Material label information acquisition method and system based on unmanned aerial vehicle

Abstract

The invention provides a material label information collection method and system based on an unmanned aerial vehicle, and belongs to the technical field of logistics information collection, and the method comprises the steps that the unmanned aerial vehicle obtains the parameter information of a material unit in a station area, and the parameter information at least comprises the material type, the material number, the material boundary dimension, the material position and the label position; generating a set flight path according to the parameter information of the material unit; the unmanned aerial vehicle moves according to a set flight path and collects image information of the labels on the material units, and the unmanned aerial vehicle obtains environment information around the unmanned aerial vehicle in the moving process and adjusts the actual flight movement track of the unmanned aerial vehicle according to the environment information. The position and angle of the image acquisition unit on the unmanned aerial vehicle can be adjusted according to the position, size and other parameter information of the material unit, so that acquisition of image information of labels at different positions on the material units at different positions is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics information collection, and in particular to a material label information collection method and system based on unmanned aerial vehicle. Background Art

[0002] Material units are usually provided with labels that record data such as type, size, weight, etc. of the material unit for easy reading and management. There are problems such as high cost and low reliability when configuring RFID (radio frequency identification tags) on material units. The manual identification of labels on material units requires a large number of operators, increases labor costs, and increases the workload of operators. At the same time, the manual identification of labels on material units is also prone to problems such as misidentification and missed identification. During the transportation of material units such as steel coils inside and outside the factory, they are usually placed in unspecified positions on transportation tools such as logistics vehicles, resulting in different actual positions of labels on each material unit, making reading inconvenient. Taking steel coils as an example, steel coils can be placed on logistics vehicles in a vertical or horizontal manner, and steel coils are generally affixed with two labels. Due to the large variety of steel coils, different models and sizes, and different placement positions, the actual positions of the labels on each steel coil are various. At the same time, some labels are folded and deformed, and cannot be identified, so it is difficult to implement conventional methods such as image collectors such as cameras installed on driving vehicles to identify labels. Summary of the invention

[0003] In view of the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a material label information collection method and system based on drones, which is used to solve the problem in the prior art that material units are irregularly placed and difficult to identify through conventional image collectors.

[0004] To achieve the above objectives and other related objectives, the present invention provides a material label information collection method based on a drone, comprising:

[0005] The drone obtains parameter information of the material unit in the workstation area, wherein the parameter information at least includes material type, material quantity, material size, material location and label location;

[0006] Generate a set flight path according to parameter information of the material unit;

[0007] The drone moves according to the set flight path and collects image information of the label on the material unit. The drone obtains environmental information around the drone during movement and adjusts the actual flight movement trajectory of the drone according to the environmental information.

[0008] Optionally, during the movement of the drone, the image information of the label is identified. If the identification fails, the position of the drone is adjusted and the image information of the label on the material unit is re-collected.

[0009] Optionally, before the drone obtains parameter information of the material unit in the workstation area, the drone first moves to a preset observation point outside the workstation area, and the drone obtains parameter information of the material unit in the workstation area at the preset observation point.

[0010] Optionally, the drone obtains parameter information of the material unit through a laser radar unit and / or a depth image acquisition unit.

[0011] Optionally, parameter information of the material unit is respectively obtained by a laser radar unit and a depth image acquisition unit, and the parameter information respectively obtained by the laser radar unit and the depth image acquisition unit are fused to generate the set flight path.

[0012] Optionally, a positioning tag is provided in the workstation area, and the drone recognizes the positioning tag through a depth image acquisition unit, and calibrates the current position of the drone according to the recognition result.

[0013] Optionally, the temperature of the material unit is obtained, a safe distance between the drone and the material unit is determined according to the temperature of the material unit, and the actual flight trajectory of the drone is adjusted according to the safe distance.

[0014] Optionally, the set flight path includes a fast scanning path and a supplementary scanning path located after the fast scanning path, the fast scanning path surrounds all material units in the workstation area, and the supplementary scanning path is generated based on parameter information of material units whose label information is not collected in the fast scanning path.

[0015] Optionally, the set flight path passes through each of the material units in sequence.

[0016] Optionally, there are at least two labels on the material unit, the two labels are pasted at different positions, and the data recorded on the labels on the same material unit are the same.

