Roof low-altitude intelligent unmanned aerial vehicle logistics distribution system and architecture thereof

Abstract

The invention provides a roof low-altitude intelligent unmanned aerial vehicle logistics distribution system and a framework thereof, and the system comprises a parapet wall which is arranged on a roof and serves as the boundary of the system; an automatic storage and taking logistics cabinet is arranged in the cabinet body, and a storage area is arranged in the cabinet body and used for storing and taking logistics packages; a start-stop area is arranged on one side of the automatic access logistics cabinet and used for starting and stopping the unmanned aerial vehicle; a start-stop point identifier and a stop induction device sensor are arranged in the start-stop area and are used for assisting the unmanned aerial vehicle to start and stop in the start-stop area; an elevator and a sliding rail are further arranged in the start-stop area and used for putting the logistics parcels carried by the unmanned aerial vehicle into the corresponding positions of the storage area; grounding wires are arranged on the automatic storing and taking logistics cabinet, the sliding rails and the start-stop area. A camera is arranged on the parapet wall and is used for monitoring the interior of the system; the system is also provided with a power supply module for supplying power to each device in the system. The architecture is used for realizing the system.

Description

Technical Field

[0001] The present invention relates to an unmanned aerial vehicle logistics distribution system and its architecture, in particular to a low-altitude intelligent unmanned aerial vehicle logistics distribution system on a roof and its architecture. Background Art

[0002] This section merely provides background information related to the present disclosure and is not necessarily prior art.

[0003] With the booming development of e-commerce, the logistics industry is facing huge challenges and opportunities. The traditional logistics model has many problems in the "last 100 meters" distribution, such as low distribution efficiency, insufficient security, and privacy leakage risks. At the same time, the disposal of packaging waste in reverse logistics has also increased environmental pressure. Therefore, it is particularly important to develop a new low-altitude economic intelligent logistics system.

[0004] Drones can expand some scenarios that conventional human delivery cannot reach. W airspace is uncontrolled airspace below 120m (registration and reporting required), which has many application scenarios. At present, there is also rigid demand, such as mountainous areas, scenic spots, parks, industrial parks, and rural areas. It can be used as an effective capacity supplement, especially to alleviate the problem of capacity shortage in cities during peak capacity periods.

[0005] At present, similar technologies related to low-altitude economic W airspace intelligent logistics facilities and systems are mainly in the early stages, with the focus on drone logistics route planning, simple drone lockers and energy storage integrated devices. The system design focuses on the use of logistics companies, or simple experimental structures, and is not clear enough in site selection and design.

[0006] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0007] Purpose of the invention: The technical problem to be solved by the present invention is to provide a rooftop low-altitude intelligent drone logistics distribution system and its architecture in response to the deficiencies of the prior art.

[0008] In order to solve the above technical problems, the present invention discloses a rooftop low-altitude intelligent drone logistics distribution system and its architecture, the system comprising:

[0009] The parapet set on the roof serves as the boundary of the system; an automatic storage and retrieval logistics cabinet is arranged inside the parapet, and a storage area is arranged inside the automatic storage and retrieval logistics cabinet for storing and retrieving logistics packages; a start-stop area is arranged on one side of the automatic storage and retrieval logistics cabinet for starting and stopping the drone; the start-stop area is provided with start-stop point markings and a stop induction device sensor for assisting the drone to start and stop in the start-stop area; the start-stop area is also provided with an elevator and a slide rail for dropping the logistics packages carried by the drone into the corresponding position of the storage area; the automatic storage and retrieval logistics cabinet, the slide rail and the start-stop area are all provided with grounding wires; a camera is arranged on the parapet for monitoring the inside of the system; the system is also provided with a power module to supply power to various devices in the system.

[0010] Furthermore, the system is also provided with a reverse logistics device, and the reverse logistics device comprises:

[0011] A storage box for storing disassembled logistics parcel boxes, wherein the storage box is provided with a storage opening, through which a user puts the disassembled logistics parcel box into the storage box; an automatic packer is provided on one side of the storage box for compressing the disassembled logistics parcel box; a friction roller is provided on the other side of the automatic packer for leveling the compressed logistics parcel box; a binding rope extractor is provided on the other side of the friction roller for packing the leveled logistics parcel box; a storage table is provided on the other side of the binding rope extractor for storing the packed logistics parcel box;

[0012] The reverse logistics device is also provided with a circuit control board for controlling the reverse logistics device and communicating with the system.

[0013] Furthermore, the logistics package carried by the drone is placed in a corresponding position in the storage area, specifically including:

[0014] The elevators and slide rails in the start-stop area automatically allocate corresponding positions in the storage area according to the type of the logistics package, and deliver the package according to the allocated position, as follows:

[0015] The sizes of the corresponding positions in the storage area are divided into three types: large, medium and small. At the same time, the logistics packages are identified and divided into three types: large, medium and small according to their sizes. The packages are matched and assigned positions according to the types.

