Unmanned aerial vehicle transportation system obstacle avoidance control method and photovoltaic cleaning system

Abstract

The invention discloses an unmanned aerial vehicle transportation system obstacle avoidance control method and a photovoltaic cleaning system, and belongs to the technical field of unmanned aerial vehicles. The unmanned aerial vehicle transportation system comprises a carrying unmanned aerial vehicle; the unmanned aerial vehicle transportation system obstacle avoidance control method comprises the following steps: in a hovering process of a carrying unmanned aerial vehicle, acquiring an image of a surrounding environment of the carrying unmanned aerial vehicle; determining the type of an obstacle in the surrounding environment of the carrying unmanned aerial vehicle and the distance between the obstacle and the carrying unmanned aerial vehicle according to the acquired image; if the obstacle is a bird and the distance between the obstacle and the carrying unmanned aerial vehicle is smaller than a first preset distance, executing a first avoiding strategy; if the obstacle is the floating object and the distance between the obstacle and the carrying unmanned aerial vehicle is smaller than a second preset distance, executing a second avoiding strategy; wherein the second preset distance is smaller than the first preset distance. The embodiment of the invention provides an obstacle avoidance strategy when the unmanned aerial vehicle transportation system hovers, and the safety of the unmanned aerial vehicle transportation system can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles (UAVs), and in particular to an obstacle avoidance control method for an UAV transport system and a photovoltaic cleaning system. Background Art

[0002] Currently, photovoltaic cleaning robots can be deployed onto and retrieved from photovoltaic panels using drone suspension. The drone transport system requires a hovering rotorcraft to suspend the photovoltaic cleaning robot. However, if the rotorcraft's blades are disturbed by aerial obstacles during operation, there is a risk of the drone falling, compromising the safety of the drone transport system. Summary of the Invention

[0003] The present invention provides an obstacle avoidance control method for a drone transportation system and a photovoltaic cleaning system to solve one of the technical problems raised in the above background technology.

[0004] In a first aspect, an embodiment of the present invention provides an obstacle avoidance control method for a UAV transport system, wherein the UAV transport system includes a carrier UAV; the obstacle avoidance control method for the UAV transport system includes:

[0005] Acquiring an image of the surrounding environment of the carrier drone during the hovering of the carrier drone;

[0006] Determining the type of obstacles in the surrounding environment of the carrier drone and the distance between the obstacles and the carrier drone based on the acquired images;

[0007] If the obstacle is a flying bird and the distance between the obstacle and the carrier drone is less than a first preset distance, executing a first avoidance strategy;

[0008] If the obstacle is a floating object and the distance between the obstacle and the carrier drone is less than a second preset distance, executing a second avoidance strategy;

[0009] The second preset distance is smaller than the first preset distance.

[0010] Optionally, the first avoidance strategy includes:

[0011] When the distance between the obstacle and the carrier drone is between the first preset distance and a third preset distance, activating the bird repellent; wherein the third preset distance is smaller than the first preset distance;

[0012] When the distance between the obstacle and the carrier drone is less than the third preset distance, controlling the carrier drone to avoid the obstacle;

[0013] The second avoidance strategy includes:

[0014] Get the current wind direction;

[0015] predicting a floating trajectory of the obstacle based on the current wind direction and the position of the obstacle;

[0016] If it is determined based on the floating trajectory that the obstacle will interfere with the blades of the carrier drone, the carrier drone is controlled to avoid the obstacle.

[0017] Optionally, controlling the carrier drone to avoid the obstacle includes:

[0018] If the obstacle is located below the carrier drone, controlling the carrier drone to fly upward;

[0019] If the obstacle is above the carrier drone, controlling the carrier drone to fly downward;

[0020] If the obstacle and the carrier drone are located on the same horizontal plane, the carrier drone is controlled to fly upward or downward.

[0021] Optionally, controlling the carrier drone to avoid the obstacle includes:

[0022] When there is only one obstacle, controlling the carrier drone to fly in a direction away from the obstacle;

[0023] When there are multiple obstacles, calculating the obstacle avoidance direction of the carrier drone away from each obstacle;

[0024] The carrier UAV is controlled to fly along the obstacle avoidance direction.

[0025] Optionally, a plurality of cameras are provided on the fuselage of the carrier drone, and the horizontal field of view of the plurality of cameras covers a 360° range around the fuselage of the carrier drone;

[0026] The acquiring of the image of the surrounding environment of the carrier drone includes: acquiring images captured by each camera on the carrier drone to obtain the image of the surrounding environment of the carrier drone.

[0027] Optionally, the drone transport system further includes: a hoist and a grabbing drone; the hoist is fixedly mounted on the carrier drone, and the hoist suspends the grabbing drone via a rope, and the grabbing drone is used to grab the photovoltaic cleaning robot; the method further includes:

[0028] With the grab drone already activated:

[0029] Acquire an image of the environment surrounding the grasping drone, and determine the type of obstacles in the environment surrounding the grasping drone and the distance between the obstacles and the grasping drone based on the acquired image;

[0030] If the obstacle is a flying bird, and the distance between the flying bird and the grabbing drone is greater than a fourth preset distance, controlling the grabbing drone to continue to remain in the started state;

[0031] If the obstacle is a flying bird, and the distance between the flying bird and the grabbing drone is less than the fourth preset distance, the bird repeller is activated and the grabbing drone is controlled to stop.

[0032] Optionally, when the distance between the flying bird and the grabbing drone is less than the fourth preset distance, before controlling the grabbing drone to stop, the method further includes:

[0033] Determining the flight direction of the bird based on the captured image of the drone's surroundings;

[0034] If the flight direction is toward the grabbing drone, controlling the grabbing drone to stop;

[0035] If the flight direction is toward the carrier drone, the grabbing drone is controlled to continue to remain in the started state, and the carrier drone's avoidance strategy for the flying bird is determined according to the distance between the flying bird and the carrier drone.

