Unmanned aerial vehicle task planning method based on graphic label

Abstract

The invention relates to the technical field of unmanned aerial vehicle control and RFID, and discloses an unmanned aerial vehicle task planning method based on a graphic tag, and the method comprises the steps: designing a graphic tag with an RFID chip; deploying a graphic label network with environment perception capability; establishing an optimized communication link between the unmanned aerial vehicle and the graphic tag, and setting an initial position and direction; reading a data packet containing a state code and a timestamp by optimizing a communication protocol; performing a hierarchical action based on the status code bit pattern; carrying out path planning and generating an action sequence by adopting an improved A * algorithm; and the unmanned aerial vehicle monitors abnormal conditions in real time, and performs path verification and built-in sensor calibration. Through combination of the graphic tag and the RFID technology and collaborative design of the state code and the path planning algorithm, efficient planning and execution of unmanned aerial vehicle tasks are realized, the problems of unmanned aerial vehicle positioning drifting and poor task adaptability in a complex environment are solved, and the method is particularly suitable for field inspection and search and rescue scenes.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle (UAV) control and RFID technology, and in particular to a UAV mission planning method based on graphic tags. Background Art

[0002] With the rapid development of drone technology, it has been widely used in many fields such as aerial photography, logistics distribution, surveying and mapping, inspection, search and rescue, etc. In actual application scenarios, drone mission planning is the key link to ensure its efficient and accurate execution of tasks.

[0003] In recent years, UAV mission planning methods based on graphic tags have gradually attracted attention. This method arranges graphic tags within a preset mission area, and the UAV performs the mission by recognizing the information on the graphic tags. Compared with traditional methods, graphic tags can provide high-precision location information, reduce the impact of GPS signal obstruction, and improve the accuracy of UAV positioning. The layout of graphic tags can be flexibly adjusted according to mission requirements and adapt to mission planning needs in different environments. However, existing UAV mission planning methods based on graphic tags still have some shortcomings. Traditional graphic tags usually use simple visual recognition methods with low recognition efficiency and cannot achieve real-time communication with the UAV. Existing methods often rely on pre-programmed paths, lack intelligent decision-making capabilities, and cannot dynamically adjust mission planning according to real-time environmental changes. In complex environments, communication between UAVs and graphic tags is easily interfered with, resulting in reduced system stability and reliability.

[0004] Chinese invention CN113220020B discloses a UAV mission planning method based on graphic tags, which focuses on guiding the UAV to perform tasks according to the tag sequence through visual recognition of graphic tags, and does not involve the application of RFID communication and improved algorithm planning path.

[0005] Chinese invention CN110347181B discloses an energy consumption-based distributed formation control method for UAVs, focusing on the distributed formation control of multiple UAVs. The formation cost function is mainly set based on the error between the real-time position of the UAVs and the target position, and does not involve the collection and processing of environmental data to guide task execution.

[0006] Therefore, the present invention proposes a UAV mission planning method based on graphic labels. Summary of the Invention

[0007] The present invention provides a UAV mission planning method based on graphic tags. By designing graphic tags with RFID chips and combining them with optimized communication protocols and path planning algorithms, it can provide UAVs with accurate location information and mission instructions, thereby enhancing the accuracy, reliability and flexibility of UAV mission planning in complex environments.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] A UAV mission planning method based on graph labels, comprising:

[0010] Step S1, designing a graphic tag with an RFID chip for drone mission planning, wherein the graphic tag includes an outer frame, a direction indicator, an icon, and an RFID chip;

[0011] Step S2: deploying a task network, placing multiple graphic labels in a preset task area, each graphic label corresponding to a task point;

[0012] Step S3: UAV initialization: equipping the UAV with an RFID reader, establishing a communication link with the graphic tag, and setting the initial position and orientation of the UAV;

[0013] Step S4: The RFID reader activates the graphic tag in the task area through the carrier signal and reads the 12-bit data packet containing the status code and timestamp;

[0014] Step S5, mission planning, performing hierarchical actions according to the state code bit pattern, using the improved A* algorithm to plan the path, and the UAV generates the mission path and action sequence;

[0015] Step S6: The drone performs the mission and monitors abnormal conditions in real time. During the mission, the drone performs path verification and built-in sensor calibration. After the mission is completed, the drone returns to its original position and resets the system status according to the landing icon.

[0016] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0017] The present invention can clearly and accurately indicate specific tasks through the various icon designs of graphic labels and the corresponding RFID status codes, enabling the drone to quickly identify and execute corresponding actions during the task execution process, reducing the decision-making time and the probability of misoperation during the task execution process.

