WO2021237485A1 - 无人飞行器的航线平滑处理方法、装置及控制终端 - Google Patents

无人飞行器的航线平滑处理方法、装置及控制终端 Download PDF

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Publication number
WO2021237485A1
WO2021237485A1 PCT/CN2020/092463 CN2020092463W WO2021237485A1 WO 2021237485 A1 WO2021237485 A1 WO 2021237485A1 CN 2020092463 W CN2020092463 W CN 2020092463W WO 2021237485 A1 WO2021237485 A1 WO 2021237485A1
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Prior art keywords
route
waypoint
altitude
smoothness
work
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PCT/CN2020/092463
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English (en)
French (fr)
Inventor
邹亭
赵力尧
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深圳市大疆创新科技有限公司
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Priority to CN202080044429.4A priority Critical patent/CN114041097B/zh
Priority to PCT/CN2020/092463 priority patent/WO2021237485A1/zh
Publication of WO2021237485A1 publication Critical patent/WO2021237485A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/10—Simultaneous control of position or course in three dimensions

Definitions

  • the present invention belongs to the technical field of flight, and particularly relates to a method, device and control terminal for smoothing flight routes of unmanned aerial vehicles.
  • unmanned aerial vehicles are used more and more widely.
  • users often use unmanned aerial vehicles to perform various tasks such as aerial photography, agricultural plant protection, and surveying.
  • unmanned aerial vehicles to perform operational tasks
  • the initial route of the planned operation area will be smoothed to obtain the target route, and then the unmanned aerial vehicle will be controlled according to the target route.
  • the human aircraft performs operations on the operation objects in the operation area.
  • the unmanned aerial vehicle may perform different tasks (for example, trees, rice or buildings) in the operation area according to the planned route in different operation scenarios (such as mountains, hills or plains). Such as spraying or shooting).
  • different situations different job scenarios, different types of job tasks, and different types of job objects
  • the solutions in the prior art cannot adapt to the different requirements for smoothness in various situations.
  • the invention provides an unmanned aerial vehicle's route smoothing method, device and control terminal to meet the different requirements of the unmanned aerial vehicle for the smoothness of the route in various situations.
  • the present invention is implemented as follows:
  • an embodiment of the present invention provides a route smoothing method for an unmanned aerial vehicle, the method including:
  • Acquire smoothness adjustment parameters where the smoothness adjustment parameters are based on the topography of the work area, the status information of the work object in the work area, the type of work performed on the work object, and the user’s One or more of the smoothness adjustment operations are determined;
  • an embodiment of the present invention provides a route smoothing device for an unmanned aerial vehicle.
  • the device includes a memory and a processor,
  • the memory is used to store program codes
  • the processor calls the program code, and when the program code is executed, is used to perform the following operations:
  • Acquire smoothness adjustment parameters where the smoothness adjustment parameters are based on the topography of the work area, the status information of the work object in the work area, the type of work performed on the work object, and the user’s One or more of the smoothness adjustment operations are determined;
  • an embodiment of the present invention provides a control terminal, and the control terminal includes: the above-mentioned unmanned aerial vehicle route smoothing device.
  • an embodiment of the present invention provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the method for smoothing the flight path of the above-mentioned unmanned aerial vehicle is realized.
  • the initial flight path of the unmanned aerial vehicle in the operation area can be obtained, and the smoothness adjustment parameter can be obtained; wherein, the smoothness adjustment parameter is based on the topography of the operation area, the status information of the operation object in the operation area, and the operation One or more of the task type performed by the object and the user’s smoothness adjustment operations are determined. Then, according to the smoothness adjustment parameters, the initial route is smoothed to obtain the target route, and finally, the target route is controlled according to the target route.
  • the unmanned aerial vehicle performs operation tasks on the operation objects in the operation area.
  • one of the smoothness adjustment operations according to the topography of the work area, the status information of the work object in the work area, the type of work task performed on the work object, and the user's smoothness adjustment operation Or multiple types of determined smoothing adjustment parameters, so that the smoothing adjustment parameters can be more adapted to the current operation tasks and/or user requirements, so as to adapt to the different requirements of the unmanned aerial vehicle for the smoothness of the route in various situations.