[0036] Optionally, the method further includes:

[0037] If the obstacle is a floating object, and the distance between the floating object and the grabbing drone is greater than a fifth preset distance: controlling the grabbing drone to continue to be in the started state; wherein the fifth preset distance is less than the fourth preset distance;

[0038] If the obstacle is a floating object, and the distance between the floating object and the grabbing drone is less than the fifth preset distance:

[0039] predicting a floating trajectory of the floating object based on the current wind direction and the position of the floating object;

[0040] If it is determined based on the floating trajectory that the floating object will interfere with the blades of the grabbing drone, controlling the grabbing drone to stop;

[0041] If it is determined based on the floating trajectory that the floating object will not interfere with the blades of the grabbing drone, the grabbing drone is controlled to continue to remain in the started state.

[0042] Optionally, when executing the first avoidance strategy or executing the second avoidance strategy and controlling the grabbing drone to continue to remain in the started state, the method further includes:

[0043] If the carrier drone is controlled to fly upward, the rope is released to a first length; wherein the first length is equal to the distance the carrier drone flies upward;

[0044] If the carrier drone is controlled to fly downward, the rope is retracted to a second length; wherein the second length is equal to the distance the carrier drone flies downward.

[0045] Optionally, a plurality of cameras are provided on the fuselage of the grabbing drone, and the horizontal field of view of the plurality of cameras covers a 360° range around the fuselage of the grabbing drone;

[0046] The acquiring of the image of the surrounding environment of the grasping drone includes: acquiring images captured by each camera on the grasping drone to obtain the image of the surrounding environment of the grasping drone.

[0047] Optionally, the photovoltaic cleaning robot is provided with a rotatable camera; the method further comprises:

[0048] Controlling the rotatable camera to rotate so that the field of view covers the carrying drone and the grabbing drone;

[0049] The acquiring of the image of the surrounding environment of the carrier drone comprises: acquiring the image of the surrounding environment of the carrier drone from the image captured by the rotatable camera;

[0050] The acquiring of the image of the surrounding environment of the captured drone includes: acquiring the image of the surrounding environment of the captured drone from the image captured by the rotatable camera.

[0051] In the second aspect, an embodiment of the present invention also provides a photovoltaic cleaning system, comprising: a drone transportation system and a photovoltaic cleaning robot; the drone transportation system is used to place the photovoltaic cleaning robot onto the photovoltaic panel and to recover the photovoltaic cleaning robot from the photovoltaic panel; wherein, the drone transportation system adopts the drone transportation system obstacle avoidance control method provided by any embodiment of the present invention to avoid obstacles.

[0052] In the obstacle avoidance control method for the drone transport system provided by the embodiment of the present invention, during the hovering process of the carrier drone, the obstacle type is distinguished based on the acquired image of the surrounding environment and different safety distances are set accordingly for obstacle avoidance. Since the speed of birds is generally faster than floating objects, and birds have autonomy in their movement direction relative to floating objects, avoiding birds earlier can effectively improve safety during hovering and avoid falls. Therefore, in the embodiment of the present invention, setting a larger safety distance for biological obstacles such as birds can effectively ensure the obstacle avoidance effect and ensure the safety of hovering; and setting a smaller safety distance for non-biological obstacles such as floating objects can avoid frequent obstacle avoidance operations and ensure the stability of hovering. Therefore, the embodiment of the present invention can effectively improve the safety and stability of the carrier robot during hovering, ensure that the photovoltaic cleaning robot can be smoothly deployed and recovered, and improve the safety of the drone transport system.

[0053] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0055] Figure 1 This is a flow chart of an obstacle avoidance control method for a UAV transportation system provided by an embodiment of the present invention;

[0056] Figure 2 is a flow chart of a first avoidance strategy provided by an embodiment of the present invention;

[0057] Figure 3 is a flow chart of a second avoidance strategy provided by an embodiment of the present invention;

[0058] Figure 4 is a schematic diagram of a drone transportation system provided by an embodiment of the present invention;

[0059] Figure 5 This is a flow chart of the control strategy for grabbing a drone provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0061] It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and the accompanying drawings are used to distinguish similar items and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, such that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein. Furthermore, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions.

[0062] An embodiment of the present invention provides an obstacle avoidance control method for a drone transport system, which can be applied to obstacle avoidance processing during the hovering process of the drone transport system. The method can be executed by a controller in the drone transport system. The drone transport system may include a carrier drone, which can serve as the main aircraft for transporting photovoltaic cleaning robots, robot dogs, and other transported items. To facilitate understanding of the technical solution of this application, the following example uses the implementation of the delivery and recovery of photovoltaic cleaning robots to photovoltaic panels as an example. The carrier drone is a rotor drone that can hover in the air, specifically a multi-rotor drone.

[0063] Figure 1 This is a flow chart of the obstacle avoidance control method for the UAV transportation system provided by an embodiment of the present invention. Figure 1 , the method comprises the following steps:

[0064] S110 . Acquire an image of the surrounding environment of the carrier drone during the hovering process of the carrier drone.

[0065] Specifically, when the carrier drone drops the photovoltaic cleaning robot onto the target photovoltaic panel and recovers the photovoltaic cleaning robot from the target photovoltaic panel, it hovers in the airspace above the target photovoltaic panel and can drop or recover the photovoltaic cleaning robot through a mechanical device carried on the carrier drone. The mechanical device includes at least a mechanical arm for clamping the photovoltaic cleaning robot, and may also include an RTK module, a camera, a lidar, etc. to accurately identify and locate the photovoltaic cleaning robot.

