Unmanned aerial vehicle hoisting flight method, device, equipment and storage medium

Abstract

The application discloses a kind of unmanned aerial vehicle's hoisting flight method, device, equipment and storage medium, it is related to unmanned aerial vehicle technical field.Unmanned aerial vehicle is equipped with ground sensor and hoisting system, hoisting system includes sling and the goods hoisted on sling, the method includes: obtaining the original route of goods;Ground sensor is collected and ground sensing information is obtained;According to ground sensing information, establish environment topographic map;According to environment topographic map and original route, the expected running track of goods is planned;According to expected running track, control unmanned aerial vehicle flight.Through the above technical means, the goods is always kept safe distance with ground when unmanned aerial vehicle hoisting flight, unmanned aerial vehicle needs not to keep target flight height and continuously fly, solve the problem that unmanned aerial vehicle cannot normally execute hoisting task in prior art due to high-altitude control or other reasons, guarantee the execution efficiency of hoisting task.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) technology, and in particular to a method, apparatus, equipment, and storage medium for lifting and flying UAVs. Background Technology

[0002] With the rapid development of drones, their applications in industry, logistics, and agriculture are becoming increasingly widespread. Especially in lifting operations, drones, with their high efficiency and flexibility, have become an important supplement to traditional transportation methods. However, when drones perform lifting tasks, there is a risk of the cargo hitting the ground. To avoid this, the drone's flight altitude is crucial.

[0003] In existing technologies, the target flight altitude of the drone can be preset, and after takeoff, the drone can first ascend vertically to the target flight altitude, then fly horizontally to the unloading point of the goods, and finally land vertically at the unloading point. However, in some areas, the drone may be unable to climb to the target flight altitude due to air traffic control or other reasons, which would prevent the drone from performing the lifting task and affect the efficiency of the lifting task. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for unmanned aerial vehicle (UAV) hoisting flight. It plans a desired flight trajectory that mimics the terrain and maintains a safe distance from the ground using an environmental topographic map. The UAV is controlled to fly according to the desired flight trajectory, ensuring that the cargo is always kept at a safe distance from the ground during UAV hoisting flight. This eliminates the need for the UAV to maintain a target flight altitude for continuous flight, solving the problem in the prior art where UAVs cannot perform hoisting tasks normally due to air traffic control or other reasons, and ensuring the efficiency of hoisting task execution.

[0005] In a first aspect, this application provides a method for hoisting a drone, the drone being equipped with a ground sensor and a hoisting system, the hoisting system including a hoisting rope and cargo hoisted on the hoisting rope, the method comprising:

[0006] Obtain the original route taken by the goods;

[0007] Acquire ground sensing information collected by ground sensors;

[0008] An environmental topographic map is created based on the aforementioned ground sensing information;

[0009] The desired trajectory of the cargo is planned based on the environmental topographic map and the original route.

[0010] The drone is controlled to fly according to the desired flight trajectory.

[0011] Secondly, this application provides a hoisting flight device for a drone, the drone being equipped with a ground sensor and a hoisting system, the hoisting system including a hoisting rope and cargo hoisted on the hoisting rope, the device comprising:

[0012] The original path acquisition module is configured to acquire the original route taken by the goods;

[0013] The sensor information acquisition module is configured to acquire ground sensing information collected by the ground sensor;

[0014] The topographic map creation module is configured to create an environmental topographic map based on the ground sensing information;

[0015] The cargo trajectory planning module is configured to plan the desired trajectory of the cargo based on the environmental topographic map and the original route.

[0016] The flight control module is configured to control the flight of the UAV according to the desired flight trajectory.

[0017] Thirdly, this application provides a hoisting flight device for unmanned aerial vehicles, comprising:

[0018] One or more processors; a memory storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the sling-flying method as described in the first aspect.

[0019] Fourthly, this application provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the hoisting flight method as described in the first aspect.

[0020] In this application, the original route of the cargo is obtained, and real-time ground sensing information is acquired from ground sensors. A high-precision environmental topographic map is constructed based on the ground sensing information. The altitude of the original route is adjusted using the environmental topographic map, and a desired flight trajectory that mimics the terrain and maintains a safe altitude from the ground is planned based on the adjusted original route. The UAV is controlled by the desired flight trajectory to ensure that the cargo maintains a safe distance from the ground during the lifting process, thereby improving the safety of both the cargo and the UAV. The UAV does not need to maintain a target flight altitude continuously during lifting flight, solving the problem in existing technologies where UAVs cannot perform lifting tasks normally due to air traffic control or other reasons, thus ensuring the efficiency of lifting task execution. Attached Figure Description

[0021] Figure 1 This is a flowchart of a hoisting flight method for an unmanned aerial vehicle (UAV) provided in an embodiment of this application;

[0022] Figure 2 This is a flowchart of determining the original path provided in the embodiments of this application;

[0023] Figure 3 This is a schematic diagram of a drone lifting flight provided in an embodiment of this application;

[0024] Figure 4 This is a flowchart illustrating the construction of an environmental topographic map provided in an embodiment of this application;

[0025] Figure 5 This is a schematic diagram of the moment when the drone lifts up the cargo, as provided in an embodiment of this application;

[0026] Figure 6 This is a schematic diagram of the cargo area, the sling area, and the corresponding adjacent areas provided in the embodiments of this application;

[0027] Figure 7 This is a schematic diagram of the drone and the ground provided in an embodiment of this application;

[0028] Figure 8 This is a flowchart illustrating the planned expected running trajectory provided in an embodiment of this application;

[0029] Figure 9 This is a schematic diagram of the original waypoints provided in the embodiments of this application;

[0030] Figure 10 This is a schematic diagram of the original waypoints and the desired waypoints provided in the embodiments of this application;

[0031] Figure 11 This is a schematic diagram of the distance sampling points provided in the embodiments of this application;

[0032] Figure 12 This is a flowchart of controlling the flight of a drone provided in an embodiment of this application;

[0033] Figure 13 This is a schematic diagram of the structure of a hoisting flight device for a drone provided in an embodiment of this application;

[0034] Figure 14 This is a schematic diagram of the structure of a drone hoisting flight device provided in an embodiment of this application. Detailed Implementation

[0035] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. A process can be terminated when its operation is completed, but it may also have additional steps not included in the drawings. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0036] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0037] In most implementations, drones performing lifting missions employ a fixed-altitude flight method. This involves the drone taking off, ascending vertically to the target altitude set for the mission, then flying horizontally above the unloading point, and finally landing vertically. However, in areas with significant altitude variations, such as mountains and valleys, drones may be unable to climb to the target altitude due to air traffic control or other reasons. This prevents the drone from using the fixed-altitude flight method, impacting the efficiency of the lifting mission. Alternatively, drones can use a ground-following flight method, controlling the drone to maintain a safe distance from the ground based on altitude data collected by ground sensors. However, the data collected by ground sensors includes information about the lifting rope and cargo, leading to inaccurate altitude measurements. This can cause the drone to lose a safe distance from the ground during lifting operations, increasing the risk of cargo impact and compromising the safety of both the cargo and the drone.

[0038] To address the problems of the aforementioned implementation methods, this embodiment provides a hoisting flight method. This method constructs a high-precision environmental topographic map using real-time ground sensing information collected by ground sensors. The desired flight trajectory, mimicking the terrain while maintaining a safe distance from the ground, is planned based on this map. The drone is then controlled to fly according to this desired trajectory, ensuring that the cargo remains at a safe distance from the ground during hoisting operations. This reduces the risk of cargo contact with the ground and improves the safety of both the drone and the cargo. Furthermore, the drone does not need to maintain a target flight altitude continuously, ensuring the efficiency of the hoisting mission.

[0039] The hoisting flight method provided in this embodiment can be executed by hoisting flight equipment, which can be implemented through software and / or hardware. This equipment can consist of two or more physical entities, or it can be a single physical entity. For example, the hoisting flight equipment can be a drone, or it can be the drone's processor. In this embodiment, the drone is equipped with a ground sensor and a hoisting system, which includes a hoisting rope and the cargo hoisted on the rope. When performing a hoisting task, the drone can collect real-time ground sensing information through the ground sensor, and then adjust its altitude according to the ground sensing information to ensure that the cargo hoisted by the rope always maintains a safe distance from the ground during hoisting flight. After the drone reaches the unloading point and unloads the cargo, the hoisting task is completed.