[0016] Furthermore, the power supply module adopts a photoelectric complementary form, specifically including:

[0017] The power module includes: an AC / DC integrated machine and a solar panel; wherein,

[0018] The AC / DC integrated machine includes an AC 220V mains power module, a DC 48V to 220V inverter module and a battery pack; the solar panel is connected to the battery pack to provide solar power and power the system. When the battery pack is low on power, the AC 220V mains power module is turned on and the AC 220V mains power is used to power the system.

[0019] Furthermore, the shutdown induction device sensor includes:

[0020] Radar system and infrared sensor; wherein the radar system adopts laser radar, and performs 360-degree environmental depth information detection through mechanical scanning or phased array. The radar system obtains the distance information of the environment around the UAV in real time to provide data support for obstacle avoidance decisions; the infrared sensor is used to assist the radar system to detect and identify obstacles at night or in low-light environments.

[0021] Further, the assisting the drone to start and stop in the start and stop area specifically includes:

[0022] Combined with the data of the radar system and infrared sensor in the parking induction device sensor, the optimal flight path of the UAV is calculated through a dynamic path planning method, and the landing and taxiing routes of the UAV are adjusted in real time while avoiding obstacles, as follows:

[0023] Training a deep neural network model to predict traffic flow and road condition changes, and combining GPS data with data from a radar system and infrared sensors in the parking induction device sensor to locate the drone and identify obstacles;

[0024] Train the path selection model, using reinforcement learning strategy to continuously iterate and optimize path selection in a simulated environment;

[0025] According to the trained deep neural network model and path selection model, the path planning scheme is adjusted in real time to assist the UAV to start and stop in the start and stop area.

[0026] Furthermore, the logistics package is identified, specifically including:

[0027] Converting the color image of the logistics package into a grayscale image;

[0028] Noise removal, using filters to remove image noise;

[0029] Edge detection, using edge detection methods to highlight the boundaries of the logistics package;

[0030] Size normalization, adjust the image to a uniform size;

[0031] Use feature point detector to extract key points and calculate descriptors;

[0032] Use convolutional neural networks (CNNs) to learn hierarchical feature representations from raw images;

[0033] Build deep learning models for end-to-end recognition and classification;

[0034] According to the detected boundary size of the logistics package, combined with perspective transformation or camera calibration method, the actual size of the object is estimated;

[0035] Complete the identification of the logistics package.

[0036] Furthermore, the solar power supply specifically includes:

[0037] The solar panel adopts a dual-axis tracking system solar panel to automatically track the sun's trajectory and maximize the sunlight receiving area. The dual-axis tracking system solar panel includes a solar panel, a bracket, an azimuth rotator, an altitude rotator, a base, a drive motor, a transmission mechanism, a photoelectric sensor, a sundial, a GPS and a control module;

[0038] The solar panel is installed on the bracket, and the bracket is connected to the base through an azimuth rotator and an altitude rotator; the drive motor and the transmission mechanism drive the azimuth rotator to control the solar panel to rotate around the vertical axis; the drive motor and the transmission mechanism drive the altitude rotator to control the solar panel to rotate around the horizontal axis;

[0039] The photoelectric sensor, sundial and GPS detect the position and light intensity of the sun in real time; the control module controls the driving motor.

[0040] Furthermore, the drone is provided with sensors and communication devices, and the system is provided with a ground station for coordinating multiple drones.

[0041] The present invention also proposes an architecture of a rooftop low-altitude intelligent drone logistics distribution system, which is used to implement the above-mentioned system, including:

[0042] The system is divided into infrastructure layer, perception layer, management and service component layer and software and hardware platform layer;

[0043] The infrastructure layer includes: inter-sensory base station, low-altitude economic satellite, ground-based augmentation system, LAEL micro-weather station, TOC start-stop service station, TOB start-stop service station, charging station and maintenance point;

[0044] The perception layer includes outdoor location perception gateway, image perception gateway, weather perception gateway, aircraft power perception, channel perception gateway, outdoor altitude perception, emergency support gateway, LAEL facility busy and idle perception, aircraft automatic return module, aircraft collision avoidance coordination module, aircraft temperature sensor module and LEAL imaging gateway.

[0045] Management and service component layer, including logistics service interface, express service interface, takeaway service interface, other API interfaces, digital twin city module, large model component module, 3D digital earth component, airspace editing and visualization module, IoT middle platform component, weather service component, flight situation sharing component, authentication and authorization component, data access module, data storage module, data calculation module and data service module;

[0046] The software platform layer specifically includes the digital twin large screen module, the flight service applet module, the airspace management module, the aircraft supervision service client module, the warning and rescue assistance module, the anti-UAV monitoring system module, the low-altitude safety control software platform module, the air traffic flow management module, the waterway management module, the flight insurance management module, the aircraft management module and the operator management module.

[0047] Beneficial effects:

[0048] (1) Significantly improve logistics and distribution efficiency:

[0049] This application realizes efficient delivery of the "last 100 meters" of logistics through the close cooperation between drones and rooftop smart facilities. Drones can directly deliver goods from logistics stations or takeaway stores to the user's rooftop smart logistics pick-up cabinet, avoiding delays caused by ground traffic congestion and inefficient personnel delivery in traditional logistics.

