Unmanned aerial vehicle laser obstacle removing system and obstacle removing method based on multi-mode switching

Abstract

The invention relates to the technical field of unmanned aerial vehicle laser obstacle clearance, and discloses an unmanned aerial vehicle laser obstacle clearance system and method based on multi-mode switching, through an environment sensing module and an obstacle recognition module, the system can analyze and recognize the type of an obstacle according to the image feature of the obstacle, and meanwhile, through the design of a multi-mode switching module, the obstacle clearance efficiency is improved. Therefore, the system can automatically select and switch to the most suitable obstacle clearing mode according to different obstacle types, so that the obstacle clearing efficiency is improved, and the obstacle clearing effect and safety are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV laser obstacle removal, and particularly to a UAV laser obstacle removal system and method based on multi-mode switching. Background Art

[0002] UAV laser obstacle removal is a technology that uses a UAV equipped with a laser device to remove obstacles on transmission lines. The laser obstacle removal UAV carries devices such as a laser module, a controller, and a power supply on a multi-rotor UAV, and uses the high temperature and high precision characteristics of the laser to remove obstacles. When a foreign object is found on the transmission line, the ground operator controls the UAV to fly to a suitable position. After determining the specific situation of the obstacle through the onboard high-definition camera and image recognition system, the laser emitter is activated, and the laser beam is irradiated onto the obstacle, and the obstacle is ablated, cut, or vaporized by the high temperature generated by the laser, so as to achieve the purpose of removal.

[0003] Compared with the traditional manual power outage operation, the UAV laser obstacle removal significantly shortens the obstacle removal time. There is no need for personnel to directly contact the high-voltage line, reducing the safety risk. At the same time, no strong mechanical force is generated during the laser obstacle removal process, reducing the possibility of secondary damage to the transmission line itself.

[0004] However, currently, traditional UAV obstacle removal systems often adopt a single obstacle removal method. When facing complex and changeable obstacles, they only have one obstacle removal method and cannot identify and automatically switch to the most suitable obstacle removal mode according to the obstacle type, resulting in a lack of flexibility and adaptability in the overall obstacle removal system and being difficult to quickly adjust according to the task requirements and environmental changes. Summary of the Invention

[0005] The present invention provides a UAV laser obstacle removal system and method based on multi-mode switching to solve the problem that the existing technology cannot identify and automatically switch to the most suitable obstacle removal mode according to the obstacle type, resulting in a lack of flexibility and adaptability in the overall obstacle removal system.

[0006] To achieve the above object, the present invention is realized through the following technical solutions:

[0007] In a first aspect, the present invention provides a UAV laser obstacle removal system based on multi-mode switching, including:

[0008] A UAV module, which is used as a basic carrier to carry the remaining modules of the system to perform flight tasks;

[0009] The environmental perception module includes a collection unit and an environmental modeling unit. The collection unit is used to collect environmental image data around the obstacle and the distance between the obstacle and the drone in real time to obtain environmental collection information. The environmental modeling unit is used to learn and classify and analyze the environmental collection information, and transmit the analysis result to the obstacle recognition module;

[0010] The obstacle recognition module is used to detect and identify obstacle information according to the analysis result. The obstacle information includes obstacle type, shape and size;

[0011] The multi-mode switching module is used to store all modes and their parameters, and is also used to select and switch to the most suitable obstacle clearing mode according to the obstacle information, and is also used to judge whether to continue cutting according to the information input by the cutting state perception module;

[0012] The laser cutting module is used to adjust the power of the laser, the laser emission mode, the laser emission position and the cutting accuracy according to the obstacle clearing mode of the multi-mode switching module;

[0013] The cutting state perception module is used to obtain the real-time state of laser cutting the obstacle, judge whether the cutting at the current position is completed, and use the judgment result as the signal input of the multi-mode switching module.

[0014] Optionally, the collection unit includes a vision-distance compound perception unit installed on the drone body, which is used to capture image information of the transmission line, the surrounding environment and the distance between the obstacle and the drone in real time to obtain a video picture.

[0015] Optionally, the obstacle recognition module includes an image recognition unit and a material determination unit;

[0016] The image recognition unit is used to identify the characteristic information of the obstacle to obtain an image recognition result. The characteristic information includes the size, shape and color of the obstacle;

[0017] The material determination unit is used to emit low-power pulsed laser in the pre-cutting stage based on laser-induced breakdown spectroscopy technology, detect the emission spectrum line through the spectrometer on the drone, and judge the type of the obstacle in combination with the image recognition result of the image recognition unit.