[0040] The hoisting flight equipment is equipped with at least one type of operating system. Based on this operating system, the hoisting flight equipment can install at least one application. This application can be a built-in application of the operating system or an application downloaded from a third-party device or server. In this embodiment, the hoisting flight equipment has at least one application capable of executing the hoisting flight method.

[0041] For ease of understanding, this embodiment uses a drone as the main entity for performing the hoisting flight method.

[0042] Figure 1 A flowchart of a hoisting flight method for a drone according to an embodiment of this application is provided. (Reference) Figure 1 The specific methods for lifting and flying include:

[0043] S110. Obtain the original route taken by the goods.

[0044] The original path is the route the cargo takes when the drone maintains a safe distance from the horizontal plane where it takes off to perform the hoisting task. For example, the user can configure the task information for the hoisting task through the remote control device, adding information such as the cargo start point, cargo destination, transport area, original path of the cargo, hoisting rope length, maximum flight speed, maximum flight acceleration, unloading point, maximum hoisting rope swing angle, and cargo shape. The remote control device uploads the task information to the drone, which then performs the corresponding hoisting task based on the task information. The drone can obtain the original path set in the hoisting task, that is, it can obtain the pre-configured original path from the task information of the hoisting task. In addition, the original path can consist of multiple waypoints. The user adds multiple waypoints to form the original path in the task information, and after the drone receives the task information uploaded by the remote control device, it obtains these multiple waypoints from the task information.

[0045] The remote control device can be a remote controller that works with the drone, or it can be a user terminal, such as a user's mobile phone or tablet.

[0046] Optionally, the drone can receive the original route sent by the remote control device. The remote control device can determine the starting point and ending point of the cargo transportation based on the task information set by the user, or determine the lifting area information through which the drone completes the lifting task. Then, based on the starting point and ending point of the cargo transportation, or based on the lifting area information, the drone can perform path planning to generate the initial flight path of the drone and the original route of the cargo. The original route of the cargo can then be sent to the drone.

[0047] Optionally, the original path can also be derived from the drone's initial flight path. The initial flight path is the projection of the path traversed by the drone during the hoisting task onto the horizontal plane; that is, the initial flight path includes the horizontal positions of the waypoints passed by the drone but excludes altitude information. For example, Figure 2 This is a flowchart illustrating the determination of the original path provided in an embodiment of this application. For example... Figure 2 As shown, the steps for determining the original route include S1101-S1103:

[0048] S1101. Determine the horizontal position of the initial flight path of the UAV as the horizontal position of the original route of the cargo.

[0049] For example, a user can add the initial flight path of the drone to the mission information of a hoisting task via a remote control device, or add a takeoff point and a unloading point to the mission information. The remote control device automatically plans an initial flight path with the takeoff point as the starting point and the unloading point as the ending point based on the takeoff point and the unloading point. After receiving the mission information sent by the remote control device, the drone can obtain the initial flight path from the mission information. Then, the horizontal position of each waypoint on the initial flight path is determined as the horizontal position of the corresponding waypoint on the original path.

[0050] S1102. The preset safety distance is determined as the altitude of each waypoint in the original route of the cargo relative to the takeoff point; wherein, the preset safety distance is the safety distance maintained between the cargo and the ground.

[0051] For example, the preset safety distance is determined as the altitude position of each waypoint in the original route so that each waypoint in the original route maintains a safe distance from the horizontal plane where the takeoff point is located.

[0052] S1103. Generate the original route of the cargo based on the horizontal position of the original route and the altitude of each waypoint relative to the takeoff point.

[0053] For example, the horizontal and vertical positions of waypoints on the original route are combined to obtain the three-dimensional position of the waypoint in space, and the three-dimensional positions of each waypoint are summarized to obtain the original route.

[0054] This embodiment uses the initial flight path of the drone to deduce the original route of the cargo, so that the cargo can move along the initial flight path during the hoisting process, avoiding collisions with surrounding obstacles and improving the safety of cargo hoisting.

[0055] S120. Acquire ground sensing information collected by the ground sensor.

[0056] Among them, the ground sensor is a sensor installed on the UAV to collect the UAV's altitude above the ground. Ground sensors include, but are not limited to, LiDAR, depth cameras, and millimeter-wave radar. The ground sensing information is the collected altitude information of the UAV relative to the area below. When performing a hoisting mission, the UAV can activate the ground sensor to obtain real-time ground sensing information.

[0057] S130. Establish an environmental topographic map based on ground sensing information.

[0058] For example, after acquiring ground sensing information, the UAV can build an environmental topographic map based on the height information of each location point contained in the ground sensing information. The environmental topographic map includes the height information of each location point relative to the horizontal plane where the takeoff point is located.

[0059] It needs to be explained that, Figure 3 This is a schematic diagram of a drone lifting flight provided in an embodiment of this application. Figure 3 As shown, when the UAV 10 is in flight carrying cargo, the area below the UAV 10 includes the hoisting rope 11, the cargo 12, and the ground 13. That is, the ground sensing information includes the altitude information of the UAV 10 relative to the hoisting rope 11, the cargo 12, and the ground 13. To obtain accurate altitude information of the ground 13, the hoisting rope data and cargo data in the ground sensing information can be filtered out to obtain terrain data representing the altitude information of the ground 13. Specifically, the hoisting rope data is the altitude information of the UAV relative to the hoisting rope collected by the ground sensor, and the cargo data is the altitude information of the UAV relative to the cargo.

[0060] To construct high-precision environmental topographic maps, interference data in the ground sensing information can be filtered out first, and then the environmental topographic map can be constructed based on the filtered ground sensing information. For example, Figure 4 This is a flowchart illustrating the construction of an environmental topographic map provided in an embodiment of this application. For example... Figure 4 As shown, the steps for constructing the environmental topographic map specifically include S1301-S1302:

[0061] S1301. Filter the rope data and cargo data in the ground sensing information to obtain the remaining ground sensing information.

[0062] For example, when the ground sensor is a depth camera, the sling and cargo pixels can be identified from the images captured by the depth camera. Based on the identified sling and cargo pixels, the sling and cargo data in the ground sensing information are determined. This determined sling and cargo data is then removed from the ground sensing information, leaving the remaining ground sensing information which can be used as terrain data. When the ground sensor is a lidar or millimeter-wave radar, a 3D model can be created from the 3D point cloud data obtained by the lidar or millimeter-wave radar scan, resulting in a 3D model of the area below the UAV. Based on the shape of the sling and cargo, the sling and cargo models are identified in the 3D model. Based on the identified sling and cargo models, the sling and cargo data in the ground sensing information are determined. This determined sling and cargo data is then removed from the ground sensing information, leaving the remaining ground sensing information which can be used as terrain data.

[0063] The system can filter the sling data and cargo data in the ground sensing information, and also determine the sling length and direction. The cargo is at the end of the sling. Therefore, the system can filter the sling and the ground sensing information within a certain range around it based on the sling length and direction. In other words, the ground sensing information within a specified range around the sling and cargo is used as sling data and cargo data for filtering.

[0064] In addition, the sling pose and cargo position can be inferred from the UAV's position, sling length, and sling direction. Based on the sling pose and cargo position, the sling data and cargo data in the ground sensing information can be determined, and then the sling data and cargo data can be removed from the ground sensing information to obtain terrain data. For example, the steps of filtering sling data and cargo data from the ground sensing information specifically include S13011-S13013:

[0065] S13011, Obtain the length and direction of the suspension rope.

[0066] For example, the drone can obtain the length of the hoisting rope set in the hoisting task, that is, obtain the pre-configured hoisting rope length in the task information of the hoisting task.

