Non-embedded unmanned aerial vehicle information acquisition device and method

Abstract

This invention discloses a non-embedded UAV information acquisition device and method. The non-embedded UAV information acquisition device includes a shell assembly, a three-mode adapter structure, a standardized physical interface, a main control module, a communication module, a positioning and sensing module, and a power management module. The internal cavity wall of the shell assembly is fitted with an anti-magnetic shielding layer made of permalloy. The three-mode adapter structure is integrated into the bottom of the shell assembly and includes a magnetic suction component, a suspension component, and a screw fixing interface. The standardized physical interface is located on the surface of the shell assembly and uses a gold-plated gold finger contact structure, which is electrically connected to the main control module. This invention enables deployment without disassembly of the UAV through a non-intrusive design while maintaining the UAV's airworthiness. It utilizes edge computing to alleviate cloud scheduling pressure and reduce task latency, and with independent power supply, achieves long endurance and high reliability, making it widely adaptable to various UAV models and harsh operating environments.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) information acquisition technology, and in particular to a non-embedded UAV information acquisition device and method. Background Technology

[0002] With the explosive growth of the low-altitude economy, drones are increasingly being used in logistics, power line inspection, emergency rescue, and urban management, leading to an exponential increase in their numbers. In building city-level dispatch platforms, real-time acquisition and monitoring of key parameters such as the geographical location, remaining battery power, real-time payload, and mission execution status of each drone are fundamental to achieving efficient air traffic management and resource optimization. However, current drone monitoring and data acquisition solutions still face numerous challenges in practical applications.

[0003] Current UAV data acquisition primarily relies on onboard flight control systems, but data fragmentation is severe, with many flight control logs only stored locally, making it difficult for remote scheduling platforms to monitor flight status in real time. Regarding compatibility, due to varying interface types and communication protocols among different manufacturers, existing external devices often fail to achieve cross-platform plug-and-play functionality. Furthermore, existing external acquisition devices generally suffer from high power consumption, significantly reducing the effective operating time of UAVs and impacting mission continuity. In terms of environmental adaptability, existing equipment often lacks sufficient protection against rain, high humidity, and strong magnetic fields, easily leading to data loss or device malfunction. Even more serious is the fact that traditional data acquisition equipment typically requires UAV disassembly and wiring modifications, a complex and cumbersome process that can cause the UAV to lose its original airworthiness certification, increasing operational risks and compliance costs.

[0004] Therefore, developing a non-embedded UAV information acquisition device that is compatible with multiple installation modes, requires no disassembly or modification, has extremely low power consumption, and can operate stably in complex environments has become a key technical problem that urgently needs to be solved in the low-altitude economy. By improving the integration level and edge computing capabilities of the device, it is possible to efficiently and in real-time complete the acquisition and transmission of multi-dimensional data without compromising the original airworthiness of the UAV. This has significant application value for promoting the standardization and intelligent scheduling of the UAV industry. Summary of the Invention

[0005] This invention addresses the technical shortcomings of existing UAV monitoring equipment in practical applications, including the need to disassemble the airframe leading to compromised airworthiness, poor compatibility due to inconsistent interface protocols, high power consumption shortening the effective operating time of the UAV, insufficient environmental protection capabilities, and task scheduling delays caused by excessive reliance on cloud-based data processing. It proposes a non-embedded UAV information acquisition device and method. Through a non-intrusive hardware structure design and intelligent scheduling logic at the edge, this invention achieves real-time, highly reliable acquisition and preprocessing of multi-dimensional flight data without altering the original physical structure and airworthiness of the UAV.

[0006] This invention provides a non-embedded UAV information acquisition device, including a shell assembly, a three-mode adapter structure, a standardized physical interface, a main control module, a communication module, a positioning and sensing module, and a power management module; the internal cavity wall of the shell assembly is fitted with an anti-magnetic shielding layer made of permalloy; the three-mode adapter structure is integrated into the bottom of the shell assembly, and the three-mode adapter structure includes a magnetic suction component, a suspension component, and a screw fixing interface; the standardized physical interface is set on the surface of the shell assembly, and the standardized physical interface adopts a gold finger contact structure with a gold-plated layer, and the gold finger contacts are electrically connected to the main control module.