[0018] Optionally, the multi-mode switching module includes a multi-mode preset unit and a judgment and switching unit. The multi-mode preset unit is used to set all cutting modes of the drone laser obstacle clearing system. All cutting modes include high-precision cutting mode, powerful crushing mode, layer-by-layer clearing mode and edge trimming mode.

[0019] Optionally, all of the cutting modes are associated with a set of preset specific cutting data, which includes laser power, cutting speed, laser lens parameters, and laser emission mode.

[0020] Optionally, the laser cutting module includes a laser emission controller, a power regulator, a lens zoom mechanism, and an optical path controller. The laser emission controller is used to adjust the laser emission mode according to the obstacle clearing mode of the multi-mode switching module; the power regulator is used to adjust the power of the laser according to the obstacle clearing mode of the multi-mode switching module; the lens zoom mechanism is used to adjust the cutting accuracy according to the obstacle clearing mode of the multi-mode switching module; the optical path controller is used to adjust the laser emission position according to the obstacle clearing mode of the multi-mode switching module.

[0021] Optionally, the cutting state sensing module includes a near-infrared sensor and a thermal imaging sensor;

[0022] The near-infrared sensor determines the type of the obstacle before obstacle clearing by detecting the visible light reflectivity and infrared absorption rate reflected by the obstacle, and is also used to determine whether the obstacle at the laser irradiation position has been cleared during obstacle clearing;

[0023] The thermal imaging sensor determines whether the laser cutting is completed by detecting the temperature distribution of the obstacle, and adjusts the cutting mode and cutting parameters in real time by detecting the cutting completion time.

[0024] This application also provides a method for laser obstacle clearing of an unmanned aerial vehicle based on multi-mode switching, which is applied to the above-mentioned laser obstacle clearing system of an unmanned aerial vehicle based on multi-mode switching. The method includes:

[0025] S1. The operator controls the unmanned aerial vehicle to reach near the obstacle, adjusts the position of the unmanned aerial vehicle to make the lenses of the environment sensing module, the obstacle recognition module, and the laser cutting module face the obstacle, and makes the unmanned aerial vehicle stay in the obstacle clearing area. If it is not in the obstacle clearing area, the system alarms to prompt that it is not in the obstacle clearing area;

[0026] S2. The environment sensing module senses the environment around the obstacle in real time, captures the image information of the transmission line, the surrounding environment, and the distance between the obstacle and the unmanned aerial vehicle;

[0027] S3. The image recognition unit of the obstacle recognition module is used to identify the characteristics of the obstacle such as size, shape, and color. The material determination unit of the obstacle recognition module is based on the laser-induced breakdown spectroscopy technology. During the pre-cutting stage, a low-power pulse laser of 50 μs is emitted, the plasma emission spectrum is detected by the spectral analyzer on the unmanned aerial vehicle, and the visible light reflectivity and infrared absorption rate reflected by the obstacle are detected in real time by the near-infrared sensor of the cutting state sensing module. Then, combined with the image recognition result of the image recognition unit, the type of the obstacle is determined;

[0028] S4, the multi-mode switching module automatically selects and switches to the most suitable obstacle removal mode according to different obstacle types and parameters such as obstacle shape and size, and adjusts the laser parameters of the laser transmitter according to the distance between the obstacle and the drone;

[0029] S5. The near-infrared sensor of the cutting state sensing module detects the visible light reflectivity and infrared absorption rate reflected by the obstacle in real time. Combined with the temperature distribution of the obstacle detected by the thermal imaging sensor, it detects in real time whether the obstacle at the laser irradiation point has been cleared. The cutting mode and cutting parameters are adjusted in real time by detecting the cutting completion time.

[0030] S6. After the environment perception module and cutting state perception module detect that the obstacle has been cleared, the laser emission is stopped and the completion status is recorded by video and photos. The drone automatically flies back or is controlled by the operator to fly back.

[0031] Beneficial effects:

[0032] The UAV laser obstacle removal system based on multi-mode switching provided by the present invention, through the environmental perception module and the obstacle recognition module, the system can analyze and identify the obstacle type according to the image characteristics of the obstacle. At the same time, combined with the design of the multi-mode switching module, the system can automatically select and switch to the most suitable obstacle removal mode according to different obstacle types, so as to improve obstacle removal efficiency and ensure obstacle removal effect and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a structural block diagram of a UAV laser obstacle removal system based on multi-mode switching according to a preferred embodiment of the present invention;

[0034] Figure 2 The present invention is a flowchart of a UAV laser obstacle removal method based on multi-mode switching according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following is a clear and complete description of the technical solutions of the present invention. It should be understood that the embodiments described are only a portion of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are intended to fall within the scope of protection of the present invention.