[0066] During the hovering process, images of the drone's surroundings can be captured in real time, and information about obstacles around the drone can be updated in real time. This allows the drone to avoid obstacles when they are detected. For example, images from multiple different perspectives can be captured to obtain complete information about the drone's surroundings.

[0067] S120: Determine the type of obstacles in the surrounding environment of the carrier drone and the distance between the obstacles and the carrier drone based on the acquired image.

[0068] In this step, machine learning and other methods can be used to perform image recognition on the acquired images to distinguish obstacle types and locate their locations. This embodiment does not limit the specific image recognition method. Obstacle types can be divided into two categories: flying birds and floating objects. Floating objects include non-living items such as plastic bags and paper. Based on different obstacle types and distances from the carrier drone, corresponding avoidance strategies can be implemented to ensure the carrier drone maintains a stable hover.

[0069] S130: If the obstacle is a flying bird and the distance between the obstacle and the carrier UAV is less than a first preset distance, execute a first avoidance strategy.

[0070] The first preset distance can be understood as the safe distance between a bird and a carrier drone. This can be set based on experience or by analyzing historical data on similar carrier drones affected by bird interference, resulting in hovering or even falling. For example, the first preset distance can be between 15 and 25 meters, such as 15, 20, or 25 meters. In specific applications, the first preset distance can also be set based on the size of the bird, for example, a longer first preset distance is set for larger birds.

[0071] The first avoidance strategy is a bird avoidance strategy, which can be established based on information such as the bird's flight habits. For example, if the distance between the bird and the carrier drone is greater than a first preset distance, the carrier drone may not be controlled to avoid the bird and the bird's position may be continuously monitored. The first avoidance strategy can be promptly executed if the bird enters the first preset distance range of the carrier drone.

[0072] S140: If the obstacle is a floating object and the distance between the obstacle and the carrier UAV is less than a second preset distance, execute a second avoidance strategy.

[0073] Among them, the second preset distance can be understood as the safe distance between floating objects and the carrier drone. It can be set specifically based on experience, or determined by analyzing historical data of similar carrier drones affected by floating objects and even falling. The second preset distance is smaller than the first preset distance. Since flying birds have autonomy in their movement direction and their speed is usually faster than that of floating objects, setting the safe distance for floating objects relatively small can minimize the control of the carrier robot's movement while ensuring hovering safety, thereby improving hovering stability. Exemplarily, the second preset distance can be between 10-20m, such as 10m, 15m or 20m, and is smaller than the selected first preset distance.

[0074] The second avoidance strategy is for floating objects and can be established based on information such as the floating object's buoyancy characteristics. For example, if the distance between the floating object and the carrier drone is greater than a second preset distance, the carrier drone may not be controlled to avoid the floating object and the position of the floating object may be continuously monitored. The second avoidance strategy can be promptly executed if the floating object enters the second preset distance range of the carrier drone.

[0075] It is understood that the acquired images of the environment surrounding the carrier drone cover image information within a first preset distance range from the carrier drone, so that an avoidance strategy can be implemented based on the type of obstacle captured and its distance from the carrier drone. When there are no obstacles within the image coverage area, the image acquisition frequency can be appropriately reduced to reduce power consumption. When an obstacle appears within the image coverage area, the image acquisition frequency can be appropriately increased to timely update the obstacle's location and initiate a corresponding response.

[0076] In the obstacle avoidance control method for the drone transport system provided by the embodiment of the present invention, during the hovering process of the carrier drone, the obstacle type is distinguished based on the acquired image of the surrounding environment and different safety distances are set accordingly for obstacle avoidance. Since the speed of birds is generally faster than floating objects, and birds have autonomy in their movement direction relative to floating objects, avoiding birds earlier can effectively improve safety during hovering and avoid falls. Therefore, in the embodiment of the present invention, setting a larger safety distance for biological obstacles such as birds can effectively ensure the obstacle avoidance effect and ensure the safety of hovering; and setting a smaller safety distance for non-biological obstacles such as floating objects can avoid frequent obstacle avoidance operations and ensure the stability of hovering. Therefore, the embodiment of the present invention can effectively improve the safety and stability of the carrier robot during hovering, ensure that the photovoltaic cleaning robot can be smoothly deployed and recovered, and improve the safety of the drone transport system.

[0077] The following are examples of avoidance strategies for different types of obstacles.

[0078] Figure 2This is a flow chart of the first avoidance strategy provided by an embodiment of the present invention. Figure 2 In one embodiment, optionally, the first avoidance strategy includes:

[0079] S210: When the distance between the obstacle and the carrier UAV is between the first preset distance and the third preset distance, activate the bird repellent.

[0080] Among them, the third preset distance is less than the first preset distance. In this case, the carrier drone can be temporarily controlled to maintain the current hovering state without taking evasive action, and the bird can be driven away from the vicinity of the carrier drone by relying on a bird repellent (not shown). If the bird repellent fails to repel the bird and the bird enters the range within the third preset distance from the carrier drone, then corresponding to the situation in S220, it is necessary to control the carrier drone to move to avoid the bird. Exemplarily, the third preset distance can be between 5-10m, for example, 5m, 7m, 9m or 10m.

[0081] S220: When the distance between the obstacle and the carrier drone is less than a third preset distance, control the carrier drone to avoid the obstacle.

[0082] In this case, while controlling the movement of the carrier drone to avoid flying birds, the bird repellent can still be controlled to remain in the activated state, so that the bird repelling and avoidance actions are performed simultaneously, avoiding the carrier drone from being affected by flying birds as much as possible.