[0007] In a preferred embodiment of the non-embedded UAV information collection device provided by the present invention, a silicone sealing ring is provided at the seam of the outer shell assembly, and the outer shell assembly as a whole has an IP67-level protective structure.

[0008] In a preferred embodiment of the non-embedded UAV information collection device provided by the present invention, the magnetic suction component is composed of several sets of neodymium iron boron permanent magnets; the suspension component is a quick-release slide rail bracket, which is provided with an elastic buckle; and the screw fixing interface is provided with an M3 or M4 threaded hole.

[0009] In a preferred embodiment of the non-embedded UAV information acquisition device provided by the present invention, the physical layer of the standardized physical interface supports CAN-FD bus, UART bus and GPIO level triggering, and the main control module establishes a bidirectional communication link with the UAV flight control system through the standardized physical interface.

[0010] In a preferred embodiment of the non-embedded UAV information acquisition device provided by the present invention, the main control module has a built-in edge computing unit based on ARM architecture, and the edge computing unit is configured with static random access memory and flash memory; the communication module has a built-in 4G or 5G wireless communication module and is equipped with a MIMO antenna system integrated inside the shell.

[0011] In a preferred embodiment of the non-embedded UAV information acquisition device provided by the present invention, the positioning and sensing module integrates a GNSS unit and a six-axis inertial sensor composed of a three-axis accelerometer and a three-axis gyroscope; the power management module has a built-in independent battery cell and integrates a charging management circuit and a low-dropout regulator.

[0012] The present invention also provides an information acquisition method based on the above-mentioned non-embedded UAV information acquisition device, comprising the following steps: S1. Plug and play initialization: The non-embedded UAV information acquisition device is fixed to the UAV through a three-mode adapter structure. When the gold finger contact is connected to the UAV interface, the main control module detects the baud rate of the UAV communication interface through an automatic baud rate recognition algorithm and establishes a communication link. S2. Multi-source data fusion acquisition: The main control module extracts the internal flight control parameters of the UAV through the gold finger contact point, and simultaneously acquires the independent position and attitude data generated by the positioning and perception module. The main control module performs timestamp alignment and spatial coordinate system transformation on the heterogeneous data to form a multi-dimensional state vector. S3. Edge scoring prediction: The main control module uses the edge scheduling algorithm to calculate the multi-dimensional state vector and obtain the comprehensive evaluation score of the current UAV. S4. Status Reporting and Recommendation: The non-embedded UAV information collection device encapsulates the status data and the comprehensive evaluation score into an encrypted data packet and uploads it to the cloud scheduling platform through the communication module. S5. Closed-loop execution of tasks: The cloud-based scheduling platform allocates resources based on the received comprehensive evaluation score and sends scheduling decision instructions to the non-embedded UAV information acquisition device. After receiving the instructions, the non-embedded UAV information acquisition device sends task guidance parameters to the UAV flight control system through the gold finger contact.

[0013] In a preferred embodiment of the information acquisition method provided by the present invention, in step S2, the multi-source data fusion acquisition process includes: the main control module compares the difference between the GNSS data inside the UAV and the data from the positioning and sensing module of the non-embedded UAV information acquisition device. When the difference exceeds a preset confidence interval, the main control module switches to the positioning and sensing module as the reference data.

[0014] In a preferred embodiment of the information collection method provided by the present invention, in step S3, the formula for calculating the comprehensive evaluation score is: Score = α·Battery_Index + β·Distance_Index + γ·Load_Index + δ·Environment_Index; where Battery_Index reflects the matching degree between the remaining power and the task power consumption requirement, Distance_Index reflects the spatial distance weight between the current position and the target task point, Load_Index reflects the current payload margin, Environment_Index reflects the degree of influence of the current weather conditions on flight, and α, β, γ, and δ are weighting coefficients.