[0018] The present invention can collect environmental data through the built-in sensor integrated into the RFID chip, and perform edge computing through a low-power processor to compress the environmental data into a status code, thereby realizing real-time perception and intelligent processing of the mission area environment.

[0019] By improving the A* algorithm, the present invention can adjust the path planning in real time according to dynamic factors such as the current position of the drone, the target position, and the status code of the graphic label, ensuring that the drone always chooses the optimal path to complete the task in a complex and changing environment.

[0020] The present invention optimizes the communication protocol and supports automatic adjustment of the communication frequency band according to environmental conditions and data transmission requirements, thereby improving the stability of data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 A flowchart of a method for planning a UAV mission based on graphic tags according to an embodiment of the present invention;

[0023] Figure 2 A schematic diagram of the RFID chip architecture provided by an embodiment of the present invention;

[0024] Figure 3 A schematic diagram of status code generation provided by an embodiment of the present invention;

[0025] Figure 4 A schematic diagram of the improved A* algorithm flow provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] To further illustrate the technical means and effectiveness of the present invention in achieving its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effectiveness of a graphic tag-based drone mission planning method proposed in accordance with the present invention. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0027] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0028] The following examples are for illustrative purposes only and are not intended to limit the scope of the present invention.

[0029] The following describes in detail a specific solution of a UAV mission planning method based on graphic tags provided by the present invention with reference to the accompanying drawings.

[0030] Please refer to Figure 1 The following is a flowchart of a method for planning a UAV mission based on graphic tags according to an embodiment of the present invention, which includes the following steps:

[0031] Step S1, designing a graphic tag with an RFID chip for drone mission planning, the graphic tag including: an outer frame, a direction indicator, an icon, and an RFID chip;

[0032] Wherein, step S1 further includes the following sub-steps:

[0033] S1-1, the outer frame is hexagonal, the distance between opposite sides is 5cm, the border width is 4mm, the outer frame is made of anti-metal material, suitable for UAV take-off and landing platforms or field environments;

[0034] S1-2, the outer frame adopts a high-contrast black and white two-color design to ensure the visual recognition stability of the graphic label in complex environments;

[0035] An ultra-high frequency RFID antenna is embedded inside the S1-3 outer frame and directly integrated with the RFID chip for data transmission and communication;

[0036] S1-4, the direction indicator is a static arrow printed on the top of the inner side of the outer frame. The arrow is 1.5 cm long and the tip of the static arrow points to the preset reference direction of the graphic label. It is used to assist in the calibration of the UAV take-off and landing and mission path.

[0037] S1-5, the icon is located in the circular dotted frame inside the direction indicator and is used to indicate specific tasks, including: start, hover, emergency landing and data return;

[0038] The start icon is a black solid circle with a diameter of 2 cm and an RFID status code of 0000. The drone records the mission starting point and initializes the flight parameters.

[0039] The hover icon is a double vertical line of equal width, 1.5cm high and 0.5cm wide. RFID status code bit 2 is 1, indicating abnormal vibration. The drone needs to hover for 30 seconds.

[0040] The landing icon is a solid black inverted equilateral triangle with a 2cm diameter circumscribed circle. The RFID status code is 1001, indicating that the temperature is too high and the drone needs to make an emergency landing.

[0041] The data return icon is 3 solid dots with a diameter of 4mm and a spacing of 3mm. The RFID status code bit 3 is 1, indicating that the humidity is too high and the drone needs to return data.

[0042] S1-6, RFID chip integrates built-in sensor, low-power processor and embedded memory;

[0043] The built-in sensor is used to collect environmental data and is connected to the processor through a multi-mode interface, and the multi-mode interface includes at least one digital interface and one analog interface;

[0044] The low-power processor performs edge computing on the collected environmental data and compresses the environmental data into a 4-bit status code through a status code generation algorithm;

[0045] The specific steps of the status code generation algorithm include:

[0046] Bit 4 is the temperature abnormality flag. When the temperature exceeds 50°C, it is set to 1 and triggers the drone to make an emergency landing. Otherwise, it is set to 0.

[0047] Bit 3 is the humidity composite flag, which is set to 1 when the humidity exceeds 80% relative humidity and triggers the drone to transmit data back, otherwise it is set to 0;

[0048] Bit 2 is the vibration composite flag. When the vibration exceeds 0.5g, it is set to 1 and triggers the drone to hover for 30 seconds. Otherwise, it is set to 0.