[0050] (2) Enhance logistics security and privacy protection:

[0051] Users do not need to go downstairs to pick up their parcels, which reduces contact with strangers and reduces the risk of item theft and privacy leakage. At the same time, the rooftop smart logistics lockers use identity authentication technology to ensure that only legitimate users can pick up parcels, further improving the security of the logistics process.

[0052] (3) Optimize resource allocation and space utilization:

[0053] Using rooftop space as the installation point for logistics facilities not only saves ground resources, but also avoids the potential impact of traditional logistics delivery cabinets on ground transportation, fire safety and garden landscape. In addition, through the design of intelligent distribution of express cabinets and reverse logistics boxes, the optimal allocation of logistics resources is achieved.

[0054] (4) Promote environmental protection and energy conservation and emission reduction:

[0055] The design of the reverse logistics box enables the effective collection of logistics waste such as recyclable packaging bags and boxes, and returns them to the recycling point through drones, reducing the workload of garbage disposal and promoting the recycling of resources. At the same time, the photovoltaic complementary power supply module makes full use of the solar energy resources on the roof to achieve green and low-carbon energy supply.

[0056] (5) Improve user experience and satisfaction:

[0057] Users can pick up or send parcels without leaving the building, which greatly improves the convenience of logistics services and user satisfaction. At the same time, the intelligent delivery device system can automatically allocate express lockers according to the size of the items, avoiding delivery failures or delays caused by size mismatch.

[0058] (6) Enhance system flexibility and scalability:

[0059] The intelligent logistics facilities and drone systems in this application have strong flexibility and scalability. With the continuous advancement of technology and the growth of logistics needs, it is easy to upgrade system hardware, optimize software algorithms or add new functional modules to meet more diverse logistics needs.

[0060] (7) Reduce operating costs and labor costs:

[0061] The automated delivery of drones reduces the reliance on human delivery personnel and reduces labor costs. At the same time, through intelligent management and optimized resource allocation, the operating costs of logistics companies can be further reduced and their overall competitiveness can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments, and the above and / or other advantages of the present invention will become more clear.

[0063] Figure 1 It is a schematic diagram of the system in the present invention.

[0064] Figure 2 It is a schematic diagram of the overall architecture of the system in the present invention.

[0065] Figure 3 It is a schematic diagram of the reverse logistics device configuration.

[0066] In the figure, 1 is a parapet, 2 is an automatic storage and retrieval logistics cabinet, 3 is an automatic start and stop drone, 4 is a lift, 5 is a slide rail, 6 is a storage area, 7 is a start and stop area, 8 is a grounding wire, 9 is a grounding wire, 10 is a grounding wire, 11 is a start and stop point mark, 12 is a camera, 13 is a stop induction device sensor, 14 is a power module; 21 is a storage box, 22 is a shelf, 23 is an automatic packer, 24 is a strapping rope extractor, 25 is a storage table, 26 is a friction roller, and 27 is a circuit control board. DETAILED DESCRIPTION

[0067] Based on the defects of the prior art, the overall design concept of the present invention is as follows:

[0068] First, solve the problem of construction location design: most of the traditional logistics is to deliver goods to the community (park), and traditional logistics does not solve the problem of the last 100 meters, including the safety of goods, privacy protection, storage space, and environmental sanitation. At present, logistics, express delivery, and take-out generally adopt the method of on-site placement, often in the existing space, often stolen goods, animals bite, affecting the appearance, traditional logistics delivery cabinets need to occupy land, affecting ground transportation and fire safety, and destroying the integrity of the original garden landscape design. In the future low-altitude economic environment, the focus will be on using rooftop space as a resource for low-altitude logistics. The consignee and the consignor only need to reach the low-altitude infrastructure on the rooftop to complete the work. The use of rooftop resources is designed according to the area of ​​the building. Usually, buildings within 20,000 square meters can reserve 9 square meters of space, and if the building is 50,000 square meters, 16 square meters of space can be reserved.

[0069] Secondly, it solves the end-to-end manual logistics distribution problem. It uses drones to directly deliver goods from logistics sites or takeaway stores to residential buildings, business buildings, and campus rooftops on intelligent infrastructure, reducing human contact and having greater applicability for closed campuses and parks. The drones are stored in express cabinets at the delivery end, and the intelligent picking robots automatically pick up the items and deliver them to the user end through drones. The user end is set on the rooftop of the building, and the user can get the items without leaving the building, solving the privacy and logistics security issues of the last 100 meters of logistics delivery and pickup.

[0070] Finally, the reverse logistics problem was solved. Traditional logistics and delivery use a large number of packaging bags and boxes, which users need to disassemble before discarding into the trash can. In fact, secondary garbage sorting is required, which increases the workload. Drone logistics can recycle packaging bags and boxes and reduce the empty load of drone logistics.

[0071] The technical solution proposed by the present invention is as follows:

[0072] A low-altitude intelligent drone logistics distribution system on the rooftop, such as Figure 1As shown, a complete logistics distribution system is installed on the roof of the building. The system includes five core modules: drone parking apron, intelligent delivery device, intelligent logistics collection and delivery cabinet, reverse logistics box, and intelligent supporting facilities.