[0067] Alternatively, the drone's flight power can be monitored in real time after startup. When the change in flight power when the drone lifts the cargo exceeds a preset threshold, the sling length is determined based on the sling angle and the drone's position. For example, when the drone leaves the ground, the cargo is still on the ground, and the drone's flight power is relatively low. When the drone lifts the cargo off the ground, the drone's flight power suddenly increases due to the sudden increase in load. The preset threshold can be considered the minimum change in flight power before and after the drone lifts the cargo off the ground. That is, when the change in flight power exceeds the preset threshold, it can be determined that the drone has just lifted the cargo off the ground. When the drone lifts the cargo off the ground, the cargo is approximately on the ground, and the sling used to connect the cargo is taut. The Euclidean distance between the drone and the cargo is approximately the length of the sling. Figure 5 This is a schematic diagram illustrating the moment a drone lifts cargo, as provided in an embodiment of this application. Figure 5As shown, at the instant the drone 10 lifts the cargo 12, the cargo 12 is still on the ground, and the sling 11 between the drone 10 and the cargo 12 is taut. The Euclidean distance between the drone 10 and the cargo 12 is equal to the length of the sling 11. The drone 10, the cargo 12, and the projection point of the drone 10 on the ground form a right triangle. The swing angle θ of the sling 11 is the angle between the line segment between the drone 10 and the cargo 12 and the line segment between the drone 10 and the projection point. The length of the line segment between the drone 10 and the projection point is equal to the height of the drone 10. According to the cosine theorem of a triangle, the ratio of the height of the drone 10 to the length L of the sling 11 is equal to cos θ. The height of the drone 10 can be determined based on its position, and cos θ can be determined based on the swing angle θ of the sling 11. The ratio of the height of the drone 10 to cos θ is then defined as the length L of the sling 11. It is understandable that if the volume of cargo 12 is ignored, the ratio of the height of drone 10 to cosθ is determined as the length L of sling 11. If the volume of cargo 12 is not ignored, the distance between drone 10 and cargo 12 can be determined based on the shape of cargo 12, the height of drone 10 and cosθ, and thus the length L of sling 11 can be determined.

[0068] It should be noted that the sling angle and sling direction can be considered the same parameter, except that the sling angle is a scalar and the sling direction is a vector. The sling angle can be determined based on the sling direction, or using the same method as determining the sling direction. For example, the sling angle can be detected by a motion sensor mounted on the sling hook or a force sensor mounted at the connection between the sling and the drone. Alternatively, the sling angle can be determined by the drone's acceleration. The motion sensor can be a gyroscope or an IMU (Inertial Measurement Unit). (Reference) Figure 5 Assume the acceleration of the drone is (a x a y a z If the acceleration of cargo 12 is (a), then the acceleration of cargo 12 is (a). x a y a z +g), a x a y a z Let X, Y, and Z be the acceleration components in the X, Y, and Z directions, respectively, and g be the acceleration due to gravity. Through force analysis, the swing angle of the suspension rope 11 and the acceleration satisfy the following relationship:

[0069]

[0070] When the change in the drone's flight power is detected to be greater than a preset change threshold, the current acceleration of the drone is obtained, the current sling swing angle is determined based on the drone's acceleration and gravitational acceleration, and the sling length is determined based on the sling swing angle.

[0071] The sling direction refers to the sling's orientation in world coordinates, which can be represented using a three-dimensional vector. In this embodiment, the sling direction can be detected by a motion sensor mounted on the sling hook or by a force sensor mounted at the connection point between the sling and the drone. Alternatively, the cargo acceleration can be determined using the drone's acceleration, and the sling direction can be determined based on this cargo acceleration. (Reference) Figure 5 The drone will accelerate by 10 (a x a y a z The acceleration component a in the Z direction of ) z Adding the gravitational acceleration g, we can obtain the cargo's acceleration (a). x a y a z +g), while the cargo 12 acceleration (a x a y a z The unit direction of +g) is the direction of the lifting rope 11. Therefore, normalizing the acceleration of the cargo 12 is equivalent to dividing the acceleration of the cargo 12 by the corresponding modulus to obtain the direction of the lifting rope 11, which is a. L / ||a L ||,a L =(a x a y a z +g).

[0072] S13012. Determine the cargo location and sling location based on the sling direction, sling length, and UAV location.

[0073] refer to Figure 5 The position of cargo 12 can be considered as a translation of the position of drone 10 along sling 11. That is, the product of the direction and length of sling 11 is the translation vector from the position of drone 10 to the position of cargo 12. Therefore, the translation vector between drone 10 and cargo 12 is determined based on the length and direction of the sling; the sum of this translation vector and the position of drone 10 is used to determine the position of cargo 12. For example, assuming the position of cargo 12 is (x, y, z), then the position of drone 10 is (x, y, z) + L*a. L / ||A L The translation vector is obtained by multiplying the length of the sling 11 by the direction of the sling 11, and the position of the cargo 12 is obtained by subtracting the offset vector from the position of the drone 10.

[0074] refer to Figure 5The sling 11 can be considered as a straight line segment between the cargo 12 and the drone 10. After determining the position of the cargo 12, the position of the line connecting the positions of the cargo 12 and the drone 10 can be determined as the position of the sling 11. Alternatively, the position of the drone 10 can be determined as the end point of the sling 11. The position of the sling 11 can be determined based on the end point of the sling 11, the direction of the sling 11, and the length of the sling 11.

[0075] S13013. Determine the sling data and cargo data in the ground sensing information based on the sling position and cargo position, and filter the sling data and cargo data in the ground sensing information to obtain the remaining ground sensing information.

[0076] For example, the hoisting rope area is determined based on the hoisting rope's position and cross-sectional area, and the data from the ground sensing information that falls into the hoisting rope area is identified as hoisting rope data. Similarly, the cargo area is determined based on the cargo's position and shape, and the data from the ground sensing information that falls into the cargo area is identified as cargo data.

[0077] It should be noted that when the ground sensor scans the sling and cargo, it will collect some noise data around them due to the influence of the sling and cargo. In order to ensure the accuracy of the terrain data acquired later, the noise data around the sling and cargo can be filtered out when filtering the sling and cargo data.

[0078] For example, a lifting rope area can be determined based on the lifting rope's location, and a lifting rope neighborhood within a preset distance range centered on the lifting rope area can be defined. The ground sensing information within the lifting rope area and its neighborhood is then used as lifting rope data. Similarly, a cargo area can be determined based on the cargo's location, and a cargo neighborhood within a preset distance range centered on the cargo area can be defined. The ground sensing information within the cargo area and its neighborhood is then used as cargo data. For example, Figure 6 This is a schematic diagram of the cargo area, the sling area, and the corresponding adjacent areas provided in an embodiment of this application. For example... Figure 6As shown, the hoisting rope region 14 is determined based on the hoisting rope's position and cross-sectional area, and the area surrounding the hoisting rope region 14 within a preset distance range is defined as the hoisting rope neighborhood 16. The cargo region 15 is determined based on the cargo's position and shape, and the area surrounding the cargo region 15 within a preset distance range is defined as the cargo neighborhood 17. Data from the ground sensing information located within the hoisting rope region 14 and the hoisting rope neighborhood 16 are defined as hoisting rope data, and data from the ground sensing information located within the cargo region 15 and the cargo neighborhood 17 are defined as cargo data. This allows for the subsequent removal of the hoisting rope and cargo height data, along with the corresponding noise data, from the ground sensing information, preserving accurate terrain data. The preset distance range can be set according to actual needs, but regardless of how the preset distance range is determined, it will not include the terrain data below within the cargo or hoisting rope neighborhood. That is, when filtering hoisting rope and cargo data, terrain data will not be filtered out, further improving the accuracy of the terrain data. This embodiment improves the accuracy of terrain data acquisition by removing data related to the sling, cargo, and surrounding noise from the ground sensing information, thus preserving the terrain data belonging to the ground and ensuring the accuracy of the subsequent planned operating trajectory and UAV flight trajectory.

[0079] This embodiment calculates the cargo and sling positions based on the positional relationship between the drone, the sling, and the cargo. It then filters cargo and sling data from ground sensing information based on these positions, eliminating the need for complex recognition algorithms to detect them. This improves the efficiency of terrain data acquisition, reduces the computational load on the drone, and enhances the drone's control stability.

[0080] S1302. Create an environmental topographic map based on the remaining ground sensing information.