[0015] In a preferred embodiment of the information acquisition method provided by the present invention, in step S5, the task closed-loop execution process includes: when the communication module detects that the network signal strength RSSI is lower than a preset threshold, the main control module starts the local storage mechanism to temporarily store the acquired data in the flash memory, and resends the data after the network is restored.

[0016] The beneficial effects of this invention are reflected in the following aspects: Firstly, this invention effectively maintains the airworthiness of drones and enables deployment without modification. Through a non-embedded, integrated structural design combined with a three-mode adapter structure involving magnetic attachment, suspension, and screw fixing, the device can be quickly installed without touching the drone's internal circuitry or altering its original skin structure. This non-invasive data collection method avoids the problem of drone airworthiness certificates becoming invalid due to the need for disassembly and wiring required by traditional add-on equipment. It significantly lowers the deployment threshold and compliance costs, achieving a technological leap by enabling cross-model deployment within 30 seconds.

[0017] Secondly, this invention achieves a significant reduction in cloud load and an improvement in response speed through edge intelligent computing. The main control module built into the device is not a simple data transmission module, but a computing node with edge scoring and prediction capabilities. By performing data cleaning, multi-source fusion, and preliminary scheduling evaluation on the terminal side, complex computing logic is front-endized. This approach reduces the amount of invalid data reported by approximately 30% to 50%, alleviates the computing bottleneck of the cloud scheduling platform when large-scale drone swarms are connected, and effectively controls the end-to-end latency of task scheduling.

[0018] Thirdly, this invention boasts extremely low power consumption and excellent battery life. By selecting a low-power hardware architecture and implementing a refined power management strategy, the average operating power consumption of the entire device is reduced to the 60mW level. Combined with a built-in, independent, high-capacity battery cell, the device can provide over 14 hours of continuous operation without consuming the drone's power battery. This feature solves the problem of excessive power consumption from external attachments shortening the effective operating radius of the drone, ensuring the smooth implementation of long-term inspections and high-frequency logistics tasks.

[0019] Fourth, this invention demonstrates extremely high environmental adaptability and data reliability. The IP67 protection rating, combined with an internal anti-magnetic shielding layer, enables the device to operate stably in harsh environments such as moderate rain, high humidity, and strong electromagnetic interference (e.g., during high-voltage power line inspections), preventing equipment crashes or data overflows caused by external interference. Simultaneously, the built-in independent sensors and flight control data serve as backups for each other, and combined with a breakpoint resume mechanism, achieve extremely high robustness in the data acquisition closed-loop.

[0020] Fifth, this invention achieves strong versatility and cost reduction through standardized interfaces. By employing standardized gold finger contacts and a universal communication protocol stack, a single device can be adapted to various brands and applications of drones used for logistics, inspection, emergency response, and agriculture. This standardized design reduces the R&D investment required for developing dedicated data acquisition modules for specific drone models, and significantly reduces the cost of monitoring a single drone through large-scale application, providing crucial hardware support for the large-scale commercial operation of the low-altitude economy.

[0021] In summary, this invention, through its innovative non-embedded hardware architecture and edge-side data processing method, solves the core contradictions that have long existed in the field of UAV information collection, such as airworthiness conflicts, adaptation difficulties, power consumption bottlenecks, and data lag, laying a solid technical foundation for building an intelligent and standardized low-altitude traffic management system. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the hardware structure of a non-embedded UAV information acquisition device provided in an embodiment of the present invention; Figure 2 This is a front view of the non-embedded UAV information acquisition device provided in an embodiment of the present invention; Figure 3 This is a side view of a non-embedded UAV information acquisition device provided in an embodiment of the present invention; Figure 4 A bottom view of the non-embedded UAV information acquisition device provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the internal structure of a non-embedded UAV information acquisition device provided in an embodiment of the present invention; Figure 6This is a structural block diagram of a non-embedded UAV information acquisition device provided in an embodiment of the present invention; Figure 7 A flowchart of an information collection method provided in an embodiment of the present invention.