[0017] Optionally, before the UAV moves according to the set flight path, the estimated power consumption of the UAV is determined based on the set flight path, and the power of the UAV is compared with the estimated power consumption. If the power of the UAV meets the estimated power consumption, the UAV moves according to the set flight path; if the power of the UAV does not meet the estimated power consumption, the UAV is charged.

[0018] The present invention also provides a drone-based material label information collection system, which is used to implement the drone-based material label information collection method as described in any one of the above claims, including a drone and a controller module, and the drone and the controller module are connected by a wireless signal.

[0019] As described above, the material label information collection method and system based on drones of the present invention has the following beneficial effects: using drones as carriers, and generating a set flight path according to the parameter information of the material unit, that is, the drone can adjust the position and angle of the image acquisition unit on the drone according to the parameter information such as the position and size of the material unit, thereby realizing the collection of image information of labels located at different positions on material units at different positions. The drone is flexible in movement and easy to control. During the movement, the drone obtains the environmental information around the drone and adjusts the actual flight movement trajectory of the drone according to the environmental information, thereby improving the anti-interference ability of the drone and improving the reliability of label information collection. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Shown is a flow chart of a material tag information collection method based on a drone in an embodiment of the present invention;

[0021] Figure 2 Shown is a schematic diagram of a drone in an embodiment of the present invention;

[0022] Figure 3 Shown is a schematic diagram of the position change of the binocular camera in an embodiment of the present invention;

[0023] Figure 4 Shown is a schematic diagram of the layout within the factory area in an embodiment of the present invention.

[0024] Explanation of the reference numerals: drone 1, temperature sensor 2, laser radar 3, binocular camera 4, wireless transceiver 5, battery 6, airborne controller 7, driving lane 8, isolation belt 9, industrial computer 10, observation point 11, work station area 12, logistics vehicle 13, wireless charging station 14. DETAILED DESCRIPTION

[0025] The following describes the embodiments of the present invention through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention.

[0026] It should be noted that the diagram provided in the present embodiment only illustrates the basic concept of the present invention in a schematic manner, so the diagram only shows the components related to the present invention rather than drawing according to the number, shape and size of the components during actual implementation. The type, quantity and ratio of each component during actual implementation can be a random change, and the component layout type may also be more complicated. The structure, ratio, size, etc. illustrated in the drawings of the present specification are only used to match the content disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the limiting conditions that the present invention can implement, so they have no technical substantive significance. Any modification of the structure, change of the proportional relationship or adjustment of the size should still fall within the scope of the technical content disclosed by the present invention without affecting the effect that the present invention can produce and the purpose that can be achieved. At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" quoted in this specification are only for the convenience of narration, and are not used to limit the scope of the present invention. The change or adjustment of its relative relationship should also be regarded as the scope of the present invention without substantially changing the technical content.

[0027] See also Figure 1 , this embodiment provides a material label information collection method based on a drone, comprising the following steps:

[0028] S10: The drone obtains parameter information of the material unit in the workstation area, where the parameter information at least includes material type, material quantity, material size, material location, and label location;

[0029] S20: Generate and set a flight path according to parameter information of the material unit;

[0030] S30: The drone moves along the set flight path and collects image information of the label on the material unit.

[0031] During the movement of the drone, the drone also obtains environmental information around the drone and adjusts the actual flight trajectory of the drone according to the environmental information.

[0032] In this embodiment, the drone can obtain parameter information of the material unit in the workstation area through the laser radar unit, and can also obtain parameter information of the material unit in the workstation area through the depth image acquisition unit. The laser radar unit can emit a laser beam to detect the position, speed and other characteristic quantities of the target, and has the advantages of high resolution, strong interference ability, good low-altitude detectability, small size, and light weight. The depth image acquisition unit is also a binocular camera, which can detect the distance information of the shooting space, thereby obtaining three-dimensional environmental data, and has the advantages of high accuracy.

[0033] The laser radar unit and the depth image acquisition unit can also be combined with each other to obtain parameter information of the material unit through the laser radar unit and the depth image acquisition unit respectively. The collected parameter information of the material unit is more comprehensive and accurate, which is conducive to improving the drone's ability to collect parameter information of material units in the work station area. The parameter information respectively obtained by the laser radar unit and the depth image acquisition unit are integrated to generate a set flight path. The generated set flight path is also more accurate and effective.

[0034] In this embodiment, the drone also obtains the temperature of the material unit, determines the safe distance between the drone and the material unit according to the temperature of the material unit, and adjusts the actual flight trajectory of the drone according to the safe distance.