[0081] For example, Figure 7 This is a schematic diagram of the drone and the ground provided in an embodiment of this application. For example... Figure 7 As shown, the altitude H1 of the UAV 10 relative to each location point on the ground 13 in the terrain data represents the vertical distance between the UAV 10 and the corresponding topographic envelope vertex. The UAV 10 takes off from the ground plane 18, with the takeoff point altitude being the altitude of the ground plane 18. The altitude H2 of the UAV 10 represents the vertical distance between the UAV 10 and the takeoff point. When using the filtered remaining ground sensing information as terrain data to build an environmental terrain map, the altitude H2 of the UAV 10 can be subtracted from the altitude H1 corresponding to each location point in the terrain data to obtain the terrain altitude H3 for the corresponding location point. This terrain altitude represents the vertical distance between the topographic envelope vertex at the corresponding location point and the takeoff point. Then, an environmental terrain map can be constructed based on the terrain altitude of each location point.

[0082] In this embodiment, when the original route or initial flight path of the hoisting task is being executed for the first time, the terrain height of the corresponding points in the initial environmental terrain map is updated based on the height of each location point in the terrain data; wherein, the terrain height of each location point in the initial environmental terrain map is zero. The initial environmental terrain map is an environmental terrain map established by the UAV relative to the takeoff point height before takeoff, and the terrain height corresponding to any location point in the initial environmental terrain map is zero. Of course, before establishing the initial environmental terrain map, it is determined whether the original route or initial flight path is being executed for the first time; if so, the initial environmental terrain map is established; otherwise, it is not established. The height of each location point in the terrain data is the vertical distance between the UAV and the corresponding terrain envelope vertex at that location point; the difference between the height of the UAV and the height of each location point is determined as the terrain height of the corresponding location point in the initial environmental terrain map. (Reference) Figure 7 Subtract the height H1 of location point A from the height H2 of UAV 10 to obtain height H3, and use height H3 as the terrain height of location point A in the initial environmental terrain map.

[0083] Furthermore, if the original route or initial flight path of the hoisting mission is not the first execution, the historical environmental terrain map corresponding to the original route or initial flight path is obtained. The terrain height of the corresponding points in the historical environmental terrain map is updated based on the height of each location point in the terrain data. The historical environmental terrain map is the environmental terrain map generated during the previous execution of the original route or initial flight path, recording the terrain height of each location point determined by the UAV during the previous execution. The difference between the UAV's altitude and the altitude of each location point can be determined as the real-time terrain height of the corresponding location point. The terrain height of the corresponding location point in the historical environmental terrain map is updated based on the real-time terrain height of the location point, and the updated historical environmental terrain map is used as the current environmental terrain map. Specifically, the average of the real-time terrain height and the terrain height in the historical environmental terrain map can replace the terrain height of the corresponding location point in the historical environmental terrain map. Alternatively, if the difference between the real-time terrain height and the terrain height in the historical environmental terrain map is large, the real-time terrain height replaces the terrain height in the historical environmental terrain map; otherwise, the terrain height in the historical environmental terrain map is retained. This embodiment improves the efficiency and accuracy of environmental topographic map construction by building a real-time environmental topographic map based on real-time acquired topographic data on the basis of historical environmental topographic maps.

[0084] S140. Plan the desired trajectory of the goods based on the environmental topographic map and the original route.

[0085] For example, after constructing the environmental topographic map, a desired flight trajectory that mimics the terrain and maintains a safe distance from the topographic envelope vertices at each location point can be planned based on the terrain elevation of each location point in the environmental topographic map. The flight trajectory of the UAV can then be inferred from the desired flight trajectory, so that when the UAV flies based on the flight trajectory, the cargo being transported moves along the desired flight trajectory, mimicking the terrain, and the cargo always maintains a safe distance from the ground, ensuring the safety of both the cargo and the UAV.

[0086] In this embodiment, Figure 8 This is a flowchart of the planned expected running trajectory provided in the embodiments of this application.

[0087] like Figure 8 As shown, the steps of the planned trajectory specifically include S1401-S1403:

[0088] S1401. Obtain multiple original waypoints along the original route.

[0089] For example, if the original path in the mission information consists of multiple original waypoints, then the multiple original waypoints in the mission information are directly obtained. If the original path is a path segment set by the user or planned from the initial flight path, then multiple original waypoints are sampled on the original path. Here, an original waypoint can be understood as a spatial point through which the cargo passes when the UAV is hoisting cargo in the ground plane scene corresponding to the takeoff point. The original waypoint includes both horizontal position and altitude. The altitude of each original waypoint is its vertical height relative to the takeoff point, and the altitude of each original waypoint is equal and equal to the safe distance maintained between the cargo and the ground during cargo hoisting. Figure 9 This is a schematic diagram of the original waypoints provided in the embodiments of this application. For example... Figure 9 As shown, the altitude H4 of the original waypoint 19 is the vertical height of the original waypoint relative to the ground plane 18 of the takeoff point. It can be understood that if the drone is carrying cargo in a scenario on ground plane 18, the cargo will pass through each original waypoint 19, meaning the cargo always maintains a safe distance from ground plane 18. Since various terrains exist on ground plane 18, if the drone carries cargo based on the original waypoint 19, the cargo will collide with the actual ground 13. Therefore, after obtaining the original waypoints, the altitude of the original waypoints can be adjusted based on the terrain height of each location on the environmental terrain map to avoid collisions between the cargo and the actual ground when the drone is carrying cargo.

[0090] S1402. Based on the environmental topographic map, perform terrain-following elevation adjustment on multiple original waypoints to obtain multiple desired waypoints for the cargo. The elevation of the desired waypoint is equal to the sum of the elevation of the original waypoint at the same horizontal position and the elevation of the corresponding position on the environmental topographic map.

[0091] Here, the expected waypoints are the waypoints that the cargo is expected to pass through when the UAV performs a lifting mission. For example, the corresponding position point on the environmental terrain map is determined based on the horizontal position of the original waypoint. The sum of the terrain height of this position point and the height of the original waypoint is determined as the height of the expected waypoint at the same horizontal position, so that the cargo maintains a safe distance from the top of the terrain envelope at the corresponding position when it arrives at the expected waypoint. Figure 10 This is a schematic diagram of the original waypoints and desired waypoints provided in the embodiments of this application. For example... Figure 10 As shown, the original waypoint 19 is adjusted to the desired waypoint 21 after terrain simulation. The line connecting multiple desired waypoints 21 approximates the actual terrain of the ground 13. Point B is the desired waypoint 21, and point C is the top of the terrain envelope at the location corresponding to point B. The vertical height of point B relative to point C is equal to the height H4 of the original waypoint before adjustment at the same horizontal position, which is also the safe distance between the cargo and the ground. The height of point B is equal to height H4 plus the terrain height H3 of point C.

[0092] S1403. Plan the desired trajectory of cargo based on multiple desired waypoints.

[0093] For example, after adjusting the altitude of each original waypoint, the desired flight path over a future period can be planned using constraint information such as dynamics, kinematics, and maximum rigging angle. The length of the desired flight path can be set according to actual needs. For instance, the length of the desired flight path can be set based on the sensing range of the ground sensor, because the UAV can acquire terrain data within its sensing range, thereby adjusting the altitude of the original waypoints based on the terrain data within the sensing range.

[0094] In this embodiment, the desired trajectory of the cargo can be planned based on multiple expected waypoints, the maximum sling swing angle, and the dynamic and kinematic constraints of the UAV. The desired trajectory includes multiple trajectory points and the position, time, velocity, and acceleration of the cargo when it is scheduled to arrive at each trajectory point. The kinematic constraints include the UAV's velocity, acceleration, position, attitude, and geometric constraints, while the dynamic constraints include the UAV's thrust. A smooth cargo route is obtained by fitting multiple expected waypoints. The position, time, velocity, and acceleration of the cargo at each point on the planned cargo route are determined based on the maximum sling swing angle, the UAV's velocity, acceleration, position, attitude, geometric constraints, and thrust. Each point on the planned cargo route is then used as a trajectory point in the desired trajectory. The position, time, velocity, and acceleration of each trajectory point are then summed to obtain the desired trajectory. This embodiment uses the maximum sling swing angle and the dynamic and kinematic constraint information of the UAV to accurately plan the desired flight trajectory, so that the cargo can move along the desired flight trajectory when the UAV is carrying the cargo, thereby improving the control accuracy of the UAV, ensuring that the cargo maintains a safe distance from the ground, and improving the safety of both the cargo and the UAV.