[0083] This embodiment provides a first avoidance strategy of the pioneer bird and then avoidance, which can move the carrier drone as little as possible while ensuring the safety of hovering.

[0084] Figure 3 This is a flow chart of the second avoidance strategy provided by an embodiment of the present invention. Figure 3 In one embodiment, optionally, the second avoidance strategy includes:

[0085] S310: Obtain the current wind direction.

[0086] Among them, the UAV transport system can be equipped with a wind vane, and the wind direction can be obtained in real time based on the detection results of the wind vane when needed. The location of the wind vane can be set according to needs, for example, it can be set on the carrier UAV.

[0087] S320: Predict the floating trajectory of the obstacle based on the current wind direction and the position of the obstacle.

[0088] For example, the floating direction and speed of the obstacle can be determined based on the wind direction, wind speed, volume and mass of the obstacle, and the floating trajectory of the obstacle can be predicted by combining fluid mechanics and adopting machine learning and other methods. The specific prediction method is not described here.

[0089] S330. Determine whether the obstacle will interfere with the blades of the carrier UAV based on the floating trajectory; if so, execute S340; if not, execute S350.

[0090] For example, when the predicted floating trajectory passes through the blades of the carrier drone, it is considered that the obstacle will interfere with the blades of the carrier drone; otherwise, it will not interfere with the blades of the carrier drone.

[0091] The specific process of trajectory prediction and interference judgment can be:

[0092] For obstacles with a height difference from the carrier drone that is less than or equal to a preset height difference: When the current wind direction forms an acute angle with the line connecting the carrier drone and the obstacle, it is considered that the floating object is more likely to drift toward the carrier drone under the wind, interfering with the carrier drone's blades, and therefore needs to be avoided. When the current wind direction forms a non-acute angle with the line connecting the carrier drone and the obstacle (i.e., an obtuse angle or a right angle), it is considered that the floating object is more likely to drift away from the carrier drone under the wind, and will not interfere with the carrier drone's blades. This is a relatively safe situation and can be temporarily avoided. Among them, when the height difference between the floating object and the carrier drone is less than or equal to the preset height difference, it can be considered that the two are approximately on the same horizontal plane. The angle between the current wind direction and the line connecting the carrier drone and the obstacle can be used to determine whether the floating object is floating toward the carrier drone. The preset height difference can be less than 5m, for example, and can specifically be 3m or 2m. The preset height difference can be set according to actual conditions and is not limited here.

[0093] Furthermore, when the current wind direction forms a large acute angle with the line connecting the carrier drone and the obstacle, it can be considered that the probability of floating objects continuing to approach the carrier drone is low, indicating a relatively safe situation where they will not interfere with the carrier drone's propellers. Therefore, a preset acute angle threshold can be set. When the current wind direction forms an acute angle less than the preset acute angle threshold with the line connecting the carrier drone and the obstacle, step S340 is executed; otherwise, step S350 is executed, further minimizing the impact on the carrier drone's movement. The preset acute angle threshold can be 50°, 40°, 30°, or 20°, and can be set based on actual needs.

[0094] For obstacles whose height difference from the carrier drone is greater than the preset height difference: the current wind direction can be decomposed into a vertical component and a horizontal component; if the vertical component is from the horizontal plane where the obstacle is located toward the horizontal plane where the carrier drone is located, it can be considered that the floating object has the possibility of drifting towards the carrier drone. At this time, it can be further determined whether there is an acute angle between the horizontal component and the projection of the line between the carrier drone and the obstacle on the horizontal plane. If so, it can be considered that the floating object will interfere with the blades of the carrier drone under the influence of the wind and needs to be avoided. If not, it can be considered that the floating object will not interfere with the blades of the carrier drone and does not need to be avoided; if the vertical component is from the horizontal plane where the obstacle is located toward the direction away from the horizontal plane where the carrier drone is located, it can be considered that the floating object will not interfere with the blades of the carrier drone and can be temporarily avoided. For example, if a floating object is currently located on a horizontal plane below the carrier drone and the height difference exceeds a preset value, if the vertical component of the current wind direction is downward, it is not necessary to avoid the floating object; if the vertical component of the current wind direction is upward, and the horizontal component and the projection of the line between the carrier drone and the floating object on the horizontal plane form a right angle or an obtuse angle, it is also possible to avoid the floating object; if the vertical component of the current wind direction is upward, and the horizontal component and the projection of the line between the carrier drone and the floating object on the horizontal plane form an acute angle, it is necessary to control the avoidance of the floating object.

[0095] S340, control the carrier drone to avoid obstacles.

[0096] S350: Control the carrier drone to keep hovering at the original position.

[0097] This embodiment provides a second avoidance strategy combined with wind direction, which can minimize the movement of the carrier drone while ensuring hovering safety.

[0098] Based on the above embodiments, there are many ways to control the carrier drone to avoid obstacles. Several of them are described below, but they are not intended to limit the present invention.

[0099] In one embodiment, optionally, controlling the carrier drone to avoid obstacles includes:

[0100] If the obstacle is below the carrier drone, the carrier drone is controlled to fly upward.

[0101] If the obstacle is above the carrier drone, the carrier drone is controlled to fly downward.

[0102] If the obstacle and the carrier drone are on the same horizontal plane, the carrier drone is controlled to fly upward or downward.

[0103] This embodiment controls the carrier drone to dodge in the up and down directions, making the control logic easy to implement.