[0049] Bit 1 is an odd parity bit and is generated according to the following rules:

[0050] When bit 4 = 1, the status code is forced to 1001 and triggers an emergency landing. Bit 1 is fixed to 1 and does not participate in any verification logic;

[0051] In other cases, the odd check bit value is set according to the parity of the number of 1s in the first three bits. If the number of 1s in the current three bits is odd, bit 1 is 0; if the number of 1s in the current three bits is even, bit 1 is 1. When forcibly generating 1001, the parity check result of the first three bits is ignored.

[0052] The embedded memory is divided into a built-in sensor raw data area and a status code storage area.

[0053] Please refer to Figure 2 This is a schematic diagram of the RFID chip architecture provided by an embodiment of the present invention.

[0054] Please refer to Figure 3 This is a schematic diagram of status code generation provided by an embodiment of the present invention.

[0055] It should be noted that the RFID antenna is responsible for establishing a wireless communication link between the graphic tag and the reader to achieve energy transmission and data exchange.

[0056] The preset reference direction refers to a fixed direction pre-defined when designing a graphic label. This direction will serve as a reference for the drone's takeoff and landing and mission path calibration.

[0057] The ultra-high frequency (840-960 MHz) belongs to the long-range radio frequency band with a working distance of 5-10 meters, and supports high-speed mobile identification of drones.

[0058] The built-in sensors include temperature sensor, humidity sensor and vibration sensor. The temperature sensor is used to monitor the temperature changes in the drone's operating environment, the humidity sensor is used to monitor the humidity changes in the drone's operating environment, and the vibration sensor is used to monitor the vibration of the drone.

[0059] A low-power processor is a microprocessor that operates at low power consumption.

[0060] Embedded memory is a storage device integrated into an embedded system to store program code, data, and system configuration information.

[0061] Step S2: deploying the task network, placing multiple graphic labels in a preset task area, with each graphic label corresponding to a task point;

[0062] Wherein, in step S2, the following sub-steps are also included:

[0063] S2-1, select the graphic label spacing mode according to the task type. Task types include:

[0064] In the inspection task mode, set the distance between graphic tags to 5-10 meters to ensure that there is a 1.5-2 meter overlap between the RFID read and write areas of adjacent graphic tags;

[0065] In search task mode, set the graphic label spacing to 2-5 meters to form a high-density grid layout;

[0066] S2-2, directional deployment, so that the direction indicator of each graphic label points to the next target graphic label, forming a directed task chain;

[0067] S2-3, adjust the installation angle of the graphic tag so that the RFID antenna plane forms an angle of 45°±5° with the preset flight altitude of the drone.

[0068] It should be noted that the overlap area ensures that the drone will not miss any graphic label during the flight.

[0069] A high-density grid layout can improve search efficiency and ensure that the drone can cover the entire mission area.

[0070] The angle of 45°±5° between the RFID antenna plane and the preset flight altitude of the drone ensures the optimal signal transmission between the RFID antenna and the RFID reading device of the drone.

[0071] Step S3: UAV initialization: equip the UAV with an RFID reader, establish a communication link with the graphic tag, and set the initial position and orientation of the UAV;

[0072] Wherein, in step S3, the following sub-steps are also included:

[0073] S3-1, equips the drone with an RFID reader that supports communication. The RFID reader supports UHF 860-960MHz, with a default operating frequency band of 920MHz and a backup frequency band of 868MHz;

[0074] S3-2, initialize the RFID reader and establish a communication link with the graphic tag to ensure the stability and reliability of data transmission;

[0075] S3-3: Before the drone takes off, the spectrum analyzer built into the RFID reader scans the noise distribution in the 920MHz operating frequency band. If three consecutive read failures occur, the noise level is greater than -60dBm, or the tag spacing in the path planning is greater than 8m, the frequency band is switched to 868MHz.

[0076] S3-4, according to the communication distance between the UAV and the graphic tag, the data rate and transmission power are synchronously adjusted according to the preset ratio;

[0077] The estimation formula for communication distance is:

[0078]

[0079] Where d represents the communication distance between the drone and the graphic label, P tx Indicates the transmit power in dBm, RSSI indicates the received signal strength indicator in dBm, and C indicates the environmental attenuation constant in dB. In open space, C is 45.

[0080] S3-5, set the initial position and direction of the drone to ensure that the drone can accurately align with the direction of the first graphic label.