  • FIG. 1 is a schematic diagram of an application scenario of an unmanned aerial vehicle route smoothing method provided by an embodiment of the present application
  • FIG. 2 is a flow chart of the steps of a method for smoothing a flight path of an unmanned aerial vehicle according to an embodiment of the present application
  • FIG. 3 is a schematic diagram of a smoothness setting interface provided by an embodiment of the present application.
  • Fig. 4 is a schematic diagram of a route provided by an embodiment of the present application.
  • Fig. 5 is a schematic diagram of another route provided by an embodiment of the present application.
  • Fig. 6 is a schematic diagram of route fitting provided by an embodiment of the present application.
  • FIG. 7 is another schematic diagram of route fitting provided by an embodiment of the present application.
  • FIG. 8 is a schematic diagram of an initial route provided by an embodiment of the present application.
  • FIG. 9 is a schematic diagram of processing a non-operating route provided by an embodiment of the present application.
  • FIG. 10 is a block diagram of a route smoothing device for an unmanned aerial vehicle according to an embodiment of the present application.
  • FIG. 11 is a block diagram of a computing processing device provided by an embodiment of this application.
  • FIG. 12 is a block diagram of a portable or fixed storage unit provided by an embodiment of the application.
  • FIG. 1 is a schematic diagram of an application scenario of an unmanned aerial vehicle's route smoothing method provided by an embodiment of the present application.
  • the application scenario may include: the unmanned aerial vehicle 10, the user 20, the control terminal 30, and the area 40 where the farmland is located.
  • the user 20 may first plan an initial route for the operation task.
  • the initial route may represent a flight path that can be covered by the work object in the area 40 where the farmland is located.
  • the user 20 uses the control terminal 30 to control the unmanned aerial vehicle 10 to fly and spray according to the initial route, so that pesticides can be sprayed on the working objects in the area 40 where the farmland is located.
  • the smoothness of the route will affect the attitude adjustment of the unmanned aerial vehicle in flight, for example, when the smoothness requirement is high, that is, when the smoothness requirement is low, the unmanned aerial vehicle performs the operation task according to the route.
  • the flight attitude may be frequently adjusted to make the target route accurately follow the initial route. Therefore, after the initial route is obtained, the initial route is often smoothed.
  • the user 20 can obtain the initial route of the unmanned aerial vehicle in the operation area, for example, the area 40 where the farmland is located, through the control terminal 30, and then obtain the smoothness adjustment parameter, where the smoothness adjustment parameter is based on the topography and operation of the operation area.
  • One or more of the status information of the work object in the area, the type of work task performed on the work object, and the user's smoothness adjustment operation are determined, and the initial route is smoothed according to the smoothness adjustment parameter to obtain The target route, and finally the unmanned aerial vehicle 10 is controlled to perform operation tasks according to the target route.
  • the smoothing adjustment parameters determine the smoothing adjustment parameters, so that the smoothing adjustment parameters can be more adapted to the current job scene, job object, job task and/or user needs, so that it can adapt to the smoothness of various situations.
  • Different requirements can improve the effect of smoothing the initial route to a certain extent, and further improve the efficiency of performing tasks according to the target route.
  • the route smoothing processing method of the unmanned aerial vehicle will be described in detail below.
  • Fig. 2 is a flow chart of the steps of a method for smoothing a flight route of an unmanned aerial vehicle provided by an embodiment of the present application. As shown in Fig. 2, the method may include:
  • Step 101 Obtain the initial route of the unmanned aerial vehicle in the operation area.
  • the route smoothing method provided in the embodiments of the present application can be applied to a route smoothing device of an unmanned aerial vehicle.
  • the route smoothing device may be a device installed on an unmanned aerial vehicle.
  • the route smoothing device may also be able to be set on an independent device that wirelessly communicates with an unmanned aerial vehicle, for example, a control terminal, that is, the control terminal includes the route smoothing device.
  • the control terminal may be a terminal for flight route planning.
  • the terminal may be any one or more of a desktop computer, a notebook computer, a smart phone, a wearable device, and a remote control.
  • the operation area may be an area where the unmanned aerial vehicle performs operation tasks. For example, assuming that the operation task performed by the unmanned aerial vehicle is spraying pesticides on farmland A, then the area where farmland A is located can be the operation area.