[0095] It should be noted that the cargo and the drone are connected by a sling. It is possible that the sling may collide with the ground while the cargo is moving along the desired trajectory. Therefore, after the desired trajectory is planned, the position of the drone can be deduced from the position of the cargo in the desired trajectory. The position of the cargo and the position of the drone are used to determine whether the sling is kept at a safe distance from the ground. If the sling is kept at a safe distance from the ground, the flight trajectory can be planned based on the currently planned desired trajectory. Otherwise, the currently planned desired trajectory will not be executed.

[0096] The specific implementation process is as follows: Multiple time sampling points are obtained by sampling the time of each trajectory point in the desired trajectory. The corresponding UAV position is determined based on the cargo position and cargo acceleration corresponding to each time sampling point. Multiple distance sampling points are obtained by equidistant sampling between the cargo position and the UAV position corresponding to each time sampling point. The corresponding terrain height is determined on the environmental terrain map based on the position of the distance sampling points. If the difference between the height of the distance sampling point and the corresponding terrain height is less than a preset safety threshold, the desired trajectory of the cargo is replanned based on ground sensing information and the original path. Here, the time sampling points are the time points obtained by sampling the time of each trajectory point.

[0097] For example, multiple time sampling points are obtained by sampling the time at each trajectory point according to a preset time interval. For instance, the time of the first trajectory point of the desired running trajectory and the times of trajectory points that are integer multiples of the preset time interval are used as time sampling points. Then, the cargo position and cargo acceleration at each time sampling point are obtained, i.e., the planned arrival position of the cargo and the cargo acceleration at that time sampling point. The cargo position and cargo acceleration can be obtained from the position and acceleration of the trajectory point at the corresponding time in the desired running trajectory. As can be seen from the above, at any given moment, the drone position is equal to the cargo position plus the product of the sling length and the sling direction. The sling direction is equal to the cargo acceleration divided by the modulus. Therefore, the sling direction can be determined based on the cargo acceleration at the time sampling point. Based on the sling direction, sling length, and cargo position at the time sampling point, the drone position corresponding to that time sampling point, i.e., the planned arrival position of the drone at that time sampling point, is determined. Then, multiple distance sampling points are obtained by sampling at equal intervals along the straight line segment between the drone position and cargo position at the same time sampling point. These distance sampling points are spatial points in three-dimensional space.

[0098] Figure 11 This is a schematic diagram of the distance sampling points provided in an embodiment of this application. For example... Figure 11As shown, the straight line segment between the locations of the drone 11 and the cargo 12 at the same sampling point is the location of the hoisting rope 11. Equidistant sampling along this straight line segment is equivalent to sampling within the hoisting rope 12 location, and the resulting distance sampling point 20 is the spatial point of the hoisting rope 12. Based on the horizontal position of the distance sampling point 20, the terrain height at the corresponding location can be determined on the environmental terrain map. The difference between the height of the distance sampling point 20 and the terrain height at the corresponding location is the vertical height H5 of the distance sampling point 20 relative to the top of the terrain envelope at the corresponding location. The preset safety threshold is the safe distance maintained between the cargo 12 and the hoisting rope 11 and the ground during hoisting. When the vertical height H5 is greater than or equal to the preset safety threshold, it indicates that there is no risk of the hoisting rope 11 spatial point touching the ground during hoisting. When the vertical height H5 is less than the preset safety threshold, it indicates that there is a risk of the hoisting rope 11 spatial point touching the ground during hoisting. Therefore, once the difference between the height of the sampling point 20 and the corresponding terrain height is detected to be less than a preset safety threshold, it indicates that the expected trajectory cannot guarantee the safe movement of the cargo. Thus, the expected trajectory of the cargo is replanned based on ground sensing information and the original path. This embodiment reduces the number of time sampling points used to detect the safety of the expected trajectory by sampling the time of each trajectory point, thereby reducing the computational load on the UAV. Further reducing the computational load on the UAV is achieved by performing equidistant sampling between the cargo position and the UAV position at the same time sampling point to reduce the number of distance sampling points used to detect the safety of the expected trajectory. Distance sampling points characterize the sling space points, and the difference between the height of the sling space point and the terrain height at the corresponding location point determines whether the sling space point has a risk of ground contact, achieving accurate detection of the safety of the expected trajectory and ensuring safety during cargo handling.

[0099] Once the difference between the height of the sampling point and the corresponding terrain height is detected to be less than the preset safety threshold, the process can return to step S130 to re-establish the environmental terrain map, and then re-plan the desired operating trajectory through the environmental terrain map until a desired operating trajectory that can ensure the safe movement of goods is planned.

[0100] S150: Control the drone's flight according to the desired trajectory.

[0101] For example, the control quantity of the UAV can be calculated by back-calculating the position, time, speed and acceleration of the goods when they arrive at each trajectory point in the desired motion trajectory. Then, the UAV can be controlled to lift and fly according to the control quantity, so that the goods arrive at each trajectory point according to the time, speed and acceleration in the desired motion trajectory, thereby ensuring that the goods always maintain a safe distance from the ground and improving the safety of lifting the goods.

[0102] In this process, as the drone flies along the initial flight path, the position, time, speed, and acceleration of the cargo at each trajectory point in the desired trajectory can be used to reverse-engineer the corresponding flight path point of the drone in the initial flight path. This allows for altitude adjustment of the drone's flight, enabling the cargo to move along the desired trajectory during flight and ensuring that the cargo always maintains a safe distance from the ground.

[0103] As described above, if the difference between the height of a distance sampling point and the corresponding terrain height is greater than or equal to a preset safety threshold, it indicates that there is no risk of the sling touching the ground at the corresponding sling point during hoisting. In other words, the desired trajectory can only be guaranteed to ensure the safe movement of goods if and only if the sling at each distance sampling point has no risk of touching the ground. Therefore, when the difference between the height of each distance sampling point and the corresponding terrain height is greater than or equal to the preset safety threshold, the drone is controlled to fly according to the desired trajectory. That is, the difference between the height of each distance sampling point and the corresponding terrain height is compared with the preset safety threshold one by one. If the difference is less than the preset safety threshold, the desired trajectory is stopped. When the difference between the height of all distance sampling points and the corresponding terrain height is greater than the preset safety threshold, the drone is controlled to fly according to the desired trajectory.

[0104] In this embodiment, to improve the control accuracy of the UAV, the UAV's flight trajectory can be deduced from the desired flight trajectory, and then the UAV's flight can be controlled according to the flight trajectory. For example, Figure 12 This is a flowchart illustrating the control of a drone's flight, as provided in an embodiment of this application. Figure 12 As shown, the steps for controlling the flight of the drone specifically include S1501-S1502:

[0105] S1501. Determine the flight trajectory of the UAV based on the desired flight path.

[0106] For example, the position, speed, and acceleration of the drone at the corresponding time can be deduced from the cargo position, speed, and acceleration at each trajectory point in the desired flight path. Then, the drone's flight path can be obtained by summing up the drone position, speed, and acceleration at each time point.

[0107] Since the desired trajectory points are infinite, the computational workload for retrieving the corresponding UAV position, velocity, and acceleration from the cargo position, velocity, and acceleration of these trajectory points is substantial and time-consuming, impacting the UAV's flight control efficiency. To improve the computational efficiency of the flight trajectory, each trajectory point in the desired trajectory can be sampled, and the flight trajectory can be determined based on the sampled points. Specific steps include S15011-S15013:

[0108] S15011. Multiple control points are obtained by sampling each trajectory point in the desired running trajectory based on the control frequency.

[0109] For example, a control point is a time point obtained by sampling the time of each trajectory point based on the control frequency. The UAV's flight controller controls the UAV's flight at a certain control frequency, and the control time can be determined based on the control frequency. The time of the trajectory point in the desired flight trajectory that is the same as the control time is determined as the control point.

[0110] S15012. Determine the UAV position, UAV speed, and UAV acceleration corresponding to the control point based on the cargo position, cargo speed, and cargo acceleration corresponding to the control point.