[0081] It should be noted that the spectrum analysis module built into the RFID reader is a component used to monitor and analyze the wireless signal spectrum. It can detect and analyze information such as signal strength, frequency distribution, and noise level within the RFID reader's operating frequency band in real time.

[0082] In wireless communications, when the signal strength falls below -60dBm, communication reliability decreases significantly. Therefore, -60dBm is selected as the threshold to ensure that when the noise level exceeds this value, the system can switch to other frequency bands in a timely manner to avoid communication interruption.

[0083] Step S4: The RFID reader activates the graphic tag in the task area through the carrier signal and reads the 12-bit data packet containing the status code and timestamp;

[0084] Wherein, in step S4, the following sub-steps are also included:

[0085] S4-1, the drone sends a carrier signal with a frequency of 920MHz, which lasts for 10ms and activates the energy collection circuit of the graphic tag;

[0086] S4-2, data request, sends a standard Query command, which includes:

[0087] Preamble: 8-bit fixed mode 0xA5;

[0088] Command code: 0x01;

[0089] Target graphic tag ID: 4 bytes;

[0090] S4-3, after receiving the instruction, the graphic tag reads the stored environmental data from the RFID chip to trigger edge computing, and combines the 4-bit status code and the 8-bit timestamp into a 12-bit data packet;

[0091] S4-4, the graphic tag returns a 12-bit data packet, which includes:

[0092] High 4 bits: status code;

[0093] Lower 8 bits: timestamp;

[0094] S4-5, data verification, the drone verifies that the odd parity bit and timestamp of the data packet are ≤500ms away from the local clock. If the verification fails, the data is discarded and no retransmission is triggered. If the timestamps of three consecutive graphic tags are abnormal, the drone clock synchronization program is triggered.

[0095] Data verification methods include:

[0096] When the status code bit 4 is 1, it is determined to be an emergency instruction, and the status code bit 4 is verified to be 1 and the odd parity of the lower 8 bits of the timestamp is verified separately;

[0097] When status code bit 4 is 0, odd parity check is performed on the complete 12-bit data packet including the status code and timestamp;

[0098] The status code verification of emergency commands takes precedence over the regular verification process.

[0099] It should be noted that the energy harvesting circuit of the graphic tag is activated by receiving energy from the carrier signal, ensuring that the strength and duration of the carrier signal are sufficient to activate the circuit.

[0100] The Query command is a standard communication command used to read data from an RFID tag. It is sent by the RFID reader to the RFID tag to request specific information or trigger a specific operation.

[0101] The preamble is used to synchronize and identify the start of the data packet. 0xA5 is a common synchronization code used to ensure that the receiving end can correctly identify the starting position of the data packet.

[0102] 0x01 indicates a command to request data, ensuring that all graphic tags can recognize and respond to this command code.

[0103] The 4-byte ID is used to uniquely identify each graphic tag, ensuring that each tag has a unique ID and that the reader can correctly parse and match it.

[0104] After receiving the instruction, the graphic tag performs edge computing through the built-in low-power processor to generate a status code and timestamp.

[0105] The odd parity bit is used to detect single-bit errors during data transmission. Ensure that the reader and graphic tag use the same algorithm when generating and verifying the odd parity bit.

[0106] Timestamp verification is used to ensure that the timestamp of the graphic label is synchronized with the local clock of the drone. If the timestamp deviation exceeds 500ms, it may indicate clock drift or communication delay.

[0107] Step S5, mission planning, performing hierarchical actions according to the state code bit pattern, using the improved A* algorithm to plan the path, and the UAV generates the mission path and action sequence;

[0108] Wherein, in step S5, the following sub-steps are also included:

[0109] S5-1, status code parsing, the drone performs hierarchical decision-making based on the read 4-bit status code bit pattern, where the status code bits represent bit 4, bit 3, bit 2, and bit 1 from high to low, respectively. The status code bit pattern includes: bit 4 = 0, bit 3 = 1, bit 2 = 1, and status code 1001;

[0110] When bit 4 = 0, the UAV performs normal flight mission;

[0111] When bit 3 = 1, the drone performs the data return mission;

[0112] When bit 2 = 1, the drone performs a 30-second hovering mission;

[0113] When the status code is 1001, the drone performs an emergency landing mission;

[0114] When the status code triggers multiple commands at the same time, the tasks are executed in the order of emergency landing > hovering > data return > normal flight;

[0115] When status code bit 2=1 and bit 3=1 are triggered at the same time, hovering is performed first and then data is returned;

[0116] S5-2, dynamic path planning, uses an improved A* algorithm to dynamically adjust the path based on the current position and target position of the drone;