[0073] The building roofs include all floors of residential buildings, office buildings, public facilities, etc. that have flat facilities and are accessible to people and have anti-fall safety facilities, including but not limited to parapet walls 1.

[0074] Drone parking apron: Inside the apron parapet 1, there are elevators 4 and slide rails 5. The elevator 4 communicates with the drone 3 through the parking induction device sensor 13 to ensure that the drone 3 stops accurately.

[0075] The installation method of the drone logistics facility is to change the installation method of the logistics cabinet 2, install the logistics cabinet 2 on the roof, located in the start-stop area 7, and through the drone induction device sensor 13 and the start-stop point mark 11, the drone 3 can achieve logistics delivery without landing on the ground.

[0076] Intelligent delivery device: The system can automatically allocate express cabinets 2 according to the type of logistics boxes or packages, and automatically deliver them to the corresponding express cabinets 2. The allocation method is based on the matching of the box volume (types L, M, S) and the size of logistics items (three types of L, M, S), effectively avoiding the problem of mismatch between delivery cabinets and items.

[0077] Smart Logistics Pickup and Delivery Cabinet: Located in storage area 6, users can pick up or send items in the smart logistics pick-up and delivery cabinet on the rooftop through identity verification. If the item is not picked up in the cabinet for more than 72 hours, the system will automatically retrieve it through a drone and return it to the sender by the original route to ensure the timely circulation of the items.

[0078] Reverse logistics box: specially used to collect recyclable packaging bags, packaging boxes and other logistics waste. The drone can carry these items on the return trip to reduce the empty load rate and promote the recycling of resources.

[0079] Intelligent supporting facilities: including power module 14, camera 12, rainproof module and lightning protection grounding wires 8, 9, 10. The power module adopts a photoelectric complementary form, consisting of an AC / DC integrated machine (including an AC 220V mains module, a DC 48V to 220V inverter module and a battery pack) and a solar panel to ensure continuous and stable operation of the system.

[0080] Solar panels cover the express cabinets and store energy efficiently through lithium iron phosphate energy storage modules.

[0081] The AC / DC integrated machine detects that the battery pack is low on power and automatically turns on the 220V mains power supply, thereby fully utilizing the rooftop solar energy and achieving uninterrupted power supply.

[0082] Through the above system, the present invention:

[0083] (1) Significantly improve logistics and distribution efficiency:

[0084] This application realizes efficient delivery of the "last 100 meters" of logistics through the close cooperation between drones and rooftop smart facilities. Drones can directly deliver goods from logistics stations or takeaway stores to the user's rooftop smart logistics pick-up cabinet, avoiding delays caused by ground traffic congestion and inefficient personnel delivery in traditional logistics.

[0085] (2) Enhance logistics security and privacy protection:

[0086] Users do not need to go downstairs to pick up their parcels, which reduces contact with strangers and reduces the risk of item theft and privacy leakage. At the same time, the rooftop smart logistics lockers use identity authentication technology to ensure that only legitimate users can pick up parcels, further improving the security of the logistics process.

[0087] (3) Optimize resource allocation and space utilization:

[0088] Using rooftop space as the installation point for logistics facilities not only saves ground resources, but also avoids the potential impact of traditional logistics delivery cabinets on ground transportation, fire safety and garden landscape. In addition, through the design of intelligent distribution of express cabinets and reverse logistics boxes, the optimal allocation of logistics resources is achieved.

[0089] (4) Promote environmental protection and energy conservation and emission reduction:

[0090] The design of the reverse logistics box enables the effective collection of logistics waste such as recyclable packaging bags and boxes, and returns them to the recycling point through drones, reducing the workload of garbage disposal and promoting the recycling of resources. At the same time, the photovoltaic complementary power supply module makes full use of the solar energy resources on the roof to achieve green and low-carbon energy supply.

[0091] (5) Improve user experience and satisfaction:

[0092] Users can pick up or send parcels without leaving the building, which greatly improves the convenience of logistics services and user satisfaction. At the same time, the intelligent delivery device system can automatically allocate express lockers according to the size of the items, avoiding delivery failures or delays caused by size mismatch.

[0093] (6) Enhance system flexibility and scalability:

[0094] The intelligent logistics facilities and drone systems in this application have strong flexibility and scalability. With the continuous advancement of technology and the growth of logistics needs, it is easy to upgrade system hardware, optimize software algorithms or add new functional modules to meet more diverse logistics needs.

[0095] (7) Reduce operating costs and labor costs:

[0096] The automated delivery of drones reduces the reliance on human delivery personnel and reduces labor costs. At the same time, through intelligent management and optimized resource allocation, the operating costs of logistics companies can be further reduced and their overall competitiveness can be improved.

[0097] The above-mentioned rooftop low-altitude intelligent drone logistics distribution method includes basic configuration scheme, optimized configuration scheme and advanced configuration scheme, which are as follows:

[0098] Embodiment: This embodiment provides a technical solution for a low-altitude intelligent drone logistics distribution system on the rooftop, aiming to achieve a high degree of coordination between drones and intelligent logistics facilities on the rooftop to meet the needs of large-scale and efficient logistics distribution.