[0111] For example, the direction of the sling is determined based on the cargo acceleration corresponding to the control point; the position of the drone corresponding to the control point is determined based on the cargo position, sling direction, and sling length; and the position acceleration corresponding to the control point is determined based on the cargo acceleration and gravitational acceleration. The cargo velocity corresponding to the control point is then used as the drone velocity. Here, the cargo position, cargo velocity, and cargo acceleration at the control point represent the planned destination position of the cargo at the control point, as well as its velocity and acceleration during movement. Similarly, the drone position, drone velocity, and drone acceleration at the control point represent the planned destination position of the drone at the control point, as well as its velocity and acceleration during flight.

[0112] S15013. Based on the UAV position, speed, and acceleration corresponding to multiple control points, plan the UAV's flight trajectory.

[0113] For example, the drone's flight trajectory is obtained by summing the drone's position, speed, and acceleration corresponding to multiple control points. In this embodiment, the number of control points used for flight trajectory planning is reduced by sampling each trajectory point through control frequency, thereby reducing the computational load on the drone and improving the efficiency of flight trajectory calculation.

[0114] S1502. Control the flight of the drone according to its flight trajectory.

[0115] For example, based on the time, position, speed, and acceleration corresponding to each trajectory point in the flight path, the control variables of the UAV are determined. These control variables then control the UAV to arrive at the corresponding position at the specified speed and acceleration along the flight path at the corresponding time. Simultaneously, the cargo also arrives at the corresponding position at the specified speed and acceleration along the desired trajectory at the corresponding time. This ensures that the cargo moves along the desired trajectory when the UAV performs a lifting task, maintaining a safe distance from the ground and improving cargo safety.

[0116] In this embodiment, when a controllable point is approaching, the drone's position, speed, and acceleration corresponding to the control point in the flight trajectory are acquired. These parameters are then sent to the drone's flight controller, which controls the drone to fly along the trajectory. While controlling the drone along the trajectory, the flight controller determines control parameters based on these parameters and drives motors to rotate so that the drone reaches its corresponding position at the control point with the appropriate speed and acceleration. Similarly, the cargo reaches its corresponding position with the appropriate speed and acceleration.

[0117] This embodiment uses the expected flight trajectory to infer the drone's flight trajectory, and then uses the flight trajectory to precisely control the drone for hoisting flight, ensuring that the cargo always maintains a safe distance from the ground when the drone flies based on the flight trajectory, thereby improving the safety of cargo hoisting.

[0118] Since the expected trajectory is a planned trajectory over a specific period, there are situations where the lifting task is not completed but the goods are about to move to the end of the expected trajectory. To address this, if the goods move to the end segment of the expected trajectory before the lifting task is completed, a new expected trajectory is planned based on real-time ground sensing information and the original path taken by the ground sensors. The end segment can be understood as a short path before the end of the expected trajectory, and its length can be set according to actual needs. When the goods move to the beginning of the end segment of the expected trajectory, a new expected trajectory can be planned while the drone is controlled to execute the expected trajectory. Once a new expected trajectory is planned and the old one has been executed, the drone is controlled to fly based on the new expected trajectory, and this process continues until the drone reaches the unloading point.

[0119] After a lifting mission is completed, the drone may perform a new lifting mission based on the original route of this mission. Therefore, the currently constructed environmental topographic map can be associated with and saved with the original route of the lifting mission, so that a new environmental topographic map can be directly built on the basis of the environmental topographic map next time, thereby improving the execution efficiency and convenience of subsequent lifting missions.

[0120] It should be noted that most of the positioning sensors currently used by drones are RTK sensors, which are susceptible to environmental influences and can exhibit significant positioning deviations. If the positioning deviation of the drone's positioning sensor is large during a lifting mission, the constructed environmental topographic map will be inaccurate. Therefore, to ensure the safe execution of subsequent lifting missions, the environmental topographic map will not be associated with and saved along the original lifting mission path. To address this, the drone's positioning deviation can be calculated after the lifting mission is completed. If the drone's positioning deviation is equal to or equal to a preset deviation threshold, the environmental topographic map will be associated with and saved along the original lifting mission path. If the drone's positioning deviation is greater than the preset deviation threshold, the environmental topographic map will not be saved. The preset deviation threshold is the minimum deviation at which the drone's positioning deviation will not affect the accuracy of the lifting mission. In other words, if the drone's positioning deviation is less than the preset deviation threshold, it indicates that the environmental topographic map is highly accurate and can be associated with and saved along the original lifting mission path for use in subsequent lifting missions. If the drone's positioning deviation is less than the preset deviation threshold, it indicates that the environmental topographic map is less accurate, and the environmental topographic map will not be saved to avoid affecting the accuracy of subsequent lifting missions.

[0121] In summary, the hoisting flight method provided in this application obtains the original path of the cargo, acquires real-time ground sensing information from ground sensors, constructs a high-precision environmental topographic map based on the ground sensing information, adjusts the altitude of the original path using the environmental topographic map, and plans a desired flight trajectory that mimics the terrain and maintains a safe altitude from the ground based on the adjusted original path. The drone's flight is controlled by this desired flight trajectory to ensure that the cargo maintains a safe distance from the ground throughout the hoisting process, thus improving the safety of both the cargo and the drone. The drone does not need to maintain a target flight altitude continuously during hoisting flight, solving the problem in existing technologies where drones cannot perform hoisting tasks normally due to air traffic control or other reasons, and ensuring the efficiency of hoisting task execution.

[0122] Based on the above embodiments, Figure 13 This is a structural schematic diagram of a hoisting flying device provided in an embodiment of this application. (Reference) Figure 13 The hoisting flying device provided in this embodiment specifically includes: an original path acquisition module 31, a sensor information acquisition module 32, a terrain map establishment module 33, a cargo trajectory planning module 34, and a flight control module 35.

[0123] Among them, the original path acquisition module 31 is configured to acquire the original route of the goods;

[0124] The sensing information acquisition module 32 is configured to acquire ground sensing information collected by the ground sensor;

[0125] The topographic map creation module 33 is configured to create an environmental topographic map based on ground sensing information;

[0126] The cargo trajectory planning module 34 is configured to plan the desired trajectory of the cargo based on the environmental topographic map and the original route.

[0127] Flight control module 35 is configured to control the flight of the drone according to the desired flight trajectory.

[0128] Based on the above embodiments, the original path acquisition module 31 includes: a horizontal position determination submodule, configured to determine the horizontal position of the initial flight path of the UAV as the horizontal position of the original path of the cargo; an altitude determination submodule, configured to determine a preset safety distance as the altitude of each waypoint in the original path of the cargo relative to the takeoff point; wherein the preset safety distance is the safety distance maintained between the cargo and the ground; and an original path generation submodule, configured to generate the original path of the cargo based on the horizontal position of the original path of the cargo and the altitude of each waypoint relative to the takeoff point.

[0129] Based on the above embodiments, the topographic map building module 33 includes: a data filtering submodule, configured to filter the rope data and cargo data in the ground sensing information to obtain the remaining ground sensing information; and a topographic map building submodule, configured to build an environmental topographic map based on the remaining ground sensing information.

[0130] Based on the above embodiments, the data filtering submodule includes: a sling information acquisition unit configured to acquire the sling length and sling direction; a location information acquisition unit configured to determine the cargo location and sling location based on the sling direction, sling length, and UAV location; and a data filtering unit configured to determine the sling data and cargo data in the ground sensing information based on the sling location and cargo location, and filter the sling data and cargo data in the ground sensing information to obtain the remaining ground sensing information.

[0131] Based on the above embodiments, the sling information acquisition unit includes: a sling length acquisition subunit, configured to acquire the sling length set in the hoisting task; or, a sling length determination subunit, configured to determine the sling length based on the sling swing angle and the drone position when the change in flight power detected when the drone lifts the cargo is greater than a preset change threshold.

[0132] Based on the above embodiments, the sling information acquisition unit includes: a first sling direction detection subunit, configured to detect the sling direction through a motion sensor installed on the sling hook; or, a second sling direction detection subunit, configured to detect the sling direction through a force sensor installed at the connection between the sling and the drone; or, a sling direction determination subunit, configured to determine the cargo acceleration through the drone acceleration and determine the sling direction based on the cargo acceleration.

[0133] Based on the above embodiments, the location information acquisition unit includes: a translation vector determination subunit, configured to determine the translation vector between the UAV and the cargo based on the length and direction of the sling; and a cargo position determination subunit, configured to determine the cargo position based on the translation vector and the UAV position.