[0117] Improvements to the A* algorithm include:

[0118] S5-2-1, set each graphic label position to a path node, including the following fields:

[0119] "id": 4-byte graphic tag ID, used to uniquely identify each graphic tag;

[0120] "Coordinates": (x, y, z), indicating the position coordinates of the graphic label in three-dimensional space;

[0121] "Status code": 4-bit binary, indicating the status information of the graphic label;

[0122] "Direction angle": θ tag Indicates the angle between the direction indicator of the graphic label and the true north direction, with the true north direction as 0 and increasing clockwise;

[0123] S5-2-2, the formula for dynamic cost calculation is:

[0124] f(m)=g(m)×(1+α·S)+h(m)+β·max(0,∣θ-θ tag -15°)

[0125] Among them, f(m) represents the total cost of node m, which is used to evaluate the optimal path from the starting point to the target point, m represents a specific node in the path planning, g(m) represents the cumulative path cost calculated by the communication distance formula, α represents the weight coefficient of the dynamic selection of the status code, S represents the decimal value of the 4-bit status code returned by the graph label, h(m) represents the Euclidean distance from the current node m to the target end point, β expresses the direction deviation penalty coefficient, θ represents the current heading angle of the drone, and θ tag Expresses the angle between the direction indicator of the graphic label and the true north direction;

[0126] The value of α is adjusted according to the state code characteristics, which include: bit 4 = 1, bit 2 = 1 and other states;

[0127] When bit 4 = 1, α is 3.0;

[0128] When bit 2 = 1, α is 5.0;

[0129] In other states, α takes the value of 0;

[0130] The calculation formula for h(m) is:

[0131]

[0132] Among them, x m Indicates the horizontal coordinate of node m, y m Indicates the vertical coordinate of node m, x goal and y goal Indicates the horizontal and vertical coordinates of the target end point;

[0133] The dynamic adjustment method of β is:

[0134]

[0135] RSSI stands for Received Signal Strength Indicator (dBm). RSSI > -60dBm indicates good communication, while RSSI ≤ -60dBm indicates interference.

[0136] S5-3, decompose the path into a sequence of atomic actions, including:

[0137] The speed and altitude of the drone match the spacing between graphic labels;

[0138] When status code bit 4 is 1, hover and start thermal imaging scanning;

[0139] Dynamically adjust communication parameters according to the frequency band switching conditions defined in S3-3.

[0140] Please refer to Figure 4 A schematic diagram of the improved A* algorithm flow provided by an embodiment of the present invention.

[0141] It should be noted that atomic action sequence refers to breaking down complex tasks into a series of basic, indivisible actions. These basic actions are the smallest operation units that the drone can perform independently when performing tasks.

[0142] The direction indicator works in conjunction with the improved A* algorithm, in which the direction deviation penalty coefficient β is set to zero when the status code bit 4 is 1, giving priority to avoiding high-temperature areas.

[0143] The improved A* algorithm process includes the following steps:

[0144] Add the starting point to the Open list; the Open list stores the nodes to be processed;

[0145] Check whether the Open list is empty. If the Open list is empty, the path planning fails and the algorithm ends.

[0146] Take the node n with the smallest f(n) from the Open list, check whether node n is the target node, if so, return the optimal path, if not, remove node n from the Open list and add it to the Close list; f(n) represents the dynamic cost of the starting point, and the Close list stores the nodes that have been processed;

[0147] Expand node n’s neighbor nodes m, and for each neighbor node m, calculate its dynamic cost f(m);

[0148] Update the node status and add m to the Open list;

[0149] The return path starts from the end point and goes back to the starting point through the parent node;

[0150] Step S6: The drone performs the mission and monitors abnormal conditions in real time. During the mission, the drone performs path verification and built-in sensor calibration. After the mission is completed, the drone returns to its original position and resets the system status according to the landing icon.