[0023] The attached figures are labeled as follows: 1. Main control module; 2. Communication module; 3. Positioning and sensing module; 4. Power management module; 5. Standardized physical interface; 6. Shell assembly; 7. Magnetic assembly; 8. Suspension assembly; 9. Screw fixing interface; 10. UAV; 11. Cloud dispatch platform; 12. Main antenna; 13. Diversity antenna; 14. Spring pin; 15. Pin hole. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0025] Please refer to the following: Figures 1-6 This invention provides a non-embedded drone information acquisition device, which serves as an external black box device, non-invasively installed on the exterior of the drone 10. The core hardware architecture of this non-embedded drone information acquisition device consists of a main control module 1, a communication module 2, a positioning and sensing module 3, a power management module 4, and a standardized physical interface 5. These components are integrated within a highly protective outer shell assembly 6. The outer shell assembly 6 is injection molded from polycarbonate and ABS alloy materials, with a wall thickness controlled between 1.5mm and 2.0mm to ensure strength while keeping the overall weight below 95g, reducing the impact on the drone 10's payload capacity. A high-permeability permalloy shielding layer is coated onto the internal cavity wall of the outer shell assembly 6 using a vacuum sputtering process. This shielding layer has the technical performance to suppress low-frequency magnetic field interference, ensuring that the magnetic field generated by the high-power motor of the drone 10 does not interfere with the accuracy of the electronic compass in the positioning and sensing module 3. The mating surface of the outer casing assembly 6 is equipped with an EPDM rubber sealing ring, which is tightened by ultrasonic welding or fastening screws to achieve an IP67 protection rating for the entire unit. This ensures that the internal circuitry remains dry in rainy or high-humidity environments, eliminating the risk of short circuits caused by moisture intrusion.

[0026] This non-embedded UAV information acquisition device achieves rapid physical connection with the UAV 10 body through a three-mode adapter structure, without requiring any disassembly or internal wiring of the UAV 10. The three-mode adapter structure includes three modes. The first mode is the magnetic attraction component 7, which consists of four symmetrically distributed N52-grade neodymium iron boron permanent magnets. Each magnet provides a vertical tensile force of no less than 20N, fixing the device to the metal chassis or battery compartment cover of the UAV 10 through magnetic attraction. The installation process can be completed within 5 seconds. The second mode is the suspension component 8, which uses a dovetail slide rail bracket with a self-locking function. Multiple pin holes 15 are evenly arranged along the length of the dovetail slide rail bracket on its side. The dovetail slide rail bracket is secured by high-strength nylon cable ties or... The elastic buckle is fixed to the landing gear crossbeam of the UAV 10. After the device is pushed in along the dovetail slide rail bracket, it is positioned by the cooperation of the spring pin 14 and the pin hole 15. The installation process takes about 10 seconds. The third mode is to fix the screw interface 9. There are four threaded holes with metal bushings that meet the M3 standard specification on the bottom of the outer shell component 6. It is directly locked to the reserved mounting point of the UAV 10 by bolts. The installation process is completed within 30 seconds. In addition, the bottom of the magnetic component 7 is flush with the bottom of the suspension component 8, and the bottom of the screw fixing interface 9 does not exceed the bottom of the suspension component 8. These three modes complement each other and ensure the high compatibility of the device with various models such as logistics, inspection and consumer aircraft.

[0027] The standardized physical interface 5 is a key component for achieving plug-and-play functionality. Physically, it consists of a set of elastic gold finger contacts located on the bottom of the casing. The contact surface is plated with a 30µm thick hard gold layer, providing excellent wear resistance and oxidation resistance. This set of contacts includes a power input terminal, a CAN-H / L differential signal terminal, a UART transceiver terminal, and a digital ground terminal. When the device is installed on the surface of the UAV 10 via the aforementioned adapter structure, the gold finger contacts press against the elastic probe interface on the side of the UAV 10, thereby establishing a stable electrical connection. The main control module 1 extracts real-time parameters from the UAV 10's internal flight control system via the CAN-FD bus at a maximum rate of 8Mbps, including but not limited to remaining battery power, current latitude and longitude coordinates, magnetic heading, barometric altitude, motor speed, mission phase indicators, and critical system alarm bits.

