ability of fast delivery in the whole process; After the first customer (5) sends the shipping information, the cloud server (1) receives the corresponding information data and sends the information to the nearby transport vehicle that has pre-delivered the goods to the delivery address of the goods. The transport vehicle (2-1) can then pick up the goods and transport them to the corresponding delivery address.

6. The UAV-coordinated transportation and communication system according to claim 1 or 2, characterized in that: During the transportation process of the UAV (3-1), the system obtains the three-dimensional position coordinates (x, y) and flight altitude (h) data in real time through the GPS module and barometer integrated in the transport UAV; at the same time, the communication module 2 (3-2) carried by the UAV periodically accesses the airspace database maintained by the cloud server (1) to download and update the coordinate range of the no-fly zone and the altitude threshold (h min ,h max ) and the scope, restricted time and altitude constraint dynamic information of temporary traffic control areas. These real-time acquired position, altitude and airspace control information constitute the core input of path planning; The path planning adopts a hierarchical strategy and is collaboratively executed by the data processing module (3-5) of the transport drone (3-1) and / or the cloud server (1).

7. The UAV-coordinated transportation and communication system according to claim 6, characterized in that: The upper-level global planning of the path planning is based on the starting and ending coordinates of the transportation task. The starting point of the transportation task includes the transportation vehicle location, the storage cabinet location, and the customer location. Combined with the topography and airspace control static data obtained from the airspace database, a three-dimensional traversable map is constructed through the grid method, and an improved ant colony algorithm is used on the map to generate a global optimal path framework.

8. The UAV-coordinated transportation and communication system according to claim 7, characterized in that: The improved ant colony algorithm includes: (1) Differentiated pheromone initialization: When the algorithm is initialized, different weight coefficients λ are set according to the road grade associated with the grid cells in the digital map, and the initial pheromone concentration τ ij (0) is calculated by formula (1): Among them, L max is the estimated global longest path distance, d ij is the Euclidean distance from node i to node j, and ε is a small constant to prevent zero; (2) Dynamic path cost function: When the planned path approaches or enters a no-fly zone / restricted altitude zone, the system dynamically constructs a three-dimensional avoidance weight matrix W(x, y, h). The core function of this matrix is ​​W(x, y, h) = 1 + α·exp(-β·(hh) m；n (x,y)) 2 )(2) Among them, α is the penalty coefficient of the restricted area. The larger the value, the stricter the requirement for avoiding the restricted area. β is the height sensitivity factor. The control weight increases with the height deviation from the minimum allowed height h. m；n The decay rate of (x,y); h m；n (x,y) is the minimum flight altitude allowed at the current coordinate point (x,y) obtained from the airspace database; When choosing a path, the expected value or heuristic information of an ant moving from node i to node j; The pheromone concentration η from node i to j ij is the reciprocal of the distance The improved path total cost function is updated as follows: Where η is the pheromone heuristic factor, which controls the influence of pheromone concentration on path selection; W ij is the avoidance weight W(x j ,y j ,h j ); μ is the no-fly avoidance factor, which controls the influence of the avoidance weight on path selection; The larger the μ value, the more the algorithm tends to choose paths that are far away from restricted areas or meet height requirements; (3) Highly layered reward: To further guide the drone to fly at a safe altitude, a highly layered reward function is introduced. Among them, k is the steep factor of the Sigmoid function; h safe It is the reference value of the set safe cruising altitude; In the path evaluation stage (such as when calculating the total length or cost of the path), the R(h) function value is superimposed on the path evaluation index, and the total cost is multiplied by the average R(h) or the minimum R(h); R(h) is close to h safe is close to 1 when h is much lower or much higher than h safe When the temperature is close to 0, the guidance for safe altitude flight is strengthened; (4) Local obstacle avoidance in the lower layer of path planning: When the transport UAV (3-1) flies according to the global path planned in the upper layer, its onboard visual camera scans the flight path ahead in real time. Once it detects a sudden obstacle or a dynamic risk invading the preset safety boundary, it immediately triggers a local obstacle avoidance algorithm based on the artificial potential field method. This algorithm regards the target point, i.e., the next path point, as a source of attraction and the obstacle as a source of repulsion. The gravitational field function is The repulsive field function is If ρ obs (q)≤ρ0Calculate U according to the above formula rep (q), otherwise U rep (q) is 0; Among them, q is the current position of the UAV, ρ goal (q) is the distance to the target point, ρ obs (q) is the distance to the nearest obstacle, ρ0 is the obstacle influence distance threshold, ξ and η are gain coefficients; The direction of the resultant force on the drone is the obstacle avoidance direction, as shown in formula (8). According to the direction of the resultant force, the control module 2 (3-4) dynamically adjusts the flight attitude of the transport UAV (3-1) and generates new local waypoint coordinates through the PID controller to achieve instant detour; After the obstacle avoidance is completed, the transport UAV (3-1) automatically returns to the latest global path planned by the upper layer or requests a new path update.

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