[0035] like Figure 2 In this embodiment, the drone is equipped with an onboard controller, a binocular camera, a three-dimensional laser radar, a temperature sensor, a wireless transceiver, a battery, a wireless power receiving device, and the like.

[0036] LiDAR can obtain three-dimensional point clouds to obtain parameter information such as position and shape of material units in the workstation area. It can also measure the three-dimensional point cloud in front of the drone during flight to build a three-dimensional map, which is used to adjust the actual flight trajectory of the drone and achieve obstacle avoidance.

[0037] The binocular camera can be used to obtain environmental information around the drone, and the drone can also build a three-dimensional map and identify obstacles through the binocular camera. In this embodiment, during the flight of the drone, the laser radar unit and the depth image acquisition unit can also be used to obtain environmental information around the drone, and the drone can be positioned and avoid obstacles based on the fusion of the environmental information obtained by the laser radar unit and the depth image acquisition unit.

[0038] Specifically, in this embodiment, the UAV obtains environmental information around the UAV through a binocular camera and a three-dimensional laser radar at the same time. Based on the environmental information of the UAV obtained by the binocular camera and the three-dimensional laser radar, the three-dimensional environmental data is integrated to generate a three-dimensional map, thereby adjusting the actual flight trajectory of the UAV to achieve obstacle avoidance.

[0039] The fusion positioning of LiDAR and binocular camera, LiDAR can directly obtain 3D point cloud data, and binocular camera obtains 3D data through feature matching and parallax calculation.

[0040] Specifically, Z = (b × f) / d, where Z is the depth information, that is, the distance from the pixel in the image to the binocular camera, f is the focal length of the camera; b is the baseline distance between the two binocular cameras; d is the parallax. For each pixel in the image, a three-dimensional coordinate is calculated in this way, and then a three-dimensional point cloud of the entire scene is generated.

[0041] The fusion positioning of LiDAR and binocular camera adopts post-fusion method to fuse the 3D point cloud data of LiDAR with the 3D information of the camera, and uses the geometric relationships and features in 3D space to detect targets or reconstruct scenes, thereby establishing a 3D map.

[0042] Among them, all sensor devices (such as lidar and binocular cameras, etc.) need to be clock synchronized, using the time of the ground server as the reference time, and using the PTP (Precision Time Protocol) / gPTP (Generalized Precision Time Protocol) clock synchronization protocol to complete the clock synchronization between sensors to ensure that the point cloud data collected by the lidar and binocular camera are at the same time point.

[0043] In addition, there are three-dimensional markers in or around the workstation area to correct the three-dimensional mapping and positioning position. In this embodiment, a positioning tag can be set in the workstation area, and the drone recognizes the positioning tag through the depth image acquisition unit and calibrates the current position of the drone based on the recognition result.

[0044] Specifically, the identification result of the drone for the positioning tag includes the relative position relationship between the drone and the positioning tag, and also includes the coordinate information of the positioning tag. Through the relative position relationship between the drone and the positioning tag and the coordinate information of the positioning tag, the actual current position of the drone can be obtained, thereby calibrating the position of the drone. The coordinate information of the positioning tag can be directly read from the positioning tag by the drone, or the identity information of the positioning tag can be identified first, and then the coordinate information of the positioning tag matching the identity information of the positioning tag can be retrieved from the ground server or the drone locally according to the identity information of the positioning tag.

[0045] like Figure 3 As shown in the figure, considering the different positions of the steel coil labels, the binocular camera can be rotated 90° forward to a horizontal position in a vertical state, and can be rotated 360° around the front and rear directions of the drone in a horizontal position.

[0046] Specifically, the temperature sensor is used to measure the temperature of the space. The temperature of the material unit can be obtained through the temperature sensor, that is, the drone can obtain the temperature information of the material unit in the workstation area through the temperature sensor, so that the drone can control the distance between the drone and the material unit according to the measurement results, avoid the drone from getting too close to the high-temperature material unit such as steel coils and being damaged, and realize the temperature protection of the drone. When the drone avoids obstacles, the considerations are not limited to temperature, but also include material shape, intermediate obstacles, etc.

[0047] Acquiring the temperature information of the material unit in the workstation area is also the parameter information of the material unit in the workstation area. In step S20, the position and shape of the material unit in the workstation area can also be determined based on the temperature information of the material unit in the workstation area. Specifically, taking the steel coil as an example, the area in the workstation area with a higher temperature than other parts is usually the steel coil, and the area with the highest temperature in the workstation area is usually the location of the steel coil. Determining the position and shape of the material unit in the workstation area based on the temperature information of the material unit in the workstation area is conducive to improving the accuracy of the parameter information of the material unit in the workstation area obtained by the drone.