[0036] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the field to which the present invention pertains. The "first", "second" and similar terms used in the present invention do not denote any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "a" or "one" do not denote a quantity limitation, but mean that there is at least one. The terms "connected" or "coupled" and the like are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms "upper", "lower", "left", "right" and the like are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship also changes accordingly.

[0037] Please refer to Figure 1 , a drone laser obstacle clearing system based on multi-mode switching provided by the present application, includes:

[0038] The drone module is used as a basic carrier to carry the remaining modules of the system to perform flight tasks;

[0039] The environment perception module includes a collection unit and an environment modeling unit. The collection unit is used to collect environmental image data around the obstacle and the distance between the obstacle and the drone in real time to obtain environmental collection information; the environment modeling unit is used to learn and classify and analyze the environmental collection information, and transmit the analysis result to the obstacle recognition module;

[0040] The obstacle recognition module is used to detect and identify obstacle information according to the analysis result. The obstacle information includes obstacle type, shape and size;

[0041] The multi-mode switching module is used to store all modes and their parameters, and is also used to select and switch to the most suitable obstacle clearing mode according to the obstacle information, and is also used to judge whether to continue cutting according to the information input by the cutting state perception module;

[0042] The laser cutting module is used to adjust the power of the laser, the laser emission mode, the laser emission position and the cutting accuracy according to the obstacle clearing mode of the multi-mode switching module;

[0043] The cutting state perception module is used to obtain the real-time state of the laser cutting the obstacle, judge whether the cutting at the current position is completed, and use the judgment result as the signal input of the multi-mode switching module.

[0044] In this embodiment, the environment modeling unit is a machine learning model constructed based on a convolutional neural network (CNN) for learning and classifying image features.

[0045] The above-mentioned UAV laser obstacle clearing system based on multi-mode switching can, through the environment perception module and the obstacle recognition module, analyze and identify the types of obstacles according to the image features of the obstacles. Meanwhile, combined with the design of the multi-mode switching module, the system can automatically select and switch to the most suitable obstacle clearing mode according to different types of obstacles, so as to improve the obstacle clearing efficiency, ensure the obstacle clearing effect and safety.

[0046] Optionally, the acquisition unit includes a vision-distance compound perception unit installed on the UAV body, which is used to capture the image information of the transmission line, the surrounding environment and the distance between the obstacle and the UAV in real time to obtain a video picture.

[0047] In this way, a clear video picture can be obtained through the vision-distance compound perception unit installed on the UAV body.

[0048] Optionally, the obstacle recognition module includes an image recognition unit and a material determination unit;

[0049] The image recognition unit is used to identify the characteristic information of the obstacle to obtain an image recognition result, and the characteristic information includes the size, shape and color of the obstacle;

[0050] The material determination unit is used to emit low-power pulsed laser in the pre-cutting stage based on the laser-induced breakdown spectroscopy technology, detect the emission spectrum line through the spectral analyzer on the UAV, and combine the image recognition result of the image recognition unit to judge the type of the obstacle.

[0051] Optionally, the multi-mode switching module includes a multi-mode preset unit and a judgment and switching unit. The multi-mode preset unit is used to set all the cutting modes of the UAV laser obstacle clearing system, and all the cutting modes include a high-precision cutting mode, a strong crushing mode, a layered clearing mode and an edge trimming mode.

[0052] In this optional embodiment, the multi-mode preset unit is used to set all the cutting modes of the UAV laser obstacle clearing system. The system adopts a dynamic mode selection matrix to construct a 6D decision parameter space (material, size, spatial pose, ambient temperature, ambient wind speed, remaining power). The system has a built-in multi-layer decision logic to achieve the optimal selection of the cutting mode through dynamic weight distribution.

[0053] Specifically, all the cutting modes are associated with a set of preset specific cutting data, and the cutting data includes laser power, cutting speed, laser lens parameters and laser emission mode.

[0054] Optionally, the laser cutting module includes a laser emission controller, a power regulator, a lens zoom mechanism, and an optical path controller. The laser emission controller is used to adjust the laser emission mode according to the obstacle clearing mode of the multi-mode switching module; the power regulator is used to adjust the power of the laser according to the obstacle clearing mode of the multi-mode switching module; the lens zoom mechanism is used to adjust the cutting accuracy according to the obstacle clearing mode of the multi-mode switching module; the optical path controller is used to adjust the laser emission position according to the obstacle clearing mode of the multi-mode switching module.

[0055] Optionally, the cutting state sensing module includes a near-infrared sensor and a thermal imaging sensor;

[0056] The near-infrared sensor determines the type of obstacle before obstacle clearing by detecting the visible light reflectivity and infrared absorption rate reflected by the obstacle, and is also used to determine whether the obstacle at the laser irradiation position has been cleared during obstacle clearing;

[0057] The thermal imaging sensor determines whether the laser cutting is completed by detecting the temperature distribution of the obstacle, and adjusts the cutting mode and cutting parameters in real time by detecting the cutting completion time.