[0151] Wherein, in step S6, the following sub-steps are also included:

[0152] S6-1, the UAV starts the mission execution according to the generated mission path and action sequence;

[0153] S6-2, task execution monitoring, triggers abnormal condition processing when the following conditions occur, including: graphic tag reading failure for three consecutive times, communication interruption, battery power <20% and status code bit 2 = 1 appearing three times in a row;

[0154] If the graphic tag fails to be read three times in a row, the drone switches to the 868MHz frequency band and reduces the flight speed by 50%;

[0155] When the signal is interrupted, the drone will fly to the next graphic label along the direction indicator;

[0156] When the battery level is less than 20%, the drone is forced to return to the nearest charging point;

[0157] When the status code with bit 2=1 appears three times in a row, the drone terminates the mission;

[0158] When multiple abnormal conditions are detected at the same time, the response is based on the priority of communication interruption > low battery > read failure > status code abnormality;

[0159] S6-3 automatically performs the following operations after completing every 5 graphic label accesses, including:

[0160] Path backtracking verification verifies whether the parity of the status codes of visited graph labels conforms to the expected distribution;

[0161] Built-in sensor calibration, correcting the drift of the drone's built-in sensors based on the temperature and humidity data of the graphic labels;

[0162] S6-4, after the drone completes all tasks, it lands according to the graphic label indicated by the landing icon, clears all task states, and initializes the drone to the pre-takeoff state, waiting for the next start.

[0163] It should be noted that the nearest charging point is defined as the location of a graphic label marked with a start icon in the task area.

[0164] Verify that the status code parity of visited graph tags follows the expected distribution. If not, log the exception and perform further inspection.

[0165] The drift of the drone's built-in sensor is corrected based on the temperature and humidity data of the graphic label. The specific calibration algorithm includes calculating the average value of the temperature and humidity data and adjusting the sensor offset.

[0166] In this way, a graph labeling-based UAV mission planning method can be realized.

[0167] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A UAV mission planning method based on graphic labels, characterized in that: The method includes: Step S1, designing a graphic tag with an RFID chip for drone mission planning, wherein the graphic tag includes an outer frame, a direction indicator, an icon, and an RFID chip; Step S2: deploying a task network, placing multiple graphic labels in a preset task area, each graphic label corresponding to a task point; Step S3: UAV initialization: equipping the UAV with an RFID reader, establishing a communication link with the graphic tag, and setting the initial position and orientation of the UAV; Step S4: The RFID reader activates the graphic tag in the task area through the carrier signal and reads the 12-bit data packet containing the status code and timestamp; Step S5, mission planning, performing hierarchical actions according to the state code bit pattern, using the improved A* algorithm to plan the path, and the UAV generates the mission path and action sequence; Step S6: The drone performs the mission and monitors abnormal conditions in real time. During the mission, the drone performs path verification and built-in sensor calibration. After the mission is completed, the drone returns to its original position and resets the system status according to the landing icon.

2. The method for UAV mission planning based on graphic tags according to claim 1, characterized in that: Wherein, step S1 further includes the following sub-steps: S1-1, the outer frame is hexagonal, the distance between opposite sides is 5cm, the frame width is 4mm, and the outer frame is made of anti-metal material, which is suitable for UAV take-off and landing platforms or field environments; S1-2, the outer frame adopts a high-contrast black and white two-color design to ensure the visual recognition stability of the graphic label in complex environments; S1-3, an ultra-high frequency RFID antenna is embedded inside the outer frame and directly integrated with the RFID chip for data transmission and communication; S1-4, the direction indicator is a static arrow printed on the top inner side of the outer frame. The arrow is 1.5 cm long and the tip of the static arrow points to the preset reference direction of the graphic label to assist in the calibration of the UAV take-off and landing and mission path. S1-5, the icon is located in a circular dotted frame inside the direction indicator and is used to indicate a specific task, including: start, hover, emergency landing, and data return; The icon for starting a mission is a black solid circle with a diameter of 2 cm and an RFID status code of 0000. The drone records the mission starting point and initializes the flight parameters. The hovering task icon is a double vertical line of equal width, 1.5 cm high and 0.5 cm wide. The RFID status code bit 2 is 1, indicating abnormal vibration. The drone needs to hover for 30 seconds. The landing mission icon is a black solid inverted equilateral triangle with a 2cm circumscribed circle. The RFID status code is forced to be 1001, indicating that the temperature is too high and the drone needs to make an emergency landing. The icon for the data return task is 3 solid dots with a diameter of 4mm and a spacing of 3mm. The RFID status code bit 3 is 1, indicating that the humidity is too high and the drone needs to return data. S1-6, the RFID chip integrates a built-in sensor, a low-power processor and an embedded memory; The built-in sensor is used to collect environmental data and is connected to the processor via a multi-mode interface, wherein the multi-mode interface includes at least one digital interface and one analog interface; The low-power processor performs edge computing on the collected environmental data and compresses the environmental data into a 4-bit status code through a status code generation algorithm; The embedded memory is divided into a built-in sensor raw data area and a status code storage area.