[0048] In this embodiment, the material unit is a steel coil, which can be placed upright as a vertical coil or horizontally as a horizontal coil. In step S20, that is, in the step of generating a set flight path according to the parameter information of the material unit, when the material unit is identified as a vertical coil, a work plan suitable for the vertical coil is first generated, and then the set flight path is generated according to the work plan. When the material unit is identified as a horizontal coil, a work plan suitable for the horizontal coil is first generated, and then the set flight path is generated according to the work plan. The work plan includes the steel coils to be photographed and the shooting order, and the set flight path is generated according to the steel coils to be photographed and the shooting order.

[0049] In step S30, during the movement of the drone, the image information of the label collected by the drone is identified. If the identification fails, the position of the drone is adjusted to re-collect the image information of the label on the material unit. The position of the drone can be adjusted to adjust the set flight path, or the actual flight movement trajectory of the drone, so that the binocular camera on the drone can re-shoot. During the movement of the drone, the image information of the label collected by the drone is identified. If the identification fails, the angle of the binocular camera can be adjusted, or the flight posture of the drone can be adjusted to facilitate the binocular camera to re-shoot.

[0050] In this embodiment, there are at least two labels on a material unit, and the two labels are attached at different locations. The labels on the same material unit record the same data. Increasing the number of labels helps reduce the risk of all labels on the material unit being unrecognizable due to label damage. Specifically, Figure 3 As shown, in this embodiment, the material unit is a steel coil. When the steel coil is a vertical coil, the two labels are located on the outside of the steel coil, and the two labels are located on opposite sides of the steel coil. When the steel coil is a horizontal coil, the two labels are located on the inside and outside of the steel coil, and the two labels are located at both ends of the horizontal coil axis.

[0051] Specifically, in this embodiment, the UAV path planning adopts the fusion of global path planning and local path planning, including the following steps:

[0052] Step 1: Obtain parameter information of material units in the workstation area from the drone at the preset observation point to determine the location of each material unit and the possible location area of ​​the label on the material unit. The possible location area of ​​the label can be confirmed based on the label setting rules and the type of material unit.

[0053] Step 2: The possible location area of ​​the label on each material unit, that is, in this embodiment, when the material unit is a vertical roll, the two opposite sides on the outer wall of the vertical roll, or when the material unit is a horizontal roll, one side of the outer wall of the horizontal roll and the side opposite to the inner wall, are used as the target points.

[0054] Step 3: Take the preset observation point as the starting point of the random number search of RRT (Rapidly-exploring Random Trees), take a certain range around the logistics vehicle (for example, within 1 meter around the logistics vehicle) as the restricted area, and calculate the Euclidean distance. Get multiple paths, and select the shortest path as the set flight path. Where ρ is the straight-line distance between the current point and the target point, x2, y2, z2 are the coordinates of the current point, and x1, y1, z1 are the coordinates of the target point.

[0055] Step 4: When the material tag positions are different or there are obstacles in the middle of the path, and the drone needs to adjust its position locally, a local path planning algorithm is used, such as the TEB (Time Elastic Band) algorithm. The TEB algorithm can use a variety of optimization objectives, including but not limited to the overall path length, trajectory running time, distance from obstacles, passing through intermediate path points, and compliance with drone dynamics, kinematics, and geometric constraints.

[0056] In this embodiment, before step S10, that is, before obtaining the parameter information of the material unit in the workstation area, the drone first moves to a preset observation point outside the workstation area, and the drone obtains the parameter information of the material unit in the workstation area at the preset observation point. The preset observation point is outside the workstation area, and there are relatively few flight obstacles, so it can fly quickly and improve work efficiency.

[0057] In a specific implementation of this example, the flight path is set to include a fast scanning path and a supplementary scanning path located after the fast scanning path. The fast scanning path surrounds all material units in the workstation area, and the supplementary scanning path is generated based on parameter information of material units whose label information is not collected in the fast scanning path.