[0058] Next, taking a complete example, the functions of the components of the above-mentioned obstacle clearing system based on the above-mentioned UAV laser obstacle clearing system will be introduced:

[0059] A UAV laser obstacle clearing system based on multi-mode switching includes: a UAV module, an environment sensing module, an obstacle recognition module, a multi-mode switching module, a laser cutting module, and a cutting state sensing module.

[0060] The UAV module includes a flight unit, a management unit, and a positioning unit. The UAV module is the basic carrier of the entire system and is responsible for carrying other modules to perform flight tasks. The specific content is as follows:

[0061] 1) The flight unit is the core of the flight controller. Through sensors such as gyroscopes and accelerometers installed inside it, it detects and measures the acceleration and rotational motion of the UAV, is responsible for calculating the flight attitude, controlling the control surfaces, performing flight tasks, etc., and determining the flight attitude and trajectory of the UAV.

[0062] 2) The management unit is responsible for the integration, power supply, and management of the relevant devices inside the environment sensing module. It can ensure that the loads of the relevant devices can work in coordination with the UAV module and the laser cutting module safely and effectively.

[0063] 3) The positioning unit uses GNSS (Global Navigation Satellite System) for navigation and positioning to ensure that the UAV can accurately reach the predetermined position and fly according to the preset flight path.

[0064] The environmental perception module includes a collection unit and an environmental modeling unit. Through the collaborative action of these two units, it can collect real-time image data of the environment around the obstacle and the distance between the obstacle and the UAV, providing key data support for subsequent obstacle clearance operations. The specific content is as follows:

[0065] 1) The collection unit includes a vision-distance composite perception unit, which is installed on the UAV body and is used to capture real-time image information of the transmission line, the surrounding environment, and the distance between the obstacle and the UAV, and provide a clear video picture to help the operator or the system accurately discover the position, shape, and size information of the obstacle.

[0066] 2) The environmental modeling unit is a machine learning model built based on a convolutional neural network (CNN) and is used for learning and classifying image features.

[0067] During the construction of the machine learning model, a large number of high-definition image data containing different obstacle types need to be collected to ensure the diversity and representativeness of the data. Then, the image data is labeled, that is, the type and position information of the obstacle in each image are clarified for the model to learn. Then, the labeled image data is divided into a training set and a validation set. The training set is used to train the model. The prediction result is calculated through forward propagation and compared with the true label, and the loss function value is calculated. The model parameters are updated using the backpropagation algorithm and an optimizer (such as the gradient descent method) to minimize the loss function.

[0068] Finally, repeat the above process for multiple training rounds until the model performance reaches stability or the preset number of training rounds is completed. After training, save the model parameters and structure for subsequent obstacle recognition tasks.

[0069] The obstacle recognition module includes an image recognition unit and a material determination unit, which are used to detect and identify obstacles based on the image data of the obstacles. The specific content is as follows:

[0070] 1) Image recognition: The image recognition unit uses image recognition and machine learning technologies to analyze and process the images collected by the high-definition camera, and automatically identify the type and feature information of the obstacles. The specific steps are as follows:

[0071] Analysis and processing: Perform grayscale conversion and median filtering on the original images collected by the high-definition camera to improve the image quality and enhance the image clarity.

[0072] Feature extraction: Use the feature extraction method of scale-invariant feature transform (SIFT) to extract features from the preprocessed images that can represent the image content. These features may include color, shape, texture, etc., and can reflect the important information and structure in the image.

[0073] Image recognition: Transmit the image data after feature extraction to the machine learning model, so that the machine learning model can determine the type, size, and position of the obstacle based on the features, and then select the corresponding obstacle cutting mode.

[0074] 2) Material determination: The material determination unit, based on the laser-induced breakdown spectroscopy (LIBS) technology, emits a 50 μs low-power pulsed laser during the pre-cutting stage, detects the plasma emission spectrum line through the spectral analyzer on the drone, and combines the image recognition result of the image recognition unit to determine the type of the obstacle.

[0075] The multi-mode switching module includes a multi-mode preset unit and a judgment switching unit, which are used to automatically select and switch to the most suitable obstacle clearing mode according to different obstacle types, so as to improve the obstacle clearing efficiency, ensure the obstacle clearing effect and safety. The system adopts a dynamic mode selection matrix to construct a 6D decision parameter space (material, size, spatial pose, ambient temperature, ambient wind speed, remaining battery power). The system has a built-in multi-layer decision logic to achieve the optimal selection of the cutting mode through dynamic weight allocation.