[0134] Based on the above embodiments, the data filtering unit includes: a sling data determination subunit, configured to determine a sling area based on the sling position, determine a sling neighborhood centered on the sling area within a preset distance range, and determine the ground sensing information within the sling area and the sling neighborhood as sling data; and a cargo data determination subunit, configured to determine a cargo area based on the cargo position, determine a cargo neighborhood centered on the cargo area within a preset distance range, and determine the ground sensing information within the cargo area and the cargo neighborhood as cargo data.

[0135] Based on the above embodiments, the topographic map building submodule includes: a first topographic map building unit, configured to update the topographic height of corresponding points in the initial environmental topographic map according to the height of each point in the topographic data when the original route of the hoisting task is executed for the first time; wherein the topographic height of each point in the initial environmental topographic map is zero; and a second topographic map building unit, configured to obtain the historical environmental topographic map corresponding to the original route when the original route of the hoisting task is not executed for the first time, and update the topographic height of corresponding points in the historical environmental topographic map according to the height of each point in the topographic data.

[0136] Based on the above embodiments, the cargo trajectory planning module 34 includes: a cargo waypoint acquisition submodule, configured to acquire multiple original waypoints on the original route; a terrain elevation adjustment submodule, configured to perform terrain elevation adjustment on the multiple original waypoints according to the environmental topographic map to obtain multiple expected waypoints for the cargo, wherein the height of the expected waypoints is equal to the sum of the height of the original waypoints at the same horizontal position and the terrain height at the corresponding position point in the environmental topographic map; and a first cargo trajectory planning submodule, configured to plan the expected trajectory of the cargo based on the multiple expected waypoints.

[0137] Based on the above embodiments, the cargo trajectory planning submodule includes a cargo route planning unit, which is configured to plan the desired trajectory of the cargo based on multiple desired waypoints, the maximum sling swing angle, and the dynamic and kinematic constraints of the UAV. The desired trajectory includes multiple trajectory points and the position, time, speed, and acceleration of the cargo when it is scheduled to arrive at each trajectory point.

[0138] Based on the above embodiments, the hoisting flight device further includes a cargo trajectory verification module. The cargo trajectory verification module includes: a time sampling unit, configured to, after planning the desired trajectory of the cargo based on the environmental topographic map and the original route, perform time sampling on each trajectory point in the desired trajectory to obtain multiple time sampling points, and determine the corresponding UAV position based on the cargo position and cargo acceleration corresponding to each time sampling point; a distance sampling unit, configured to perform equidistant sampling between the cargo position and the UAV position corresponding to the time sampling points to obtain multiple distance sampling points, and determine the corresponding terrain height on the environmental topographic map based on the position of the distance sampling points; and a cargo trajectory verification unit, configured to, if the difference between the height of the distance sampling point and the corresponding terrain height is less than a preset safety threshold, replan the desired trajectory of the cargo based on ground sensing information and the original route.

[0139] Based on the above embodiments, the flight control module 35 includes: a first flight control submodule, configured to control the drone to fly according to the desired flight trajectory when the difference between the height of each distance sampling point and the corresponding terrain height is greater than or equal to a preset safety threshold.

[0140] Based on the above embodiments, the flight control module 35 includes: a flight trajectory planning submodule, configured to determine the flight trajectory of the UAV according to the desired operating trajectory; and a second flight control submodule, configured to control the flight of the UAV according to the flight trajectory.

[0141] Based on the above embodiments, the flight trajectory planning submodule includes: a control point sampling unit, configured to sample each trajectory point in the desired operating trajectory based on the control frequency to obtain multiple control points; a control point information determination unit, configured to determine the UAV position, UAV speed, and UAV acceleration corresponding to the control point based on the cargo position, cargo speed, and cargo acceleration corresponding to the control point; and a second flight trajectory planning unit, configured to plan the UAV's flight trajectory based on the UAV position, UAV speed, and UAV acceleration corresponding to the multiple control points.

[0142] Based on the above embodiments, the second flight control submodule includes: a flight control unit, configured to send the UAV position, UAV speed and UAV acceleration corresponding to the control point to the UAV's flight controller, so that the flight controller controls the UAV to fly along the flight trajectory.

[0143] Based on the above embodiments, the cargo trajectory planning module 34 includes: a second cargo trajectory planning submodule, configured to plan a new desired trajectory based on the ground sensing information sampled in real time by the ground sensor and the original path if the cargo moves to the end segment of the desired trajectory before the hoisting task is completed after the UAV is controlled to fly according to the desired trajectory.

[0144] Based on the above embodiments, the hoisting flight device further includes a topographic map storage module, which is configured to, after controlling the UAV to fly according to the desired flight trajectory, if the positioning deviation of the UAV is less than or equal to a preset deviation threshold after the hoisting task is completed, associate and save the environmental topographic map with the original path of the hoisting task.

[0145] The hoisting flight device provided in this application, as described above, acquires the original path of the cargo, obtains real-time ground sensing information from ground sensors, constructs a high-precision environmental topographic map based on the ground sensing information, adjusts the altitude of the original path using the environmental topographic map, and plans a desired flight trajectory that mimics the terrain and maintains a safe altitude from the ground based on the adjusted original path. The drone's flight is controlled by this desired flight trajectory to ensure that the cargo maintains a safe distance from the ground throughout the hoisting process, thus improving the safety of both the cargo and the drone. The drone does not need to maintain a target flight altitude continuously during hoisting flight, solving the problem in the prior art where drones cannot perform hoisting tasks normally due to air traffic control or other reasons, and ensuring the efficiency of hoisting task execution.

[0146] The hoisting flying device provided in this application embodiment can be used to execute the hoisting flying method provided in the above embodiment, and has corresponding functions and beneficial effects.

[0147] Figure 14 This is a schematic diagram of the structure of a drone hoisting flight device provided in an embodiment of this application, with reference to... Figure 14 The drone includes a processor 41, a memory 42, a communication device 43, an input device 44, and an output device 45. The number of processors 41 and the number of memories 42 in the hoisting flight equipment can be one or more. The processor 41, memory 42, communication device 43, input device 44, and output device 45 of the hoisting flight equipment can be connected via a bus or other means.

[0148] The memory 42, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the hoisting flight method in any embodiment of this application (e.g., the original path acquisition module 31, sensor information acquisition module 32, topographic map creation module 33, cargo trajectory planning module 34, and flight control module 35 in the hoisting flight device). The memory 42 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device, etc. Furthermore, the memory 42 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0149] The communication device 43 is used for data transmission.

[0150] The processor 41 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 42, thereby realizing the above-mentioned hoisting and flying method.

[0151] Input device 44 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. Output device 45 may include display devices such as a display screen.

[0152] The drones provided above can be used to perform the hoisting flight method provided in the above embodiments, and have the corresponding functions and beneficial effects.

[0153] This application embodiment also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to execute a hoisting flight method for a drone. The hoisting flight method includes: acquiring ground sensing information collected in real time by a ground sensor; filtering the hoisting rope data and cargo data in the ground sensing information to obtain terrain data; establishing an environmental terrain map based on the terrain data; planning a desired flight trajectory based on the environmental terrain map; determining the drone's flight trajectory based on the desired flight trajectory; and controlling the drone's flight based on the flight trajectory.

[0154] Storage medium – any type of memory device or storage device. The term “storage medium” is intended to include: mounting media, such as CD-ROM, floppy disk, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. Storage medium may also include other types of memory or combinations thereof. Furthermore, storage medium may reside in a first computer system in which the program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term “storage medium” can include two or more storage media residing in different locations (e.g., in different computer systems connected via a network). Storage medium may store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0155] Of course, the computer-executable instructions contained in the storage medium provided in the embodiments of this application are not limited to the hoisting and flying method described above, but can also perform related operations in the hoisting and flying method provided in any embodiment of this application.

[0156] The hoisting flight device, storage medium, and UAV provided in the above embodiments can execute the hoisting flight method provided in any embodiment of this application. For technical details not described in detail in the above embodiments, please refer to the hoisting flight method provided in any embodiment of this application.

[0157] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of this application. The scope of this application is determined by the scope of the claims.