[0028] The main control module 1 employs a high-performance, low-power microprocessor based on the ARM Cortex-M7 core, with a maximum clock speed of 480MHz. It has 2MB of built-in flash memory for storing complex edge scheduling algorithm logic. The main control module 1 features dynamic frequency adjustment, automatically switching to a low-frequency operating mode during data sampling intervals to reduce operating current to the milliampere level. The positioning and sensing module 3 integrates a GNSS unit supporting GPS, BeiDou, GLONASS, and Galileo positioning, along with a six-axis inertial sensor. Through a built-in Kalman filter algorithm, the main control module 1 deeply fuses the absolute position information provided by the GNSS with the relative motion data provided by the inertial sensor. Even when the UAV 10 experiences temporary loss of GNSS signal due to obstruction by tall buildings or trees, it still provides continuous and smooth trajectory calculation data, ensuring the integrity of flight monitoring data.

[0029] The communication module 2 has a built-in 4G-Cat1 cellular communication unit, supporting all network frequency bands, and maintains a long-term connection with the remote cloud scheduling platform 11 via the encrypted MQTT protocol. The communication module 2 adopts a dual-antenna diversity design, with the main antenna 12 and diversity antenna 13 arranged vertically on opposite sides of the housing component 6, effectively resisting multipath interference and improving communication quality in complex urban electromagnetic environments. The power management module 4 includes a 3.4Ah 18650 lithium battery and a high-efficiency Buck-Boost converter circuit. This module has an independent fuel gauge chip to monitor its own battery status in real time. When the drone 10 is not powered on, the device is in deep sleep mode, with power consumption below 50uW; once a voltage fluctuation is detected at the gold finger contacts or vibration is detected by the IMU, the device quickly wakes up and enters working state within 200ms.

[0030] This invention also provides an information acquisition method based on the above-mentioned non-embedded UAV information acquisition device, the operation process of which is as follows: Figure 7 As shown, it includes the following steps: S1. Plug and Play Initialization Process. After the operator installs the three-mode adapter structure described in the device onto the UAV 10, the main control module 1 detects the external voltage level change through the standardized physical interface 5. The main control module 1 starts the automatic baud rate identification program, sequentially trying common CAN bus rates such as 250k, 500k, 1M, and 2M, until it successfully parses the heartbeat packet sent by the UAV 10 flight control system. Subsequently, the main control module 1 retrieves and matches the corresponding protocol template from the built-in protocol library, completing the automatic identification of the UAV 10 model. This process enables automatic access for UAVs from different manufacturers and with different protocols, eliminating the need for manual parameter configuration.

[0031] S2. Multi-source data fusion acquisition process. The main control module 1 polls the internal state of the UAV 10 at a frequency of 50Hz through the standardized physical interface 5, while simultaneously reading the raw data from the positioning and sensing module 3 at a frequency of 100Hz. The main control module 1 executes timestamp alignment logic, mapping the power data from the flight control system, the position data from the GNSS, and the attitude data from the IMU onto the same time axis. To eliminate sensor noise, the main control module 1 uses the extended Kalman filter (EKF) algorithm to fuse the multi-source data. During the algorithm operation, the main control module 1 uses the GNSS accuracy factor (HDOP) reported by the UAV 10 as a weight reference. When the HDOP value is small, the weight of the flight control position data is increased; when the HDOP value is large or the signal is lost, the main control module 1 automatically switches to a combined navigation mode that primarily relies on its own inertial navigation calculations and secondarily relies on flight control barometer altitude correction, thereby outputting a highly reliable multi-dimensional state vector.