[0076] Specifically as follows:

[0077] 1) Mode preset: The multi-mode preset unit is used to set all the cutting modes of the drone laser obstacle clearing system, including high-precision cutting mode, strong crushing mode, layer-by-layer clearing mode, and edge trimming mode. Each mode is associated with a set of preset specific cutting data, and the cutting data includes laser power, cutting speed, laser lens parameters, and laser emission mode.

[0078] Among them, the high-precision cutting mode is used for obstacles that require fine cutting, such as wires, ropes, etc., corresponding to the first cutting data. The first cutting data is to perform fast and accurate cutting with a high-power, small-spot laser beam.

[0079] Power setting: In the high-precision cutting mode, the laser power is usually relatively high but not the highest. This is because this mode mainly pursues cutting precision rather than pure energy output. The higher power can ensure that the laser beam effectively vaporizes or melts the obstacle in a short time, and at the same time, through precise control, minimize the heat affected zone. For example, for wires or ropes with a relatively small diameter, the laser power may need to reach between dozens of watts and hundreds of watts, and the specific power value will be adjusted according to the specific material and diameter of the obstacle.

[0080] Speed setting: In order to achieve high-precision cutting, the cutting speed in this mode is usually slow. The slow cutting speed helps the laser beam to operate more precisely along the preset cutting path, reducing vibration and deviation, thereby improving the cutting precision.

[0081] Lens parameters: In the high-precision cutting mode, a laser lens with a small focal length and high focusing ability is required. Such a lens can focus the laser beam into an extremely small spot, thus achieving high-precision cutting. For example, using a short-focus lens can focus the laser beam into a spot with a diameter of only 30 micrometers or even smaller, meeting the precise cutting requirements for small obstacles.

[0082] Emission mode: The high-precision cutting mode usually adopts the continuous-wave (CW) laser emission mode. The continuous-wave emission mode can provide stable laser output and is suitable for obstacles with high requirements for cutting accuracy and relatively uniform materials. The modulated continuous-wave emission mode can further reduce the heat-affected zone and improve the cutting accuracy and quality by modulating the laser output power. For example, when cutting a metal wire, the modulated continuous-wave emission mode can adjust the laser output power and frequency according to the diameter and material of the metal wire to achieve more precise cutting.

[0083] The powerful crushing mode is used for obstacles that need to be quickly crushed, such as trees, building debris, etc., corresponding to the second cutting data. The second cutting data is to use a high-energy-density laser beam for crushing and combine the mobility of the drone for multi-point strikes.

[0084] Power setting: The powerful crushing mode requires a high-energy-density laser beam to quickly crush strong obstacles, so the laser power is usually set at a relatively high level. This is sufficient to transfer a large amount of energy to the obstacle in a short time, causing its internal structure to collapse and break quickly. For large and strong obstacles such as trees and building debris, the laser power may need to be several kilowatts or even higher to achieve an efficient crushing effect.

[0085] Speed setting: Since the powerful crushing mode needs to quickly crush strong obstacles, the cutting speed is relatively fast. A faster speed can make the laser beam act on different parts of the obstacle multiple times in a short time, improving the crushing efficiency. However, the speed cannot be too fast to avoid incomplete crushing or excessive impact force. For general trees or building debris, the cutting speed is about 10 meters per minute.

[0086] Lens parameters: The powerful crushing mode usually requires a laser lens with a large depth of field and a large spot size. A lens with a large depth of field can keep the energy density of the laser beam relatively stable within a certain distance range, enabling it to better adapt to the crushing requirements of obstacles with different distances and shapes. And a large spot size can increase the contact area between the laser and the obstacle, improving the crushing efficiency.

[0087] Emission Mode: The powerful fragmentation mode generally adopts the pulse emission mode. By emitting high-energy laser pulses, a large amount of energy can be transferred to the obstacle within an extremely short time, causing its interior to heat up, melt, and even vaporize rapidly, thus achieving rapid fragmentation. The pulse emission mode can also optimize the fragmentation effect by adjusting parameters such as the pulse width, frequency, and energy.

[0088] The layer-by-layer removal mode is used for relatively thick and stacked obstacles. After preliminary scanning or visual confirmation that the obstacle has a large thickness or stacked structure, such as multi-layered entangled wires, stacked branches, etc., corresponding to the third cutting data, the third cutting data is a laser beam with a low energy density and multiple pulses for layer-by-layer cutting. Combining the high-precision positioning and stable flight ability of the drone, the layer-by-layer peeling and removal of the obstacle are realized.