[0099] Specific implementation:

[0100] Helipad system: The helipad and its ancillary equipment are made of environmentally friendly and weather-resistant polymer composite materials, and the surface is covered with solar panels to provide green and sustainable energy supplement for the entire system. When the drone is docked, it automatically completes power replenishment and flight data upload / download, which improves operational efficiency and reduces the need for manual intervention. The integrated radar and infrared sensors form an all-round three-dimensional obstacle avoidance system to ensure the safe flight and landing of the drone in the complex and changeable rooftop environment. Specifically, the radar system uses high-resolution laser radar to achieve 360-degree environmental depth information detection through mechanical scanning or phased array technology. The radar can obtain the distance information of the drone's surrounding environment in real time to provide data support for obstacle avoidance decisions. Infrared sensors are used to assist the radar system, especially at night or in low-light environments. Infrared sensors can detect temperature differences in the surrounding environment to identify potential obstacles. Combining the data of radar and infrared sensors, the obstacle avoidance algorithm calculates the optimal flight path of the drone to avoid collisions with obstacles. The obstacle avoidance algorithm also takes into account factors such as the drone's flight speed, wind direction, and wind speed to ensure the accuracy and real-time nature of obstacle avoidance decisions.

[0101] At the same time, AI algorithms are used for dynamic path planning to adjust the landing and taxiing routes of drones in real time to cope with temporary obstacles or changes that may appear on the roof. The core lies in the integration of deep learning models and real-time environmental perception systems. By training deep neural networks, the model can predict dynamic factors such as traffic flow and road conditions, and combine GPS data and sensor information to achieve high-precision positioning and obstacle identification. The algorithm adopts a reinforcement learning strategy to continuously iterate and optimize path selection in a simulated environment to find the optimal or suboptimal driving route. The system can adjust the path planning plan in real time according to user needs and current traffic conditions, effectively avoid congestion, and improve travel efficiency. In addition, the algorithm also has self-learning capabilities, can continuously adapt to new scenarios, and enhance the accuracy and robustness of planning.

[0102] Collaborative operation of multiple drones: The core lies in the integration of machine vision, path planning algorithms and wireless communication technology. The system uses machine vision to capture environmental information in real time, and combines high-precision map data to dynamically plan the optimal flight path for each drone. A distributed collaborative algorithm is used to achieve real-time information sharing and task allocation between drones to ensure efficient collaboration. The wireless communication module ensures the stability and real-time performance of data transmission, allowing multiple drones to flexibly respond to complex environments. The optimal path planning and task allocation of drones are achieved through an intelligent scheduling system. Drones maintain real-time synchronization through wireless communication to ensure the efficiency and accuracy of logistics distribution. The drone system is deeply integrated into the Internet of Things, and seamlessly connected with ground logistics facilities (such as smart warehouses, automatic sorting systems), urban traffic management systems, etc. Through big data analysis, the resource allocation of the entire logistics chain is optimized, and the intelligent management of the entire chain of goods from production to consumption is realized. In addition, drones can also serve as mobile sensors to collect urban environmental data and contribute to the construction of smart cities. Allow users to track order status in real time, make appointments for delivery services during specific time periods, and even participate in the planning of some delivery routes. By collecting user feedback, the service process is continuously optimized to provide personalized and customized logistics solutions.

[0103] like Figure 3 As shown, the reverse logistics device is configured as follows: an automatic folding or compression device is set up. After the recipient receives the express, the express box is disassembled and folded, and the box to be recycled is put into the storage box 21 through the storage port 22. The carton is compressed by the automatic packer 23, flattened by the friction roller 26, and packed by the binding rope extractor 24. The packed carton is placed on the storage table 25 and connected to the low-altitude logistics system through the circuit control board 27 to upload the operation status.

[0104] Smart delivery device upgrade: Upgrade the smart delivery device, add machine vision and artificial intelligence algorithms, and achieve more accurate logistics item identification and distribution. At the same time, it supports automatic identification and classification of multiple logistics boxes and package types.

[0105] The machine vision rules for automatic allocation are: first convert the color image to a grayscale image to reduce the processing complexity; noise removal: use filters (such as Gaussian filtering, median filtering) to remove image noise; edge detection: apply edge detection algorithms (such as Canny edge detector) to highlight the boundaries of objects; size normalization: adjust the image to a uniform size for subsequent processing; use feature point detectors such as SIFT, SURF, ORB to extract key points and calculate descriptors; use convolutional neural networks (CNN) to automatically learn hierarchical feature representations from the original image. Deep learning model: build LSTM to process sequence data and use 3D CNN to process stereo images for end-to-end object recognition and classification; estimate the actual size of the object through the detected object bounding box size, combined with perspective transformation or camera calibration technology; train the model to directly output the size (length, width, height) of the object based on the image; according to classification and size: match the identified item type and size with the specifications of the express cabinet to select the most suitable delivery location; use the Dijkstra algorithm to plan the movement path of the robot arm or conveyor belt to deliver the item to the designated location in the most efficient way.