3. The UAV mission planning method based on graphic tags according to claim 1, characterized in that: Wherein, in step S2, the following sub-steps are also included: S2-1, selecting a graphic label spacing mode according to the task type, wherein the task types include: In the inspection task mode, set the distance between graphic tags to 5-10 meters to ensure that the RFID read / write areas of adjacent graphic tags overlap by 1.5-2 meters. In search task mode, set the graphic label spacing to 2-5 meters to form a high-density grid layout; S2-2, directional deployment, so that the direction indicator of each graphic label points to the next target graphic label, forming a directed task chain; S2-3, adjust the installation angle of the graphic tag so that the RFID antenna plane forms an angle of 45°±5° with the preset flight altitude of the drone.

4. The method for UAV mission planning based on graphic tags according to claim 1, characterized in that: Wherein, in step S3, the following sub-steps are also included: S3-1, equip the drone with an RFID reader that supports communication. The RFID reader supports ultra-high frequency 860-960MHz, with a default operating frequency band of 920MHz and a backup frequency band of 868MHz; S3-2, initialize the RFID reader and establish a communication link with the graphic tag to ensure the stability and reliability of data transmission; S3-3: Before the drone takes off, the spectrum analyzer built into the RFID reader scans the noise distribution in the 920MHz operating frequency band. If three consecutive read failures occur, the noise level is greater than -60dBm, or the tag spacing in the path planning is greater than 8m, the frequency band is switched to 868MHz. S3-4, according to the communication distance between the UAV and the graphic tag, the data rate and transmission power are synchronously adjusted according to the preset ratio; The estimation formula of the communication distance is: Where d represents the communication distance between the drone and the graphic label, P tx Indicates the transmit power in dBm, RSSI indicates the received signal strength indicator in dBm, and C indicates the environmental attenuation constant in dB. In open space, C is 45. S3-5, set the initial position and direction of the drone to ensure that the drone can accurately align with the direction of the first graphic label.

5. The UAV mission planning method based on graphic tags according to claim 1, characterized in that: Wherein, in step S4, the following sub-steps are also included: S4-1, the drone sends a carrier signal with a frequency of 920 MHz, which lasts for 10 ms and activates the energy collection circuit of the graphic tag; S4-2, data request, sends a standard Query instruction, the Query instruction includes: Preamble: 8-bit fixed mode 0xA5; Command code: 0x01; Target graphic tag ID: 4 bytes; S4-3, after receiving the instruction, the graphic tag reads the stored environmental data from the RFID chip to trigger edge computing, and combines the 4-bit status code and the 8-bit timestamp into a 12-bit data packet; S4-4, the graphic tag returns a 12-bit data packet, which includes: High 4 bits: status code; Lower 8 bits: timestamp; S4-5, data verification, the drone verifies that the odd parity bit and timestamp of the data packet are ≤500ms away from the local clock. If the verification fails, the data is discarded and no retransmission is triggered. If the timestamps of three consecutive graphic tags are abnormal, the drone clock synchronization program is triggered. The data verification method includes: When the status code bit 4 is 1, it is determined to be an emergency instruction, and the status code bit 4 is verified to be 1 and the odd parity of the lower 8 bits of the timestamp is separately verified; When status code bit 4 is 0, odd parity check is performed on the complete 12-bit data packet including the status code and timestamp; The status code check of the emergency instruction takes precedence over the regular check process.

6. The UAV mission planning method based on graphic tags according to claim 1, characterized in that: Wherein, in step S5, the following sub-steps are also included: S5-1, status code parsing, the drone performs hierarchical decision-making based on the read 4-bit status code bit pattern, where the status code bits represent bit 4, bit 3, bit 2, and bit 1 from high to low, respectively. The status code bit pattern includes: bit 4 = 0, bit 3 = 1, bit 2 = 1, and status code 1001; When bit 4=0, the UAV performs a normal flight mission; When bit 3=1, the drone performs the data return task; When bit 2=1, the drone performs a 30-second hovering mission; When the status code is 1001, the UAV performs an emergency landing mission; When the status code triggers multiple commands at the same time, the tasks are executed in the order of emergency landing > hovering > data return > normal flight; When the status code bit 2=1 and bit 3=1 are triggered at the same time, data transmission is performed after hovering first; S5-2, dynamic path planning, uses an improved A* algorithm to dynamically adjust the path based on the current position and target position of the drone; S5-3, decompose the path into a sequence of atomic actions, including: The speed and altitude of the drone match the spacing between graphic labels; When status code bit 4 is 1, hover and start thermal imaging scanning; Dynamically adjust communication parameters according to the frequency band switching conditions defined in S3-3.