[0104] Specifically, taking a bird as an obstacle, if a bird appears within a first preset distance from the carrier drone, the bird repellent can be activated first. If the bird has not left and enters a third preset distance from the carrier drone, the bird's position relative to the carrier drone is determined. If the bird is above the carrier drone, the carrier drone is controlled downward; if the bird is below the carrier drone, the carrier drone is controlled upward; if the bird is on the same horizontal plane as the carrier drone, the carrier drone can be controlled either upward or downward.

[0105] In another embodiment, optionally, controlling the carrier drone to avoid obstacles includes:

[0106] If there is only one obstacle, the carrier drone is controlled to fly away from the obstacle. This direction away from the obstacle can also be referred to as the direction away from the obstacle. For floating objects, the direction away from the floating object can be determined based on the current wind direction and the angle between the current wind direction and the line connecting the floating object and the carrier drone. For flying birds, the direction away from the bird can be determined based on the bird's flight direction and the angle between its flight direction and the line connecting the bird and the carrier drone. As the obstacle moves, the carrier drone is controlled to fly away from the obstacle, gradually increasing the distance between the carrier drone and the obstacle until it exceeds the safety distance corresponding to the obstacle.

[0107] When there are multiple obstacles, the obstacle avoidance direction of the carrier drone is calculated to avoid each obstacle, and the carrier drone is controlled to fly along the obstacle avoidance direction. For example, the movement direction of the carrier drone away from each obstacle can be calculated first, and then the final obstacle avoidance direction is determined based on the calculated movement directions.

[0108] This embodiment controls the carrier drone to avoid obstacles in the direction away from them, thereby achieving precise obstacle avoidance.

[0109] Based on the above embodiments, optionally, the carrier drone is equipped with multiple cameras, each with a horizontal field of view encompassing a 360° angle around the carrier drone, thereby fully capturing information about the environment surrounding the carrier drone. It will be appreciated that the image range captured by each of the cameras covers at least a range within a first predetermined distance from the carrier drone. Accordingly, acquiring an image of the environment surrounding the carrier drone includes acquiring images captured by each of the cameras on the carrier drone to obtain an image of the environment surrounding the carrier drone.

[0110] Specifically, cameras can be installed on all four sides of the drone to detect floating objects or birds in the air. Based on the type of obstacle, the drone can then determine whether to activate a bird repellent or take evasive action. The existing cameras on the drone can also be used to capture images of the drone's surroundings, saving transportation system costs.

[0111] The above embodiments specifically explain the obstacle avoidance strategy of the carrier drone. Based on the above embodiments, the drone transport system may optionally include a grabbing drone mounted under the carrier drone, which can be used to locate the photovoltaic cleaning robot when the carrier drone is hovering, thereby enabling the deployment and recovery of the photovoltaic cleaning robot. Figure 4 The drone transport system may include: a carrier drone 100, a hoist 200, and a grabbing drone 300. The hoist 200 is fixed to the carrier drone 100, for example, fixed below the carrier drone 100. The hoist 200 suspends the grabbing drone 300 via a rope, and the grabbing drone 300 is used to grab the photovoltaic cleaning robot. The grabbing drone 300 is also a rotorcraft drone and can hover under control. A robotic arm can be installed below the grabbing drone 300 to grab and release the photovoltaic cleaning robot 400. The hoist 200 releases or retracts the grabbing drone 300 by releasing or retracting the rope. The grabbing drone 300 can be activated only when the photovoltaic cleaning robot 400 is needed. At other times, such as when the carrier drone is flying between the photovoltaic station and the robot warehouse, the grabbing robot 300 is not needed and can be controlled to stop.

[0112] Then, when the grabbing drone is already started, the method also includes an obstacle avoidance strategy for the grabbing drone to prevent the grabbing drone from being damaged by obstacles. Specifically, when the grabbing drone is already started, the method includes:

[0113] Obtain images of the environment surrounding the grasping drone, and determine the types of obstacles in the environment surrounding the grasping drone and the distance between the obstacles and the grasping drone based on the acquired images.

[0114] The image acquisition and processing process can be referenced in the acquisition and processing of images of the surrounding environment of the carrier drone, and will not be further described. For the grasping drone, the obstacle type is still distinguished as flying birds or floating objects. The following describes the obstacle avoidance strategies for the grasping drone for these two types of obstacles.

[0115] In one embodiment, when the obstacle is a flying bird, the following obstacle avoidance strategy may be implemented:

[0116] 1) If the distance between the flying bird and the grabbing drone is greater than a fourth preset distance, the grabbing drone is controlled to remain in the activated state.

[0117] The fourth preset distance can be understood as a safe distance between the bird and the grabbing drone, which can be determined based on experience or relevant historical data. When the bird is greater than the fourth preset distance from the grabbing drone, it can be considered relatively safe and there is no need to control the grabbing drone to stop.

[0118] 2) If the obstacle is a flying bird and the distance between the flying bird and the catching drone is less than a fourth preset distance, the bird repellent is activated and the catching drone is controlled to stop.

[0119] It is understandable that in this transport system, the carrier drone's hovering safety determines whether accidents such as falls occur. Compared to the carrier drone, even if the prehensile drone shuts down due to interference with its rotor blades, it remains suspended by a rope and will not fall. Therefore, the prehensile drone's bird avoidance strategy can be relatively simple, requiring only a fourth preset distance and direct control of the prehensile drone to stop when necessary to avoid entanglement. Complex movement avoidance strategies are no longer required for the prehensile drone, simplifying the control method. For example, bird repellents can be installed on both the carrier drone and the prehensile drone. When the carrier drone's avoidance strategy requires activation of a bird repellent, either only the carrier drone's or all of its devices can be activated. When the prehensile drone's avoidance strategy requires activation of a bird repellent, either only the prehensile drone's or all of its devices can be activated.