[0089] Power Setting: The layer-by-layer removal mode aims to peel and remove relatively thick and stacked obstacles layer by layer, so its laser power is relatively low. The lower power can avoid excessive damage to the obstacle, thus better controlling the cutting depth and achieving layer-by-layer cutting. For example, for multi-layered entangled wires or stacked branches, the laser power may only need about a few hundred watts, and different layers of the obstacle are gradually removed through multiple pulse actions.

[0090] Speed Setting: The cutting speed in the layer-by-layer removal mode is moderate. Too fast a speed may cause excessive removal of materials at one time, affecting the effect of layer-by-layer cutting; while too slow a speed will reduce the operation efficiency. The cutting speed in this mode will be adjusted according to the material and stacking situation of the obstacle, generally ranging from a few meters to more than ten meters per minute.

[0091] Lens Parameters: The powerful fragmentation mode usually requires a laser lens with a large depth of field and a large spot size. A lens with a large depth of field can keep the energy density of the laser beam relatively stable within a certain distance range, enabling it to better adapt to the fragmentation requirements of obstacles with different distances and shapes. And a large spot size can increase the contact area between the laser and the obstacle, improving the fragmentation efficiency.

[0092] Emission Mode: The layer-by-layer removal mode mostly adopts the pulse train emission mode. By emitting a series of continuous pulses, different layers of the obstacle can be gradually removed without generating an overly large heat-affected zone. The pulse train emission mode can flexibly adjust the number, interval, and energy distribution of the pulses to adapt to the layer-by-layer cutting requirements of obstacles with different materials and thicknesses. For example, when dealing with multi-layer plastic films, appropriate pulse train parameters can be selected according to the thickness and material of the film to achieve precise layer-by-layer peeling.

[0093] The edge trimming mode is applied after the main obstacle has been cleared. It is observed that the main obstacle has been cleared, but there are irregularities or residues at the edge, such as irregular branches or bark left after trimming a tree. Corresponding to the fourth cutting data, the fourth cutting data is a laser beam with low energy density and single pulse for edge trimming. Combining the high-precision positioning and stable flight ability of the drone, it realizes precise cutting and trimming of the obstacle edge, making it smoother and more regular.

[0094] Power setting: The edge trimming mode is mainly used for fine trimming of the obstacle edge to make it smoother and more regular, so the laser power is relatively low. The low-power laser beam can more precisely control the cutting depth and range, avoiding unnecessary damage to the surrounding area. For example, for the irregular branches or bark left after trimming a tree, the laser power may be only a few dozen watts, which is sufficient for slight trimming of the edge.

[0095] Speed setting: The edge trimming mode requires fine operations, so the cutting speed is slow. This can better control the movement trajectory of the laser beam and achieve precise trimming of the obstacle edge. For example, when trimming the edge of a branch, the cutting speed may be only a few centimeters to more than a dozen centimeters per minute to ensure that every irregular part can be carefully processed.

[0096] Lens parameters: The edge trimming mode requires a laser lens with high resolution and precise focusing ability. Such a lens can focus the laser beam into a very fine light spot and can accurately control the position and shape of the light spot to meet the requirements of precise trimming of the obstacle edge. For example, for fine trimming of the edge of a branch, a high-precision lens that can focus the laser beam to the sub-millimeter level may be required.

[0097] Emission mode: The edge trimming mode usually adopts a low-energy continuous wave or pulse emission mode. The low-energy continuous wave emission mode can provide stable laser output for fine trimming of the obstacle edge; the pulse emission mode can achieve a more accurate edge cutting effect by controlling the energy and frequency of the pulse.

[0098] 2) Matching and selection of modes: The multi-mode switching module stores all modes and their parameters, and is used to automatically select and switch to the most suitable obstacle clearing mode according to different obstacle types detected and recognized by the obstacle recognition module, as well as parameters such as the shape and size of the obstacle, so as to improve the obstacle clearing efficiency, ensure the obstacle clearing effect and safety.

[0099] The laser cutting module is the core component that performs the actual cutting operation, including a laser emission controller, a power regulator, a lens zoom mechanism, and an optical path controller. According to the obstacle clearing mode of the multi-mode switching module, the laser emission controller, the power regulator, the lens zoom mechanism, and the optical path controller are adjusted to regulate the power of the laser, the laser emission mode, the laser emission position, and the cutting accuracy.

[0100] The cutting state sensing module is used to sense the real-time state of the laser cutting obstacle, to judge whether the cutting at the current position is completed, and to serve as a signal input to the multi-mode switching module.