[0106] Power supply and monitoring module upgrade: The dual-axis tracking system solar panel automatically tracks the sun's trajectory and maximizes the sunshine receiving area. The system is mainly composed of solar panels, brackets, azimuth rotators, altitude rotators, drive motors and transmission mechanisms. The solar panel is installed on the bracket, and the bracket is connected to the base through the azimuth rotator and altitude rotator. The azimuth rotator is responsible for controlling the rotation of the solar panel around the vertical axis (i.e. the east-west direction) to track the azimuth changes of the sun. The altitude rotator is responsible for controlling the rotation of the solar panel around the horizontal axis (perpendicular to the azimuth axis) to adjust the tilt angle of the solar panel and track the altitude changes of the sun. The sensor part includes photoelectric sensors, sundials or modules combining GPS and astronomical algorithms, etc., which are used to detect the position and light intensity of the sun in real time and provide accurate data support for the control system. The system adopts a step tracking method to fine-tune the solar panel according to the preset step size and cycle. The system also has a self-learning function, which can automatically optimize the tracking strategy based on historical data and current environmental conditions.

[0107] Comprehensive upgrade of intelligent supporting facilities: Add intelligent temperature control modules to ensure the temperature stability of items in express cabinets under extreme weather conditions. At the same time, big data analysis technology is introduced to analyze and predict logistics data in real time to provide decision support for logistics companies. The added environment adaptive intelligent temperature control module uses a combination of IoT sensors and AI algorithms to monitor environmental parameters such as temperature, humidity and light intensity around the express cabinet in real time, and automatically adjust the temperature control strategy in the cabinet. To ensure the temperature stability of items in the express cabinet under extreme weather conditions, it can be precisely regulated according to seasonal changes or the storage needs of specific items, such as refrigerated medicines and perishable foods, to achieve personalized temperature control services. Integrate big data analysis technology to build a predictive maintenance model. Through the continuous collection and analysis of express cabinet operation data, the system can identify potential fault points in advance, such as motor wear and battery life attenuation, and automatically trigger the early warning mechanism to notify the operation and maintenance personnel to repair or replace parts in time. This forward-looking maintenance strategy effectively reduces the failure rate and improves equipment reliability and user satisfaction.

[0108] Optimize the user interaction interface: Develop a user-friendly interactive interface to support users to pick up and send parcels and query logistics information through mobile APP or web pages. At the same time, provide an intelligent customer service system to provide users with real-time online help.

[0109] Effect evaluation: This embodiment achieves a high degree of coordination between drones and rooftop intelligent logistics facilities through measures such as multi-drone collaborative operation, intelligent delivery device upgrade, comprehensive upgrade of intelligent supporting facilities, and optimization of user interaction interface. The system can handle large-scale and efficient logistics distribution needs, while providing better user experience and decision support functions.

[0110] The present invention also proposes an architecture design of a rooftop low-altitude intelligent drone logistics distribution system, using Figure 2 The architecture shown in the figure is designed, including the infrastructure layer, perception layer, management and service component layer, and software and hardware platform layer.

[0111] in,

[0112] The infrastructure layer specifically includes: integrated base station, low-altitude economic satellite, ground-based augmentation system, LAEL micro-meteorological station, TOC start-stop service station, TOB start-stop service station, charging station, and maintenance point.

[0113] (1) Synaptic base station

[0114] Role and function: As the core communication and perception node of the UAV logistics distribution system, it integrates communication and sensing functions to achieve efficient information exchange and data processing between UAVs, satellites and ground systems.

[0115] Specific implementation method: Use 5G / 6G communication technology combined with IoT sensing technology to transmit drone status, location information and environmental data in real time, and support low-latency and high-reliability data transmission.

[0116] (2) Low-altitude economic satellite

[0117] Role and function: Provide global coverage of drone positioning, navigation and communication services, and enhance signal coverage and positioning accuracy in low-altitude areas.

[0118] Specific implementation method: Deploy a dedicated low-orbit satellite network and use satellite communication technology to achieve precise positioning and long-distance communication of drones, ensuring that cross-regional logistics distribution is not restricted by ground facilities.

[0119] (3) Foundation reinforcement system

[0120] Role and function: Improve the navigation accuracy of drones and reduce positioning errors through ground differential GPS technology.

[0121] Specific implementation method: Deploy differential stations in key areas, receive satellite signals and compare them with known positions, calculate and broadcast differential correction information, and the drone corrects its own position information after receiving it.

[0122] (4) LAEL Micro Weather Station

[0123] Role and function: Real-time monitoring of weather conditions in low-altitude areas, providing accurate weather data support for UAV flights.

[0124] Specific implementation method: Deploy high-precision meteorological sensors, such as temperature, humidity, wind speed, wind direction, visibility, etc., transmit them wirelessly to the system center, and combine AI algorithms to predict future meteorological changes.

[0125] (5)TOC / TOB start-stop service stations, charging stations, and maintenance points

[0126] Role and function: Provide docking, charging and maintenance services for drones to ensure continuous and efficient operation of drones.