  • the process of planning the initial route may be: first identifying the operation area and the operation objects in the operation area to obtain the recognition result. Then, according to the recognition results of the work area and the work object, a reciprocating coverage path is generated, and then, according to the obstacle information in the work area, the reciprocating coverage path is adjusted to avoid obstacles. Delete the collinear in the path, the path points that are closer to the front and back, and the path points that have larger undulations, and then get the initial route. It should be noted that in actual application scenarios, path interpolation and path point height sampling can also be performed on the path according to user settings to set the attributes of the job task, for example, to set the spraying attributes. The embodiment of the application does not limit this.
  • Step 102 Obtain a smoothness adjustment parameter, where the smoothness adjustment parameter is based on the topography of the work area, the status information of the work object in the work area, and the type of work task performed on the work object. And one or more of the smoothness adjustment operations of the user are determined.
  • one or more of the topography of the work area, the status information of the work object in the work area, the type of work task performed on the work object, and the smoothness adjustment operation of the user can be determined first, and then Determine the smoothness adjustment parameter according to one or more of them. In this way, compared to directly reading the preset fixed slip adjustment parameter, the determined smoothness adjustment parameter can be more adapted to the current current task situation and/or user requirements to a certain extent.
  • Step 103 Perform smoothing processing on the initial route according to the smoothness adjustment parameter to obtain a target route.
  • the smoothness adjustment parameter may determine the smoothness of the target route obtained after smoothing the initial route. According to different smoothness adjustment parameters, the smoothness of the target route obtained after smoothing the same initial route can be different. Since the smoothness adjustment parameter in the embodiment of the present application is based on the topography of the work area, the status information of the work object in the work area, the type of work task performed on the work object, and the smoothness adjustment operation of the user Or more. Therefore, according to the smoothness adjustment parameter, the obtained smoothness of the target route can be better adapted to the current mission situation and/or user requirements to a certain extent.
  • Step 104 Control the unmanned aerial vehicle to perform the operation task on the operation object in the operation area according to the target route.
  • the unmanned aerial vehicle can be controlled to fly according to the target route, so as to implement the operation task on the operation object in the operation area.
  • the smoothness of the target route obtained may be low, and the accuracy of the ground simulation may be too high.
  • the repeated fluctuations of the route will cause the ineffective loss of the UAV's power and reduce the operation efficiency of the UAV.
  • the unmanned aerial vehicle is likely to perform obstacle avoidance and braking operations in scenes with large terrain undulations such as mountain slopes, which in turn leads to poor stability of the unmanned aerial vehicle.
  • the smoothness of the obtained target route may be higher. In this way, the route will be too smooth and the accuracy of the ground simulation will be too low, which will result in a poor operation effect.
  • the job object cannot be fully covered.
  • the smoothness of the target route obtained according to the smoothness adjustment parameter can be more adapted to the current actual situation. , Thereby ensuring the operation efficiency of subsequent unmanned aerial vehicles according to the target route and the stability of unmanned aerial vehicles. In this way, it adapts to the different requirements of the unmanned aerial vehicle for the smoothness of the route in various situations.
  • the route smoothing method for unmanned aerial vehicles can obtain the initial route of the unmanned aerial vehicle in the operation area and obtain the smoothness adjustment parameters; wherein, the smoothness adjustment parameters are based on the terrain of the operation area.
  • the status information of the operation object in the operation area, the operation type of the operation task performed on the operation object and the user's smoothness adjustment operation are determined, and then the initial route is carried out according to the smoothness adjustment parameter. Smooth processing to obtain the target route.
  • the unmanned aerial vehicle is controlled to perform tasks on the operation objects in the operation area.
  • one of the smoothness adjustment operations according to the topography of the work area, the status information of the work object in the work area, the type of work task performed on the work object, and the user's smoothness adjustment operation Or a variety of determined smoothing adjustment parameters, so that the smoothing adjustment parameters can be more adapted to the current operation tasks and/or user needs, and adapt to the different requirements of the unmanned aerial vehicle for the smoothness of the route in various situations.
  • the operation of obtaining the smoothness adjustment parameter may include sub-step (1) to sub-step (2):
  • Sub-step (1) detecting the smoothness adjustment operation of the user.