[0032] S3. Edge Scoring and Prediction Process. This is the core intelligent step of the invention. The main control module 1 no longer merely acts as a data transporter, but utilizes local computing resources to perform real-time evaluation of the execution capabilities of the UAV 10. The main control module 1 runs an edge scheduling algorithm to calculate a comprehensive evaluation score based on the currently collected multi-dimensional state vector. The formula for calculating the comprehensive evaluation score is: Score = α·Battery_Index + β·Distance_Index + γ·Load_Index + δ·Environment_Index; where Battery_Index is obtained by subtracting the reserved power for return from the current remaining power and dividing by the estimated power consumption of the task, reflecting the safety margin of the power; Distance_Index is calculated from the Euclidean distance between the current coordinates and the nearest task pending point, with a higher score for closer distances; Load_Index... The ex value is derived from the ratio of the current weight of the UAV 10 to its maximum takeoff weight, reflecting the payload redundancy. The Environment_Index is derived by combining the gust intensity detected by the IMU and the local wind speed data sent from the cloud. The weight coefficients α, β, γ, and δ are dynamically adjusted by the cloud scheduling platform 11 according to the task priority. For example, in the logistics delivery scenario, the weight of β (distance coefficient) is set to the highest; while in the power inspection scenario, the weight of α (power coefficient) is set to the highest. The main control module 1 updates the Score value once per second to provide a basis for decision-making in subsequent resource scheduling.

[0033] S4. Status Reporting and Recommendation Process. The main control module 1 encapsulates the calculated Score along with compressed trajectory data into an encrypted data packet in Protobuf format. The communication module 2 sends this data packet to the cloud scheduling platform 11 via the 4G network. To save network bandwidth and power consumption, the main control module 1 implements a variable frequency reporting strategy: when the drone 10 is in stable flight or hovering and the Score fluctuation is less than 5%, the reporting frequency is reduced to 0.2Hz; when a drastic change in heading is detected, a low-voltage warning is triggered due to insufficient power, or the Score drops rapidly, the reporting frequency is immediately increased to 2Hz. When the Score exceeds a preset recommendation threshold (e.g., 0.85), the main control module 1 sets a "recommended execution" flag in the data packet and proactively requests the next stage of task scheduling from the cloud scheduling platform 11. This edge-side pre-screening mechanism allows the cloud scheduling platform 11 to process only the high-value data that has undergone initial screening, effectively alleviating the server's computational pressure during large-scale concurrent access by drones.

[0034] S5. Task Closed-Loop Execution Process. After receiving the Score values ​​reported by multiple devices, the cloud scheduling platform 11 executes a global optimization algorithm and selects the UAV 10 with the highest score to execute the newly generated task order. The cloud scheduling platform 11 sends the task instructions to the corresponding devices. After receiving the instructions, the communication module 2 writes the task coordinates, waypoint speed, and action trigger instructions into the flight control register of the UAV 10 through the standardized physical interface 5. During task execution, the device continuously monitors the task compliance. If the actual flight trajectory of the UAV 10 deviates from the preset route by more than 5 meters, the main control module 1 immediately reports an abnormal yaw alarm to the cloud scheduling platform 11 through the communication module 2, and sends hover or one-key return-to-home instructions to the flight control system through the standardized physical interface 5 according to the preset safety logic to ensure flight safety. After the task is completed, the main control module 1 automatically summarizes the total energy consumption, average speed, and environmental interference distribution of this task, generates a task summary report, and sends it back to the cloud, completing the entire scheduling closed loop.

[0035] Building upon the above embodiments, this invention also considers reliability assurance under extreme environments. For example, in high-voltage power line inspection scenarios, strong magnetic fields often cause ordinary electronic compasses to malfunction. The device of this invention uses a permalloy shielding layer inside the outer casing 6 to block most of the constant magnetic field. Simultaneously, the main control module 1 uses the triaxial accelerometer in the positioning sensing module 3 and the velocity vector direction provided by the GNSS unit to perform complementary calculations, correcting the zero-bias error of the magnetic compass in real time, ensuring accurate heading angle output even in strong magnetic environments.