[0127] Specific implementation method: Set up service stations at key logistics nodes, equipped with automated charging equipment, rapid maintenance tools and spare parts, remotely monitor equipment status through Internet of Things technology, and realize intelligent scheduling and maintenance.

[0128] The perception layer includes: outdoor location perception gateway, image perception gateway, weather perception gateway, aircraft power perception, channel perception gateway, outdoor altitude perception, emergency support gateway, LAEL facility busy and idle perception, aircraft automatic return module, aircraft anti-collision coordination module, aircraft temperature sensor module, LEAL imaging gateway

[0129] The management and service component layer specifically includes: logistics service interface, express service interface, takeaway service interface, other API interfaces, digital twin city module, large model component module, 3D digital earth component, airspace editing and visualization module, IoT middle platform component, weather service component, flight situation sharing component, authentication and authorization component, data access module, data storage module, data calculation module, and data service module.

[0130] The software platform layer specifically includes: digital twin large screen module, flight service applet module, airspace management module, aircraft supervision service client module, warning and rescue assistance module, anti-UAV monitoring system module, low-altitude safety management and control software platform module, air traffic flow management module, waterway management module, flight insurance management module, aircraft management module, and operator management module.

[0131] In a specific implementation, the present application provides a computer storage medium and a corresponding data processing unit, wherein the computer storage medium can store a computer program, and when the computer program is executed by the data processing unit, the invention content of a rooftop low-altitude intelligent unmanned aerial vehicle logistics distribution system and its architecture provided by the present invention and some or all steps in each embodiment. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0132] Those skilled in the art can clearly understand that the technical solutions in the embodiments of the present invention can be implemented by means of computer programs and their corresponding general hardware platforms. Based on such an understanding, the technical solutions in the embodiments of the present invention can be essentially or partly contributed to the prior art in the form of computer programs, i.e., software products, which can be stored in a storage medium and include several instructions for enabling a device including a data processing unit (which can be a personal computer, a server, a single-chip microcomputer, an MCU or a network device, etc.) to execute the methods described in various embodiments of the present invention or certain parts of the embodiments.

[0133] The present invention provides a rooftop low-altitude intelligent drone logistics distribution system and its architecture ideas and methods. There are many methods and ways to implement the technical solution. The above is only a preferred implementation of the present invention. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications should also be regarded as the protection scope of the present invention. All components not specified in this embodiment can be implemented by existing technologies.

Claims

1. A rooftop low-altitude intelligent drone logistics distribution system, characterized in that: The system comprises: A parapet (1) disposed on the roof serves as the boundary of the system; an automatic storage and retrieval logistics cabinet (2) is disposed in the parapet (1), and a storage area (6) is disposed in the automatic storage and retrieval logistics cabinet (2) for storing and retrieving logistics packages; a start-stop area (7) is disposed on one side of the automatic storage and retrieval logistics cabinet (2) for starting and stopping the drone (3); a start-stop point mark (11) and a stop induction device sensor (13) are disposed in the start-stop area (7) for assisting the drone (3) in starting and stopping in the start-stop area (7). ; The start-stop area (7) is also provided with a lift (4) and a slide rail (5) for dropping the logistics package carried by the drone (3) into the corresponding position of the storage area (6); the automatic storage and retrieval logistics cabinet (2), the slide rail (5) and the start-stop area (7) are all provided with grounding wires (8, 9 and 10); the parapet (1) is provided with a camera (12) for monitoring the inside of the system; the system is also provided with a power module (14) for supplying power to various devices in the system.

2. The low-altitude intelligent unmanned aerial vehicle logistics distribution system on the rooftop according to claim 1 is characterized in that: The system is also provided with a reverse logistics device, which comprises: A storage box (21) for storing disassembled logistics parcel boxes, wherein the storage box (21) is provided with a storage opening (22), through which a user puts the disassembled logistics parcel box into the storage box (21); an automatic packer (23) is provided on one side of the storage box (21) for compressing the disassembled logistics parcel box; a friction roller (26) is provided on the other side of the automatic packer (23) for leveling the compressed logistics parcel box; a binding rope extractor (24) is provided on the other side of the friction roller (26) for packing the leveled logistics parcel box; a storage table (25) is provided on the other side of the binding rope extractor (24) for storing the packed logistics parcel box; The reverse logistics device is also provided with a circuit control board (27) for controlling the reverse logistics device and communicating with the system.

3. The low-altitude intelligent unmanned aerial vehicle logistics distribution system on the rooftop according to claim 1 is characterized in that: Putting the logistics package carried by the drone (3) into a corresponding position in the storage area (6) specifically includes: The elevator (4) and the slide rail (5) in the start-stop area (7) automatically allocate corresponding positions in the storage area (6) according to the type of the logistics package, and deliver the package according to the allocated position, as follows: The sizes of the corresponding positions of the storage area (6) are divided into three types: large, medium and small. At the same time, the logistics packages are identified and divided into three types: large, medium and small according to their sizes. The packages are matched and assigned positions according to the types.