[0058] In another specific implementation of this example, the flight path is set to pass through each material unit in sequence. In this embodiment, before the drone moves according to the set flight path, the estimated power consumption of the drone can be determined according to the set flight path, and then the power of the drone is compared with the estimated power consumption. If the power of the drone meets the estimated power consumption, the drone moves according to the set flight path. If the power of the drone does not meet the estimated power consumption, the drone is charged, and other drones can also be coordinated to operate.

[0059] Specifically, the flight time can be calculated based on the flight distance and flight speed. If the shooting angle is not good and positioning is required for shooting, additional positioning time is added to calculate the total power consumption. At the same time, the battery information of the BMS (battery management system) on the drone is received to obtain the remaining power. The remaining power is compared with the power consumption. If it cannot meet the next operation, wireless or wired charging is performed to charge the drone. After charging is completed, the charging is automatically cut off.

[0060] This embodiment also provides a drone-based material tag information collection system for implementing the drone-based material tag information collection method as described above, including a drone and a controller module, and the drone and the controller module are connected by wireless signals. In this embodiment, the controller module is an industrial computer.

[0061] The workshop layout is as follows Figure 4 As shown in the figure, in actual situations, logistics vehicles are usually used to transport steel coils inside factory workshops. There may be multiple lanes in the same workshop; there may be multiple workstations on the same lane. At the same time, there may be a separation zone in the middle of the lane, and logistics vehicles cannot pass through. A charging station is set up inside the factory workshop for charging drones. The charging station can be wired or wireless. There is no need for direct connection between the wireless charging station and the drone, which helps to reduce the difficulty of docking the drone for charging.

[0062] The workstation area has a parking area for parking logistics vehicles, and the logistics vehicles are parked in the parking area.

[0063] When collecting material tag information, the drone can be dispatched according to the operation plan or manually dispatched. After being dispatched, the drone departs from the wireless charging station and flies to the observation point of the corresponding workstation area. The workstation area closest to the observation point is the workstation area corresponding to the observation point.

[0064] The drone identifies the type, quantity, size, location and label position of the steel coils on the logistics vehicle, and transmits the information to an industrial computer on the ground that is compatible with the drone.

[0065] The industrial computer compares and analyzes the steel coil information with the pre-set digital twin model library to determine the type of steel coil, which can be vertical coil or horizontal coil. The pre-set model is called to generate an operation plan and flight path for the vertical coil or horizontal coil according to the steel coil type, and sends it to the drone.

[0066] For vertical coils, the two labels are located on opposite sides of the outer surface of the coil, and the shooting direction is perpendicular to the location of the labels. If the label on one side of the coil is folded or damaged and cannot be identified, identify the label on the other side of the coil.

[0067] For horizontal coils, the first label is located on the outer side of the coil, and the second label is located on the inner side of the coil away from the first label. If the outer label of the horizontal coil is folded or defaced, the inner label on the other side is identified.

[0068] In a specific embodiment, the flight path is set, and the set flight path generated according to the steel coil information includes a fast scanning path and a supplementary scanning path. In the first circle, the drone quickly circles all the steel coils along the fast scanning path to take pictures of labels as much as possible. Then, along the fast scanning path, fly to the steel coils that have not been photographed and take pictures of the labels. In other optional embodiments, the set flight path is generated to fly to each steel coil in turn according to the steel coil information and take pictures of the labels. During the flight, the drone needs to detect the temperature according to the temperature sensor and maintain the minimum detection distance from the steel coil to avoid radiating high temperature and causing the drone and airborne equipment to malfunction.

[0069] After the drone receives the operation plan and flight path, the onboard controller controls the drone to fly according to the operation plan and set flight path, and generates a three-dimensional map in real time to avoid obstacles. During the flight, the drone takes pictures of the steel coil labels, obtains the label image information, and sends the label image to the industrial computer.

[0070] The industrial computer performs label recognition on the label image and sends the recognition result to the information requester. If the recognition effect is poor, the adjusted set flight path and adjustment angle will be sent to the drone.

[0071] The drone flies according to the adjusted set flight path, adjusts the angle of the binocular camera according to the adjusted angle, re-photographs the label, and sends the re-photographed label image to the industrial computer.

[0072] If the drone adjusts the set flight path or the angle of the binocular camera multiple times, for example, after 2 times, and the recognition effect is still poor, a signal can be sent to humans for manual intervention.

[0073] If the labels of each steel coil are identified, the drone completes the steel coil label identification, and the drone flies back to the wireless charging station to wait for the next operation.