Claims

1. A method for hoisting and flying an unmanned aerial vehicle (UAV), characterized in that, The drone is equipped with a ground-based sensor and a hoisting system, the hoisting system including a hoisting rope and cargo hoisted on the hoisting rope, the method including: Obtain the original route taken by the goods; Acquire ground sensing information collected by ground sensors; The sling data and cargo data in the ground sensing information are filtered to obtain the remaining ground sensing information; wherein, the sling data and the cargo data are determined based on the sling position and the cargo position, the cargo position is obtained by subtracting the product of the sling direction and the sling length from the UAV position, and the sling position is the position of the line connecting the cargo position and the UAV position; An environmental topographic map is created based on the remaining ground sensing information; The desired trajectory of the cargo is planned based on the environmental topographic map and the original route. The flight trajectory of the UAV is determined based on the desired flight trajectory; the flight of the UAV is controlled based on the flight trajectory.

2. The hoisting flight method according to claim 1, characterized in that, The process of obtaining the original route taken by the goods includes: The horizontal position of the initial flight path of the drone is determined as the horizontal position of the original route of the cargo. The preset safety distance is defined as the altitude of each waypoint in the original route of the cargo relative to the takeoff point; wherein, the preset safety distance is the safety distance maintained between the cargo and the ground; The original route of the cargo is generated based on the horizontal position of the original route and the altitude of each waypoint relative to the takeoff point.

3. The hoisting flight method according to claim 1, characterized in that, The process of filtering the rope data and cargo data from the ground sensing information to obtain the remaining ground sensing information includes: Get the length and direction of the suspension rope; The cargo position and the sling position are determined based on the sling direction, the sling length, and the drone position. Based on the position of the hoisting rope and the position of the cargo, the hoisting rope data and cargo data in the ground sensing information are determined, and the remaining ground sensing information is obtained by filtering the hoisting rope data and cargo data in the ground sensing information.

4. The hoisting and flying method according to claim 3, characterized in that, The process of obtaining the length of the suspension rope includes: Get the length of the hoisting rope set in the hoisting task; or, When the change in flight power of the drone when it pulls up the cargo is greater than a preset change threshold, the length of the sling is determined based on the sling swing angle and the drone position.

5. The hoisting and flying method according to claim 3, characterized in that, The process of obtaining the direction of the hoisting rope includes: The direction of the suspension rope is detected by a motion sensor mounted on the rope hook; or... The direction of the sling is detected by a force sensor installed at the connection point between the sling and the drone; or, The acceleration of the cargo is determined by the acceleration of the drone, and the direction of the lifting rope is determined based on the acceleration of the cargo.

6. The hoisting flight method according to claim 3, characterized in that, The step of determining the sling data and cargo data in the ground sensing information based on the sling position and the cargo position includes: The suspension rope area is determined based on the suspension rope position, and the suspension rope neighborhood is determined with the suspension rope area as the center within a preset distance range. The ground sensing information of the suspension rope area and the suspension rope neighborhood is determined as suspension rope data. Based on the cargo location, a cargo area is determined, and a cargo neighborhood within a preset distance range centered on the cargo area is determined. The ground sensing information within the cargo area and the cargo neighborhood is then identified as cargo data.

7. The hoisting flight method according to claim 1, characterized in that, An environmental topographic map is constructed based on the remaining Earth sensing information, including: If the original path of the hoisting task is the first execution, the terrain height of the corresponding point in the initial environmental terrain map is updated according to the height of each point in the remaining ground sensing information; wherein, the terrain height of each point in the initial environmental terrain map is zero. If the original route of the hoisting task is not the first execution, obtain the historical environmental topographic map corresponding to the original route, and update the terrain height of the corresponding position point in the historical environmental topographic map according to the height of each position point in the remaining ground sensing information.

8. The hoisting flight method according to claim 1, characterized in that, The step of planning the desired trajectory of the cargo based on the environmental topographic map and the original route includes: Obtain multiple original waypoints along the original route; Based on the environmental topographic map, the elevation of the multiple original waypoints is adjusted by terrain simulation to obtain multiple desired waypoints for the cargo. The elevation of the desired waypoint is equal to the sum of the elevation of the original waypoint at the same horizontal position and the elevation of the corresponding position on the environmental topographic map. The desired trajectory of the cargo is planned based on the multiple desired waypoints.

9. The hoisting flight method according to claim 8, characterized in that, The step of planning the desired trajectory of the cargo based on the multiple desired waypoints includes: The desired trajectory of the cargo is planned based on the multiple expected waypoints, the maximum sling swing angle, and the dynamic and kinematic constraints of the UAV. The desired trajectory includes multiple trajectory points and the position, time, speed, and acceleration of the cargo when it is scheduled to arrive at each trajectory point.

10. The hoisting flight method according to claim 1, characterized in that, After planning the desired trajectory of the cargo based on the environmental topographic map and the original route, the method further includes: Multiple time sampling points are obtained by sampling each trajectory point in the desired running trajectory. The corresponding UAV position is determined based on the cargo position and cargo acceleration corresponding to each time sampling point. Multiple distance sampling points are obtained by performing equidistant sampling between the cargo location and the drone location corresponding to the time sampling point. The corresponding terrain height is determined in the environmental terrain map based on the location of the distance sampling points. If the difference between the height of the distance to the sampling point and the corresponding terrain height is less than a preset safety threshold, the desired trajectory of the cargo is replanned based on the ground sensing information and the original route.

11. The hoisting flight method according to claim 10, characterized in that, The step of controlling the drone's flight according to the desired trajectory includes: If the difference between the height of each distance sampling point and the corresponding terrain height is greater than or equal to a preset safety threshold, the drone is controlled to fly according to the desired trajectory.

12. The hoisting flight method according to claim 1, characterized in that, Determining the flight trajectory of the UAV based on the desired flight trajectory includes: Multiple control points are obtained by sampling each trajectory point in the desired running trajectory based on the control frequency; The position, speed, and acceleration of the drone corresponding to the control point are determined based on the cargo position, cargo speed, and cargo acceleration of the control point. The flight trajectory of the UAV is planned based on the UAV position, speed, and acceleration corresponding to multiple control points.

13. The hoisting flight method according to claim 12, characterized in that, The step of controlling the drone's flight according to the flight trajectory includes: The drone's position, speed, and acceleration corresponding to the control point are sent to the drone's flight controller, which then controls the drone to fly along the flight path.

14. The hoisting flight method according to claim 1, characterized in that, After controlling the drone's flight according to the desired trajectory, the method further includes: If the cargo moves to the end of the expected trajectory before the hoisting task is completed, a new expected trajectory will be planned based on the ground sensing information sampled in real time by the ground sensor and the original path.

15. The hoisting flight method according to claim 1, characterized in that, After controlling the drone's flight according to the desired trajectory, the method further includes: After the hoisting task is completed, if the positioning deviation of the UAV is less than or equal to a preset deviation threshold, the environmental topographic map is associated with and saved along the original route of the hoisting task.

16. A hoisting flight device for an unmanned aerial vehicle, characterized in that, The drone is equipped with a ground-based sensor and a hoisting system. The hoisting system includes a hoisting rope and cargo hoisted on the hoisting rope. The device includes: The original path acquisition module is configured to acquire the original route taken by the goods; The sensor information acquisition module is configured to acquire ground sensing information collected by the ground sensor; The topographic map building module is configured to filter the sling data and cargo data in the ground sensing information to obtain the remaining ground sensing information; and to build an environmental topographic map based on the remaining ground sensing information; wherein the sling data and cargo data are determined based on the sling position and cargo position, the cargo position is obtained by subtracting the product of the sling direction and the sling length from the UAV position, and the sling position is the position of the line connecting the cargo position and the UAV position; The cargo trajectory planning module is configured to plan the desired trajectory of the cargo based on the environmental topographic map and the original route. The flight control module is configured to determine the flight trajectory of the UAV based on the desired flight trajectory; and to control the flight of the UAV based on the flight trajectory.

17. A hoisting flight device for an unmanned aerial vehicle (UAV), characterized in that, include: One or more processors; A memory that stores one or more programs that, when executed by one or more processors, cause the one or more processors to implement the sling-flying method as described in any one of claims 1-15.

18. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the hoisting flight method as described in any one of claims 1-15.

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