[0120] Furthermore, when the distance between the flying bird and the catching drone is less than a fourth preset distance, before controlling the catching drone to stop, the method may further include:

[0121] 1) Determine the flight direction of the bird based on the captured image of the drone’s surroundings.

[0122] Specifically, at least two frames of images taken successively may be analyzed, and the positions of the flying bird in different images may be compared to determine the flying direction of the bird.

[0123] 2) If the flight direction is toward the grabbing drone, the grabbing drone is controlled to stop.

[0124] Specifically, the flight direction toward the grabbing drone can be as follows: in each image captured successively, the distance of the bird from the grabbing drone decreases, but the distance from the carrier drone increases. In this case, the bird poses a greater safety risk to the grabbing drone, and the grabbing drone must be stopped.

[0125] 3) If the flight direction is toward the carrier drone, the capture drone is controlled to remain in the started state, and the carrier drone's avoidance strategy for the bird is determined based on the distance between the bird and the carrier drone.

[0126] Specifically, the flight direction toward the carrier drone can be the following: in each of the successively captured images, the distance of the bird from the capture drone increases, while the distance from the carrier drone decreases. Based on the above analysis, it can be seen that the capture drone's obstacle avoidance criteria are more relaxed than those of the carrier drone. Therefore, even if the bird has entered the capture drone's fourth preset distance range, if it is flying toward the carrier drone, the probability of it impacting the capture drone can be considered low. Therefore, the capture drone remains activated, while the carrier drone is controlled to execute the bird avoidance strategies described in the above embodiments, such as the first avoidance strategy based on the first preset distance.

[0127] This embodiment combines the fourth preset distance and the flight direction of the bird to jointly determine whether to control the grabbing drone to stop, which can minimize the number and probability of the grabbing drone stopping, ensure that the grabbing drone can work normally, and improve the transportation efficiency of the photovoltaic cleaning robot.

[0128] In another embodiment, when the grabbing drone is activated, after acquiring an image of the environment surrounding the grabbing drone and determining the type of obstacles in the environment surrounding the grabbing drone and the distance between the obstacles and the grabbing drone based on the acquired image, if the obstacle is a floating object, the following obstacle avoidance strategy may be implemented:

[0129] 1) When the distance between the floating object and the grabbing drone is greater than the fifth preset distance: controlling the grabbing drone to continue to maintain the startup state.

[0130] The fifth preset distance can be understood as the safe distance between floating objects and the grabbing drone, which can be determined empirically or through analysis of relevant historical data. The fifth preset distance is smaller than the fourth preset distance because floating objects lack the flight autonomy of birds and typically float at a slower speed than birds. Therefore, the safe distance between floating objects and the grabbing robot can be appropriately reduced.

[0131] 2) When the distance between the floating object and the grabbing drone is less than the fifth preset distance:

[0132] Based on the current wind direction and the position of the floating object, the floating trajectory of the floating object is predicted.

[0133] If it is determined based on the floating trajectory that the floating object will interfere with the blades of the grabbing drone, the grabbing drone is controlled to stop.

[0134] If it is determined based on the floating trajectory that the floating object will not interfere with the blades of the grabbing drone, the grabbing drone is controlled to continue to remain in the started state.

[0135] When a floating object enters the fifth preset distance of the grabbing drone, the current wind direction can be obtained, and the decision to control the grabbing drone to shut down can be made based on the wind direction. The methods for predicting the floating trajectory based on wind direction and determining whether the floating trajectory will interfere with the grabbing drone's blades can be found in the description of the transport drone avoidance strategy above and will not be repeated here. Keeping the grabbing robot activated when it is determined based on the floating trajectory that the floating object will not interfere with the grabbing drone's blades can prevent the grabbing drone from frequently shutting down and affecting the deployment and recovery efficiency of the photovoltaic cleaning robot.

[0136] The following describes an obstacle avoidance strategy for grabbing a drone using a specific embodiment. Figure 5 This is a flow chart of the control strategy for grabbing drones provided by an embodiment of the present invention. Figure 5 For example, the control strategy of the grabbing drone may include:

[0137] S401: Acquire an image of the environment surrounding the drone.

[0138] S402. Determine the type of obstacle in the surrounding environment of the captured drone based on the acquired image; if the obstacle is a flying bird, execute S403; if the obstacle is a floating object, execute S410.

[0139] S403: Determine whether the distance between the flying bird and the capturing drone is greater than a fourth preset distance; if so, execute S404; if not, execute S405.

[0140] S404: Control the grabbing drone to continue to maintain the startup state.

[0141] S405: Start the bird repellent.

[0142] S406: Determine the flight direction of the bird based on the captured image of the drone's surroundings.

[0143] S407. Determine whether the flight direction is toward the carrier UAV; if so, execute S408; if not, execute S409.

[0144] S408: Control the grabbing drone to continue to be in the started state, and determine the carrier drone's avoidance strategy for the flying bird based on the distance between the flying bird and the carrier drone.

[0145] S409: Control the grabbing drone to stop.

[0146] S410: Determine whether the distance between the floating object and the grabbing drone is greater than a fifth preset distance; if so, execute S404; if not, execute S411.

[0147] S411. Obtain the current wind direction.

[0148] S412: Predict the floating trajectory of the floating object based on the current wind direction and the position of the floating object.

[0149] S413: Determine based on the floating trajectory whether the floating object will interfere with the blades of the grabbing drone; if so, execute S409; if not, execute S404.

[0150] This embodiment provides a complete obstacle avoidance control strategy for grabbing a drone based on S401-S413, which can minimize the impact on the grabbing work of the drone while ensuring the obstacle avoidance effect.