[0101] The cutting state sensing module includes a near-infrared sensor and a thermal imaging sensor. The near-infrared sensor, by detecting the visible light reflectivity and infrared absorption rate reflected by the obstacle, is used on the one hand to judge the type of the obstacle before obstacle clearing, and on the other hand to serve as a basis for judging whether the obstacle at the laser irradiation position has been cleared during obstacle clearing. The thermal imaging sensor, by detecting the temperature distribution of the obstacle, is used to judge whether the laser cutting is completed and to adjust the cutting mode and cutting parameters in real time by detecting the cutting completion time.

[0102] The UAV laser obstacle clearing system, through the environment sensing module and the obstacle recognition module, can analyze and identify the type of the obstacle according to the image characteristics of the obstacle. At the same time, combined with the design of the multi-mode switching module, the system can automatically select and switch to the most suitable obstacle clearing mode according to different types of obstacles, so as to improve the obstacle clearing efficiency, ensure the obstacle clearing effect and safety.

[0103] Please refer to Figure 2 , this application also provides an obstacle clearing method based on the above UAV laser obstacle clearing system, which is applied to the above UAV laser obstacle clearing system based on multi-mode switching. The method includes:

[0104] S1. The operator controls the UAV to reach near the obstacle, adjusts the position of the UAV so that the lenses of the environment sensing module, the obstacle recognition module, and the laser cutting module face the obstacle, and makes the UAV stay in the clearable area. If it is not in the clearable area, the system alarms to indicate that it is not in the clearable area;

[0105] S2. The environment sensing module senses the environment around the obstacle in real time, captures the image information of the transmission line, the surrounding environment, and the distance between the obstacle and the UAV;

[0106] S3. The image recognition unit of the obstacle recognition module is used to recognize the characteristics of obstacles such as size, shape, and color. The material determination unit of the obstacle recognition module, based on laser-induced breakdown spectroscopy technology, emits a 50-μs low-power pulsed laser during the pre-cutting stage, detects the plasma emission spectrum line through the spectral analyzer on the UAV, and real-time detects the visible light reflectivity and infrared absorption rate reflected back by the obstacle through the near-infrared sensor of the cutting state perception module. Then, combined with the image recognition result of the image recognition unit, it judges the type of the obstacle;

[0107] S4. The multi-mode switching module automatically selects and switches to the most suitable obstacle clearing mode according to different obstacle types and parameters such as the shape and size of the obstacle, and adjusts the laser parameters of the laser emitter according to the distance between the obstacle and the UAV;

[0108] S5. The near-infrared sensor of the cutting state perception module real-time detects the visible light reflectivity and infrared absorption rate reflected back by the obstacle, combines with the temperature distribution of the obstacle detected by the thermal imaging sensor, and real-time detects whether the obstacle at the laser irradiation position has been cleared. And it real-time adjusts the cutting mode and cutting parameters by detecting the cutting completion time;

[0109] S6. When it is detected by the environment perception module and the cutting state perception module that the obstacle has been cleared, stop the laser emission and record the state after completion by video and taking pictures. The UAV automatically flies back or is controlled by the operator to fly back.

[0110] The obstacle clearing method of the UAV laser obstacle clearing system can implement each embodiment of the obstacle clearing system of the above UAV laser obstacle clearing system, and can achieve the same beneficial effects. Here, it will not be elaborated.

[0111] The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations according to the concept of the present invention without creative labor. Therefore, all technical solutions that can be obtained by those skilled in the art in the technical field of the present invention based on the concept of the present invention through logical analysis, reasoning or limited experiments on the basis of the prior art should be within the protection scope determined by the claims.

Claims

1. A drone laser obstacle clearing system based on multi-mode switching, characterized in that, Including: A drone module, which is used as a basic carrier to carry the rest of the system modules to perform flight missions; An environmental perception module, including an acquisition unit and an environmental modeling unit. The acquisition unit is used to collect environmental image data around the obstacle and the distance between the obstacle and the drone in real time to obtain environmental acquisition information. The environmental modeling unit is used to learn and classify and analyze the environmental acquisition information, and transmit the analysis result to the obstacle recognition module; An obstacle recognition module, which is used to detect and identify obstacle information according to the analysis result. The obstacle information includes the type, shape and size of the obstacle; A multi-mode switching module, which is used to store all modes and their parameters, and is also used to select and switch to the most suitable obstacle clearing mode according to the obstacle information, and is also used to judge whether to continue cutting according to the information input by the cutting state perception module; A laser cutting module, which is used to adjust the power of the laser, the laser emission mode, the laser emission position and the cutting accuracy according to the obstacle clearing mode of the multi-mode switching module; A cutting state perception module, which is used to obtain the real-time state of laser cutting the obstacle, judge whether the cutting at the current position is completed, and use the judgment result as the signal input of the multi-mode switching module.