4. The low-altitude intelligent unmanned aerial vehicle logistics distribution system on the rooftop according to claim 1 is characterized in that: The power module (14) adopts a photoelectric complementary form, and specifically comprises: The power module (14) comprises: an AC / DC integrated machine and a solar panel; wherein: The AC / DC integrated machine includes an AC 220V mains power module, a DC 48V to 220V inverter module and a battery pack; the solar panel is connected to the battery pack to provide solar power and power the system. When the battery pack is low on power, the AC 220V mains power module is turned on and the AC 220V mains power is used to power the system.

5. The rooftop low-altitude intelligent drone logistics distribution system according to claim 1 is characterized in that: The shutdown induction device sensor (13) comprises: A radar system and an infrared sensor; wherein the radar system uses a laser radar to detect environmental depth information within a 360-degree range through mechanical scanning or phased array, and the radar system obtains distance information of the surrounding environment of the unmanned aerial vehicle (3) in real time to provide data support for obstacle avoidance decisions; the infrared sensor is used to assist the radar system to detect and identify obstacles at night or in low-light environments.

6. The rooftop low-altitude intelligent drone logistics distribution system according to claim 1 is characterized in that: The assisting the drone (3) to start and stop in the start and stop area (7) specifically includes: In combination with the data of the radar system and the infrared sensor in the stop induction device sensor (13), the optimal flight path of the UAV (3) is calculated by a dynamic path planning method, and the landing and gliding routes of the UAV (3) are adjusted in real time, while avoiding obstacles, as follows: Training a deep neural network model to predict traffic flow and road condition changes, combining GPS data with data from a radar system and an infrared sensor in the parking induction device sensor (13) to locate the drone (3) and identify obstacles; Train the path selection model, using reinforcement learning strategy to continuously iterate and optimize path selection in a simulated environment; According to the trained deep neural network model and the path selection model, the path planning scheme is adjusted in real time to assist the UAV (3) to start and stop in the start and stop area (7).

7. The rooftop low-altitude intelligent drone logistics distribution system according to claim 3 is characterized in that: Identify the logistics package, specifically including: Converting the color image of the logistics package into a grayscale image; Noise removal, using filters to remove image noise; Edge detection, using edge detection methods to highlight the boundaries of the logistics package; Size normalization, adjust the image to a uniform size; Use feature point detector to extract key points and calculate descriptors; Use convolutional neural networks (CNNs) to learn hierarchical feature representations from raw images; Build deep learning models for end-to-end recognition and classification; According to the detected boundary size of the logistics package, combined with perspective transformation or camera calibration method, the actual size of the object is estimated; Complete the identification of the logistics package.

8. The rooftop low-altitude intelligent drone logistics distribution system according to claim 4 is characterized in that: The solar power supply specifically includes: The solar panel adopts a dual-axis tracking system solar panel to automatically track the sun's trajectory and maximize the sunlight receiving area. The dual-axis tracking system solar panel includes a solar panel, a bracket, an azimuth rotator, an altitude rotator, a base, a drive motor, a transmission mechanism, a photoelectric sensor, a sundial, a GPS and a control module; The solar panel is installed on the bracket, and the bracket is connected to the base through an azimuth rotator and an altitude rotator; the drive motor and the transmission mechanism drive the azimuth rotator to control the solar panel to rotate around the vertical axis; the drive motor and the transmission mechanism drive the altitude rotator to control the solar panel to rotate around the horizontal axis; The photoelectric sensor, sundial and GPS detect the position and light intensity of the sun in real time; the control module controls the driving motor.

9. The low-altitude intelligent unmanned aerial vehicle logistics distribution system on the rooftop according to claim 1 is characterized in that: The drone (3) is provided with sensors and communication devices, and the system is provided with a ground station for coordinating the coordination of multiple drones.

10. An architecture of a low-altitude intelligent drone logistics distribution system on a roof, characterized in that: A system for implementing any one of claims 1 to 9, comprising: The system is divided into infrastructure layer, perception layer, management and service component layer and software and hardware platform layer; The infrastructure layer includes: inter-sensory base station, low-altitude economic satellite, ground-based augmentation system, LAEL micro-weather station, TOC start-stop service station, TOB start-stop service station, charging station and maintenance point; The perception layer includes outdoor location perception gateway, image perception gateway, weather perception gateway, aircraft power perception, channel perception gateway, outdoor altitude perception, emergency support gateway, LAEL facility busy and idle perception, aircraft automatic return module, aircraft collision avoidance coordination module, aircraft temperature sensor module and LEAL imaging gateway. Management and service component layer, including logistics service interface, express service interface, takeaway service interface, other API interfaces, digital twin city module, large model component module, 3D digital earth component, airspace editing and visualization module, IoT middle platform component, weather service component, flight situation sharing component, authentication and authorization component, data access module, data storage module, data calculation module and data service module; The software platform layer specifically includes the digital twin large screen module, the flight service applet module, the airspace management module, the aircraft supervision service client module, the warning and rescue assistance module, the anti-UAV monitoring system module, the low-altitude safety control software platform module, the air traffic flow management module, the waterway management module, the flight insurance management module, the aircraft management module and the operator management module.

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