[0036] For applications requiring centimeter-level positioning accuracy, such as precise landing in automated hangars, the device of this invention supports connection to an RTK differential antenna via an external expansion interface. The main control module 1 receives RTCM3.2 format differential correction data from a ground reference station via a UART interface and performs carrier phase differential calculations internally. By resolving cycle slips and fixing integer ambiguities, the main control module 1 improves the positioning accuracy from meter-level to centimeter-level. This high-precision positioning data is shared with the flight control system of the UAV 10 via a standardized physical interface 5, enabling high-precision operation capabilities without replacing the original positioning hardware of the UAV 10.

[0037] In terms of low-power management, the power management module 4 implements a tiered power supply strategy based on the device's operating status. When the communication module 2 is idle, its power amplifier circuit is powered off, retaining only the low-power sustaining current of the baseband unit. The main control module 1 utilizes DMA (Direct Memory Access) technology to complete data reception of the standardized physical interface 5 without waking up the CPU core, further reducing processor power consumption. Through this hardware and software co-optimization scheme, the device maintains an average power consumption of around 60mW while maintaining a data reporting frequency of 1Hz, allowing the built-in 18650 battery to support more than 14 hours of continuous operation, meeting the monitoring requirements of the UAV 10 for all-weather, high-frequency operations.

[0038] This invention also possesses robust remote maintenance capabilities. Through the OTA channel provided by communication module 2, the cloud-based scheduling platform 11 can periodically push the latest algorithm models and protocol library firmware to the device. The main control module 1 employs a dual-bank flash memory design, allowing the original program to continue running normally while downloading new firmware. After downloading, a CRC cyclic redundancy check is performed, and if the check is successful, the device automatically switches to the new version upon the next power-on. This design ensures that the device can continuously evolve during long-term operation, adapting to the constantly emerging new models of drones.

[0039] Furthermore, to address potential communication link interruptions, the main control module 1 is equipped with a local data persistence mechanism. The device integrates a 128MB NAND Flash memory. When the communication module 2 detects a signal strength (RSSI) below -110dBm or a network outage, the main control module 1 automatically stores the collected timestamped flight control data into a local circular buffer. Once the network signal returns to normal, the main control module 1 initiates a breakpoint resume protocol, prioritizing the uploading of cached critical alarm data, and then gradually re-uploading historical trajectory data in the background to ensure that the data sequence obtained by the cloud-based scheduling platform 11 is continuous and complete in time.

[0040] In summary, this invention constructs a non-embedded UAV information acquisition device that is universally applicable across platforms and aircraft models through a non-embedded physical structure, standardized interface design, independent and efficient power management, and edge intelligent scoring algorithms. This device achieves real-time and accurate perception of flight status and scientific task scheduling without compromising the airworthiness of the UAV, significantly improving the safety and efficiency of low-altitude economical operation. The embodiments of this invention not only cover the physical construction details of the hardware but also delve into the processing of underlying algorithm logic and communication protocols, providing a complete, practical, and highly reliable technical solution for the digital supervision of large-scale UAV swarms.

Claims

1. A non-embedded unmanned aerial vehicle (UAV) information acquisition device, characterized in that, The system includes a housing assembly (6), a three-mode adapter structure, a standardized physical interface (5), a main control module (1), a communication module (2), a positioning sensing module (3), and a power management module (4). The internal cavity wall of the housing assembly (6) is fitted with an anti-magnetic shielding layer made of permalloy. The three-mode adapter structure is integrated into the bottom of the housing assembly (6) and includes a magnetic suction assembly (7), a suspension assembly (8), and a screw fixing interface (9). The standardized physical interface (5) is located on the surface of the housing assembly (6) and adopts a gold finger contact structure with a gold plating layer. The gold finger contact is electrically connected to the main control module (1).

2. The non-embedded UAV information acquisition device according to claim 1, characterized in that, The seams of the housing assembly (6) are provided with silicone sealing rings, and the housing assembly (6) as a whole has an IP67-level protective structure.