2. The drone laser obstacle clearing system based on multi-mode switching according to claim 1, wherein The acquisition unit includes a vision-distance composite perception unit installed on the drone body, which is used to capture image information of the transmission line, the surrounding environment and the distance between the obstacle and the drone in real time to obtain a video picture.

3. The drone laser obstacle clearing system based on multi-mode switching according to claim 1, characterized in that, The obstacle recognition module includes an image recognition unit and a material determination unit; The image recognition unit is used to recognize the characteristic information of the obstacle to obtain an image recognition result. The characteristic information includes the size, shape and color of the obstacle; The material determination unit is used to judge the type of the obstacle based on the laser-induced breakdown spectroscopy technology. In the pre-cutting stage, a low-power pulsed laser is emitted, and the emission spectrum line is detected by a spectral analyzer on the drone, and the image recognition result of the image recognition unit is combined.

4. A drone laser obstacle clearing system based on multi-mode switching according to claim 1, characterized in that, The multi-mode switching module includes a multi-mode preset unit and a judgment switching unit. The multi-mode preset unit is used to set all cutting modes of the drone laser obstacle clearing system. All the cutting modes include a high-precision cutting mode, a strong fragmentation mode, a layered clearing mode and an edge trimming mode.

5. The drone laser obstacle clearing system based on multi-mode switching according to claim 4, characterized in that, All the cutting modes are associated with a set of preset specific cutting data. The cutting data includes laser power, cutting speed, laser lens parameters and laser emission mode.

6. The drone laser obstacle clearing system based on multi-mode switching according to claim 1, characterized in that, The laser cutting module includes a laser emission controller, a power regulator, a lens zoom mechanism and an optical path controller. The laser emission controller is used to adjust the laser emission mode according to the obstacle clearing mode of the multi-mode switching module. The power regulator is used to adjust the power of the laser according to the obstacle clearing mode of the multi-mode switching module. The lens zoom mechanism is used to adjust the cutting accuracy according to the obstacle clearing mode of the multi-mode switching module. The optical path controller is used to adjust the laser emission position according to the obstacle clearing mode of the multi-mode switching module.

7. The drone laser obstacle clearing system based on multi-mode switching according to claim 1, characterized in that, The cutting state perception module includes a near-infrared sensor and a thermal imaging sensor; The near-infrared sensor determines the type of the obstacle before obstacle removal by detecting the visible light reflectivity and infrared absorption rate reflected by the obstacle, and is also used to determine whether the obstacle at the laser irradiation position has been completely removed during obstacle removal; The thermal imaging sensor is used to detect the temperature distribution of the obstacle to determine whether the laser cutting is completed and to adjust the cutting mode and cutting parameters in real time by detecting the cutting completion time.

8. A method for clearing obstacles with a drone laser based on multi-mode switching, which is applied to the drone laser obstacle clearing system based on multi-mode switching described in claim 1 above, and is characterized in that, The method includes: S1. The operator controls the UAV to approach the obstacle, adjusts the position of the UAV to make the lenses of the environment perception module, the obstacle recognition module, and the laser cutting module face the obstacle, and makes the UAV stay in the obstacle-removable area. If it is not in the obstacle-removable area, the system alarms to indicate that it is not in the obstacle-removable area; S2. The environment perception module perceives the environment around the obstacle in real time, captures the image information of the transmission line, the surrounding environment, and the distance between the obstacle and the UAV; S3. The image recognition unit of the obstacle recognition module is used to identify the characteristics of the obstacle such as size, shape, and color. The material determination unit of the obstacle recognition module, based on the laser-induced breakdown spectroscopy technology, emits a 50-μs low-power pulsed laser in the pre-cutting stage, detects the plasma emission spectrum line through the spectral analyzer on the UAV, and detects the visible light reflectivity and infrared absorption rate reflected by the obstacle in real time through the near-infrared sensor of the cutting state perception module, and then combines the image recognition result of the image recognition unit to determine the type of the obstacle; S4. The multi-mode switching module automatically selects and switches to the most suitable obstacle-removal mode according to different obstacle types and parameters such as the shape and size of the obstacle, and adjusts the laser parameters of the laser emitter according to the distance between the obstacle and the UAV; S5. The near-infrared sensor of the cutting state perception module detects the visible light reflectivity and infrared absorption rate reflected by the obstacle in real time, combines the temperature distribution of the obstacle detected by the thermal imaging sensor, detects in real time whether the obstacle at the laser irradiation position has been completely removed, and adjusts the cutting mode and cutting parameters in real time by detecting the cutting completion time; S6. When it is detected by the environment perception module and the cutting state perception module that the obstacle has been completely removed, stop the laser emission and record the state after completion by video and taking pictures, and the UAV automatically flies back or is controlled by the operator to fly back.

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