[0151] Based on the above embodiments, optionally, when executing the first avoidance strategy or the second avoidance strategy and controlling the grabbing drone to continue to remain in the started state, the method further includes:

[0152] 1) If the carrier drone is controlled to fly upward, the rope is released to a first length.

[0153] The first length is equal to the distance the carrier drone flies upward, that is, equal to the rising height of the carrier drone. In this way, the grabbing drone can be prevented from being forcibly pulled up and affecting its grabbing work during the obstacle avoidance process of the carrier drone.

[0154] 2) If the carrier drone is controlled to fly downward, the rope is retracted to the second length.

[0155] The second length is equal to the distance the carrier drone flies downward, that is, the height at which the carrier drone descends. This prevents the rope from being released too long during the carrier drone's obstacle avoidance process, causing the rope to interfere with the grabbing drone's blades or cause the grabbing drone to collide with the ground or photovoltaic panels.

[0156] Based on the above embodiments, the grabbing drone may optionally be equipped with multiple cameras, each with a horizontal field of view encompassing a 360° angle around the grabbing drone, thereby fully capturing information about the environment surrounding the grabbing drone. It is understood that the image range captured by each of the cameras covers at least a range within a fourth preset distance from the grabbing drone. Accordingly, acquiring an image of the environment surrounding the grabbing drone includes acquiring images captured by each of the cameras on the grabbing drone to obtain an image of the environment surrounding the grabbing drone.

[0157] Specifically, cameras can be installed on all four sides of the grabbing drone. The cameras originally equipped on the grabbing drone for functions such as identifying photovoltaic cleaning robots can be reused to capture images of the drone's surroundings, saving transportation system costs.

[0158] In another embodiment, optionally, see Figure 4 The photovoltaic cleaning robot 400 is provided with a rotatable camera 401. Accordingly, the method further includes:

[0159] Control the rotatable camera to rotate so that the field of view covers the carrier drone and the grabber drone.

[0160] During the hovering of the carrier drone, the rotatable camera 401 can always be controlled to rotate to the above-mentioned angle so that the rotatable camera 401 can be used to capture images of the airspace above the photovoltaic cleaning robot 400. The images captured by the rotatable camera 401 include both information about the surrounding environment of the carrier drone and information about the surrounding environment of the captured drone.

[0161] Accordingly, acquiring an image of the surrounding environment of the carrier drone may include: acquiring an image of the surrounding environment of the carrier drone from an image captured by a rotatable camera. Acquiring an image of the surrounding environment of the captured drone may include: acquiring an image of the surrounding environment of the captured drone from an image captured by a rotatable camera.

[0162] By installing a rotatable camera on the photovoltaic cleaning robot, when the carrier drone releases or retrieves the grabbing drone, the camera on the photovoltaic cleaning robot can be controlled to face the drone transport system in the air to monitor for floating objects or flying birds. Because the photovoltaic cleaning robot is located below the carrier drone and grabbing drone, the rotatable camera can simultaneously monitor the surrounding environment of the grabbing drone and the carrier drone, reducing the number of cameras required to implement this obstacle avoidance control method.

[0163] It is understandable that the rotatable camera can be reused by the camera originally equipped on the photovoltaic cleaning robot for performing functions such as identifying paths or panel dirt, thereby saving costs. It should also be noted that in actual applications, the cameras mentioned in the above embodiments can be configured according to needs, and the specific location and number of the cameras are not limited here.

[0164] The above embodiments illustrate the use of cameras to capture images, but this is not intended to limit the present invention. In other embodiments, radar may be used to capture images, such as a perception laser radar or millimeter-wave radar, which can obtain more reliable images than cameras.

[0165] An embodiment of the present invention also provides a photovoltaic cleaning system, including a drone transport system and a photovoltaic cleaning robot. The drone transport system can adopt the drone transport system obstacle avoidance control method provided in any embodiment of the present invention to avoid obstacles, which has corresponding beneficial effects. Specifically, the drone transport system is used to place the photovoltaic cleaning robot onto the photovoltaic panel and to recover the photovoltaic cleaning robot from the photovoltaic panel. Among them, the drone transport system adopts the drone transport system obstacle avoidance control method provided in any embodiment of the present invention to avoid obstacles, mainly in the hovering stage of the process of placing the photovoltaic cleaning robot onto the photovoltaic panel and recovering the photovoltaic cleaning robot from the photovoltaic panel, the above-mentioned drone transport system obstacle avoidance control method is adopted to avoid obstacles, so as to improve the hovering safety. This method can be executed, for example, by a controller equipped in the drone transport system.

[0166] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0167] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. An obstacle avoidance control method for a UAV transport system, characterized in that: The UAV transport system includes a carrier UAV; the obstacle avoidance control method of the UAV transport system includes: Acquiring an image of the surrounding environment of the carrier drone during the hovering of the carrier drone; Determining the type of obstacles in the surrounding environment of the carrier drone and the distance between the obstacles and the carrier drone based on the acquired images; If the obstacle is a flying bird and the distance between the obstacle and the carrier drone is less than a first preset distance, executing a first avoidance strategy; If the obstacle is a floating object and the distance between the obstacle and the carrier UAV is less than a second preset distance, executing a second avoidance strategy; The second preset distance is smaller than the first preset distance.