3. The non-embedded UAV information acquisition device according to claim 1, characterized in that, The magnetic suction component (7) is composed of several sets of neodymium iron boron permanent magnets; the suspension component (8) is a quick-release slide rail bracket, which is provided with an elastic buckle; the screw fixing interface (9) is provided with an M3 or M4 threaded hole.

4. The non-embedded UAV information acquisition device according to claim 1, characterized in that, The physical layer of the standardized physical interface (5) supports CAN-FD bus, UART bus and GPIO level triggering. The main control module (1) establishes a bidirectional communication link with the UAV (10) flight control system through the standardized physical interface (5).

5. The non-embedded UAV information acquisition device according to claim 1, characterized in that, The main control module (1) has a built-in edge computing unit based on ARM architecture, and the edge computing unit is equipped with static random access memory and flash memory; the communication module (2) has a built-in 4G or 5G wireless communication module and is equipped with a MIMO antenna system integrated inside the shell.

6. The non-embedded UAV information acquisition device according to claim 1, characterized in that, The positioning and sensing module (3) integrates a GNSS unit and a six-axis inertial sensor consisting of a three-axis accelerometer and a three-axis gyroscope; the power management module (4) has an independent battery cell and integrates a charging management circuit and a low-dropout regulator.

7. An information acquisition method based on the non-embedded UAV information acquisition device according to claim 1, characterized in that, Includes the following steps: S1. Plug and collect initialization: The non-embedded UAV information collection device is fixed to the UAV (10) through the three-mode adapter structure. When the gold finger contact is connected to the UAV interface, the main control module (1) detects the baud rate of the UAV communication interface through the automatic baud rate recognition algorithm and establishes a communication link. S2, Multi-source data fusion acquisition: The main control module (1) extracts the flight control parameters inside the UAV (10) through the gold finger touch point, and simultaneously acquires the independent position and attitude data generated by the positioning perception module (3). The main control module (1) performs timestamp alignment and spatial coordinate system transformation on the heterogeneous data to form a multi-dimensional state vector. S3, Edge scoring prediction: The main control module (1) uses the edge scheduling algorithm to calculate the multi-dimensional state vector and obtain the comprehensive evaluation score of the current UAV (10). S4. Status reporting and recommendation: The non-embedded UAV information collection device encapsulates the status data and the comprehensive evaluation score into an encrypted data packet and uploads it to the cloud scheduling platform (11) through the communication module (2). S5. Task closed-loop execution: The cloud scheduling platform (11) allocates resources according to the received comprehensive evaluation score and sends the scheduling decision instruction to the non-embedded UAV information collection device. After receiving the instruction, the non-embedded UAV information collection device sends the task guidance parameters to the UAV (10) flight control system through the gold finger contact.

8. The information collection method according to claim 7, characterized in that, In step S2, the multi-source data fusion acquisition process includes: the main control module (1) compares the data difference between the GNSS data inside the UAV (10) and the positioning perception module (3) of the non-embedded UAV information acquisition device. When the difference exceeds the preset confidence interval, the main control module (1) switches to the positioning perception module (3) as the reference data.

9. The information collection method according to claim 7, characterized in that, In step S3, the comprehensive evaluation score is calculated using the following formula: Score = α·Battery_Index + β·Distance_Index + γ·Load_Index + δ·Environment_Index; where Battery_Index reflects the matching degree between the remaining power and the task power consumption requirement, Distance_Index reflects the spatial distance weight between the current position and the target task point, Load_Index reflects the current payload margin, Environment_Index reflects the degree of influence of the current weather conditions on flight, and α, β, γ, and δ are weighting coefficients.

10. The information collection method according to claim 7, characterized in that, In step S5, the task closed-loop execution process includes: when the communication module (2) detects that the network signal strength RSSI is lower than the preset threshold, the main control module (1) starts the local storage mechanism to temporarily store the collected data in the flash memory, and resends the data after the network is restored.

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