7. The UAV mission planning method based on graphic labels according to claim 1, characterized in that: Wherein, in step S6, the following sub-steps are also included: S6-1, the UAV starts the mission execution according to the generated mission path and action sequence; S6-2, task execution monitoring, triggering abnormal condition processing when the following conditions occur: the graphic tag fails to read three times in a row, communication is interrupted, the battery level is less than 20%, and the status code bit 2=1 appears three times in a row; If the graphic tag fails to be read three times in a row, the drone switches to the 868MHz frequency band and reduces the flight speed by 50%; When the signal is interrupted, the drone flies to the next graphic label along the direction indicator; When the battery level is less than 20%, the drone is forced to return to the nearest charging point; When the status code with bit 2=1 appears three times in a row, the UAV terminates the mission; When multiple abnormal conditions are detected at the same time, the response is based on the priority of communication interruption > low battery > read failure > status code abnormality; S6-3 automatically performs the following operations after completing every 5 graphic label accesses, including: Path backtracking verification verifies whether the parity of the status codes of visited graph labels conforms to the expected distribution; Built-in sensor calibration, correcting the drift of the drone's built-in sensors based on the temperature and humidity data of the graphic labels; S6-4, after the drone completes all tasks, it lands according to the graphic label indicated by the landing icon, clears all task states, and initializes the drone to the pre-takeoff state, waiting for the next start.

8. The method for UAV mission planning based on graphic tags according to claim 2, characterized in that: The specific steps of the status code generation algorithm include: Bit 4 is the temperature abnormality flag. When the temperature exceeds 50°C, it is set to 1 and triggers the drone to make an emergency landing. Otherwise, it is set to 0. Bit 3 is the humidity composite flag, which is set to 1 when the humidity exceeds 80% relative humidity and triggers the drone to transmit data back, otherwise it is set to 0; Bit 2 is the vibration composite flag. When the vibration exceeds 0.5g, it is set to 1 and triggers the drone to hover for 30 seconds. Otherwise, it is set to 0. Bit 1 is an odd parity bit and is generated according to the following rules: When bit 4 = 1, the status code is forced to 1001 and triggers an emergency landing. Bit 1 is fixed to 1 and does not participate in any verification logic; In other cases, the value of the odd check bit is set according to the parity of the number of 1s in the first three bits. If the number of 1s in the current three bits is odd, bit 1 is 0; if the number of 1s in the current three bits is even, bit 1 is 1. When forcibly generating 1001, the parity check result of the first three bits is ignored.

9. The UAV mission planning method based on graphic labels according to claim 6, characterized in that: The improved A* algorithm includes: S5-2-1, set each graphic label position to a path node, including the following fields: "id": 4-byte graphic tag ID, used to uniquely identify each graphic tag; "Coordinates": (x, y, z), indicating the position coordinates of the graphic label in three-dimensional space; "Status code": 4-bit binary, indicating the status information of the graphic label; "Direction angle": θ tag Indicates the angle between the direction indicator of the graphic label and the true north direction, with the true north direction as 0 and increasing clockwise; S5-2-2, the formula for dynamic cost calculation is: f(m)=g(m)×(1+α·S)+h(m)+β·max(0,∣θ-θ tag (∣-15°) Among them, f(m) represents the total cost of node m, which is used to evaluate the optimal path from the starting point to the target point, m represents a specific node in the path planning, g(m) represents the cumulative path cost calculated by the communication distance formula, α represents the weight coefficient of the dynamic selection of the status code, S represents the decimal value of the 4-bit status code returned by the graph label, h(m) represents the Euclidean distance from the current node m to the target end point, β expresses the direction deviation penalty coefficient, θ represents the current heading angle of the drone, and θ tag Expresses the angle between the direction indicator of the graphic label and the true north direction; The value of α is adjusted according to the state code characteristics, and the state code characteristics include: bit 4=1, bit 2=1 and other states; When bit 4=1, the value of α is 3.0; When bit 2=1, the value of α is 5.0; In the other states, α takes the value of 0; The calculation formula of h(m) is: Among them, x m Indicates the horizontal coordinate of node m, y m Indicates the vertical coordinate of node m, x goal and y goal Indicates the horizontal and vertical coordinates of the target end point; The dynamic adjustment method of β is: RSSI stands for Received Signal Strength Indicator (dBm). An RSSI > -60dBm indicates good communication, and an RSSI ≤ -60dBm indicates an interference environment.

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