2. The obstacle avoidance control method for a UAV transport system according to claim 1, characterized in that: The first avoidance strategy includes: When the distance between the obstacle and the carrier drone is between the first preset distance and a third preset distance, activating the bird repellent; wherein the third preset distance is smaller than the first preset distance; When the distance between the obstacle and the carrier drone is less than the third preset distance, controlling the carrier drone to avoid the obstacle; The second avoidance strategy includes: Get the current wind direction; predicting a floating trajectory of the obstacle based on the current wind direction and the position of the obstacle; If it is determined based on the floating trajectory that the obstacle will interfere with the blades of the carrier drone, the carrier drone is controlled to avoid the obstacle.

3. The obstacle avoidance control method for a UAV transport system according to claim 2, characterized in that: The controlling the carrier drone to avoid the obstacle includes: If the obstacle is located below the carrier drone, controlling the carrier drone to fly upward; If the obstacle is above the carrier drone, controlling the carrier drone to fly downward; If the obstacle and the carrier drone are located on the same horizontal plane, the carrier drone is controlled to fly upward or downward.

4. The obstacle avoidance control method for a UAV transport system according to claim 2, characterized in that: The controlling the carrier drone to avoid the obstacle includes: When there is only one obstacle, controlling the carrier drone to fly in a direction away from the obstacle; When there are multiple obstacles, calculating the obstacle avoidance direction of the carrier drone away from each obstacle; The carrier UAV is controlled to fly along the obstacle avoidance direction.

5. The obstacle avoidance control method for a UAV transportation system according to any one of claims 1 to 4, characterized in that: The carrier drone is provided with a plurality of cameras, and the horizontal field of view of the plurality of cameras covers a 360° range around the fuselage of the carrier drone; The acquiring of the image of the surrounding environment of the carrier drone includes: acquiring images captured by each camera on the carrier drone to obtain the image of the surrounding environment of the carrier drone.

6. The obstacle avoidance control method for a UAV transportation system according to any one of claims 1 to 4, characterized in that: The UAV transport system further includes: a hoist and a grabbing UAV; the hoist is fixedly mounted on the carrier UAV, and the hoist suspends the grabbing UAV via a rope, and the grabbing UAV is used to grab the photovoltaic cleaning robot; the method further includes: With the grab drone already activated: Acquire an image of the environment surrounding the grasping drone, and determine the type of obstacles in the environment surrounding the grasping drone and the distance between the obstacles and the grasping drone based on the acquired image; If the obstacle is a flying bird, and the distance between the flying bird and the grabbing drone is greater than a fourth preset distance, controlling the grabbing drone to continue to remain in the started state; If the obstacle is a flying bird, and the distance between the flying bird and the grabbing drone is less than the fourth preset distance, the bird repeller is activated and the grabbing drone is controlled to stop.

7. The obstacle avoidance control method for a UAV transport system according to claim 6, characterized in that: When the distance between the flying bird and the grabbing drone is less than the fourth preset distance, before controlling the grabbing drone to stop, the method further includes: Determining the flight direction of the bird based on the captured image of the drone's surroundings; If the flight direction is toward the grabbing drone, controlling the grabbing drone to stop; If the flight direction is toward the carrier drone, the grabbing drone is controlled to remain in the started state, and the carrier drone's avoidance strategy for the flying bird is determined according to the distance between the flying bird and the carrier drone.

8. The obstacle avoidance control method for a UAV transport system according to claim 6, characterized in that: The method further comprises: If the obstacle is a floating object, and the distance between the floating object and the grabbing drone is greater than a fifth preset distance: controlling the grabbing drone to continue to be in the started state; wherein the fifth preset distance is less than the fourth preset distance; If the obstacle is a floating object, and the distance between the floating object and the grabbing drone is less than the fifth preset distance: predicting a floating trajectory of the floating object based on the current wind direction and the position of the floating object; If it is determined based on the floating trajectory that the floating object will interfere with the blades of the grabbing drone, controlling the grabbing drone to stop; If it is determined based on the floating trajectory that the floating object will not interfere with the blades of the grabbing drone, the grabbing drone is controlled to continue to remain in the started state.

9. The obstacle avoidance control method for a UAV transport system according to claim 6, characterized in that: When executing the first avoidance strategy or executing the second avoidance strategy and controlling the grabbing drone to continue to remain in the started state, the method further includes: If the carrier drone is controlled to fly upward, the rope is released to a first length; wherein the first length is equal to the distance the carrier drone flies upward; If the carrier drone is controlled to fly downward, the rope is retracted to a second length; wherein the second length is equal to the distance the carrier drone flies downward.

10. The obstacle avoidance control method for a UAV transportation system according to claim 6, characterized in that: The grabbing drone is provided with a plurality of cameras, and the horizontal field of view of the plurality of cameras covers a 360° range around the fuselage of the grabbing drone; The acquiring of the image of the surrounding environment of the grasping drone includes: acquiring images captured by each camera on the grasping drone to obtain the image of the surrounding environment of the grasping drone.

11. The obstacle avoidance control method for a UAV transportation system according to claim 6, characterized in that: The photovoltaic cleaning robot is provided with a rotatable camera; the method further comprises: Controlling the rotatable camera to rotate so that the field of view covers the carrying drone and the grabbing drone; The acquiring of the image of the surrounding environment of the carrier drone comprises: acquiring the image of the surrounding environment of the carrier drone from the image captured by the rotatable camera; The acquiring of the image of the surrounding environment of the captured drone includes: acquiring the image of the surrounding environment of the captured drone from the image captured by the rotatable camera.

12. A photovoltaic cleaning system, characterized in that: include: A drone transport system and a photovoltaic cleaning robot; the drone transport system is used to place the photovoltaic cleaning robot onto a photovoltaic panel and to recover the photovoltaic cleaning robot from the photovoltaic panel; wherein the drone transport system adopts the drone transport system obstacle avoidance control method described in any one of claims 1-11 to avoid obstacles.

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