[0074] In actual situations, the number of workstations for a single drone to detect label information can be reasonably allocated based on the number of lanes and workstations in the workshop, as well as factors such as the operating rate. For example, a single drone can correspond to multiple workstations, a single ground industrial computer can correspond to multiple workstations, and a single wireless charging station can correspond to 1 to 2 lanes to reduce costs. It is understandable that drones can also fly to other workstations in the corresponding lanes or workstations on other lanes in the workshop according to the operation plan or manual scheduling to collect information on material labels.

[0075] In the manual or automatic operation of the drone, the drone can scan the point cloud data of the logistics vehicle and steel coils to generate digital twin models of the logistics vehicle and steel coils. Then, the parameters of the digital twin models of the logistics vehicle and steel coils can be manually confirmed and modified to update the preset digital twin models.

[0076] In summary, the drone-based material tag information collection method and system of this embodiment uses the drone as a carrier and generates a set flight path based on the parameter information of the material unit, that is, the drone can adjust the position and angle of the image acquisition unit on the drone according to the parameter information such as the position and size of the material unit, thereby realizing the collection of image information of labels located at different positions on material units at different positions. The drone is flexible and easy to control. During the movement, the drone obtains the environmental information around the drone and adjusts the actual flight trajectory of the drone according to the environmental information, thereby improving the anti-interference ability of the drone and improving the reliability of tag information collection.

[0077] The above embodiments are merely illustrative of the principles and effects of the present invention, and are not intended to limit the present invention. Anyone familiar with the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by a person of ordinary skill in the art without departing from the spirit and technical concept disclosed by the present invention shall still be covered by the claims of the present invention.

Claims

1. A material label information collection method based on drone, characterized in that: include: The drone obtains parameter information of the material unit in the workstation area, wherein the parameter information at least includes material type, material quantity, material size, material location and label location; Generate a set flight path according to parameter information of the material unit; The drone moves according to the set flight path and collects image information of the label on the material unit. The drone obtains environmental information around the drone during movement and adjusts the actual flight movement trajectory of the drone according to the environmental information.

2. The material label information collection method based on drone according to claim 1 is characterized in that: During the movement of the drone, the image information of the label is identified. If the identification fails, the position of the drone is adjusted to re-collect the image information of the label on the material unit.

3. The material label information collection method based on drone according to claim 1 is characterized in that: Before the drone obtains parameter information of the material unit in the workstation area, the drone first moves to a preset observation point outside the workstation area, and the drone obtains parameter information of the material unit in the workstation area at the preset observation point.

4. The material label information collection method based on drone according to claim 1 is characterized in that: The drone obtains parameter information of the material unit through a laser radar unit and / or a depth image acquisition unit.

5. The material label information collection method based on drone according to claim 4 is characterized in that: The parameter information of the material unit is obtained respectively through the laser radar unit and the depth image acquisition unit, and the parameter information respectively obtained by the laser radar unit and the depth image acquisition unit are integrated to generate the set flight path.

6. The material label information collection method based on drone according to claim 1 is characterized in that: The temperature of the material unit is obtained, a safe distance between the drone and the material unit is determined according to the temperature of the material unit, and an actual flight trajectory of the drone is adjusted according to the safe distance.

7. The material label information collection method based on drone according to claim 1 is characterized in that: The set flight path includes a fast scanning path and a supplementary scanning path located after the fast scanning path, the fast scanning path surrounds all material units in the workstation area, and the supplementary scanning path is generated based on parameter information of material units whose label information is not collected in the fast scanning path.

8. According to the drone-based material label information collection method according to claim 1, a positioning tag is set in the workstation area, the drone identifies the positioning tag through a depth image acquisition unit, and calibrates the current position of the drone according to the recognition result.

9. The material label information collection method based on drone according to claim 1 is characterized in that: There are at least two labels on the material unit, the two labels are pasted at different positions, and the data recorded on the labels on the same material unit are the same.

10. The material label information collection method based on drone according to claim 1 is characterized in that: Before the drone moves according to the set flight path, the estimated power consumption of the drone is determined according to the set flight path, and the power of the drone is compared with the estimated power consumption. If the power of the drone meets the estimated power consumption, the drone moves according to the set flight path; if the power of the drone does not meet the estimated power consumption, the drone is charged.

11. A material label information collection system based on drones, characterized in that: Used to implement the material tag information collection method based on a drone as described in any one of claims 1 to 10, comprising a drone and a controller module, wherein the drone and the controller module are connected by a wireless signal.

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