  • the smoothness adjustment operation may be an operation in which the user sets the smoothness according to actual requirements.
  • the higher the accuracy of the flight path the lower the smoothness of the flight path.
  • the lower the accuracy of the flight path the higher the smoothness of the flight path.
  • Different users may have different requirements for accuracy, that is, different users may have different requirements for smoothness. Therefore, in the embodiment of the present application, when the smoothness adjustment parameter is obtained, the smoothness adjustment operation of the user may be detected first to understand the real needs of the user.
  • the embodiment of the present application may display the smoothness setting interface on the interactive device before detecting the smoothness adjustment operation.
  • detecting the smoothness adjustment operation of the user may be: detecting the smoothness setting operation of the user on the smoothness setting interface.
  • the interaction device may be a device for interacting with the user, and the interaction device may be set on the control terminal, that is, the control terminal may include the interaction device.
  • the smoothness setting interface may be an interface for setting the smoothness.
  • the smoothness setting interface may display a control for setting the smoothness, and the smoothness setting operation may be a setting operation that the user can perform on the control.
  • the preset spraying height is 3m.
  • the actual spraying height is between 2.5-3.5m and users can only accept it, while in some scenarios, the actual spraying height is between 2.0-4.0m and the users can accept it.
  • the smoothness setting interface is displayed, so that the user can conveniently set the smoothness according to the real needs, and thus can generate routes that can meet the different operation requirements of the user in different operation scenarios.
  • the user can complete the setting through the smoothness setting interface, which can improve user operation efficiency to a certain extent.
  • FIG. 3 is a schematic diagram of a smoothness setting interface provided by an embodiment of the present application.
  • the smoothness setting interface includes a slider control 05 for setting the smoothness.
  • the setting operation can be a drag operation on the option 051 in the slider control 05, or a click operation on the option 052 or 053 in the slider control 05, and an input operation on the option 054 in the slider control 05.
  • Sub-step (2) generating the smoothness adjustment parameter according to the detected smoothness adjustment operation.
  • the smoothness value corresponding to the detected smoothness adjustment operation may be obtained first, for example, after obtaining the user drag option 051, the smoothness value 0.5 corresponding to the slider control 05 is obtained. Then, the smoothness adjustment parameter is generated according to the smoothness value. Since the smoothness setting operation is often performed by the user according to actual needs, in this way, by detecting the user's smoothness setting operation, the smoothness adjustment parameter is generated according to the smoothness setting operation, so that the smoothness adjustment parameter can be adapted to the user's needs, thereby improving the follow-up The target route obtained by smoothing based on the smoothness adjustment parameter.
  • the operation of obtaining the smoothness adjustment parameter may include the following sub-steps (3) to (4):
  • Sub-step (3) respectively determine the topography of the work area, the status information of the work object in the work area, and the smoothing parameter components corresponding to the work type of the work task performed on the work object.
  • the status information of the work objects in the work area may include at least one of the following: the density of work objects in the work area, the type of work objects in the work area, and the coverage rate of the work objects in the work area.
  • the status information of the work object in the work area may be determined according to the three-dimensional model information of the work area.
  • the density of work objects is used to indicate the distance between work objects in the work area. The greater the distance between the work objects, the lower the density. The smaller the distance between the work objects, the greater the density.
  • the type of the job object can represent the attributes of the job object, and different types of job objects have different attributes. The types can be pre-divided according to the characteristics of different work objects. For example, the types can be divided into herbaceous plants, woody plants, or can also be divided into living objects, inanimate objects, and so on.
  • the coverage rate of the job object in the job area is used to indicate the proportion of the job object in the job area. The larger the proportion of work objects in the work area, the higher the coverage rate, and the smaller the proportion of work objects in the work area, the lower the coverage rate.
  • the density, type, and coverage of work objects in the work area will affect the execution process of the work task, there is a correlation between the two. For example, for different types of work objects, the spraying process may be different when performing spraying tasks when the density and coverage of the work objects are different. Therefore, in the embodiments of the present application, the density, type, and coverage rate are used as the status information, to a certain extent, to ensure that the subsequent smooth adjustment parameters determined based on the status information can be more adapted to the work task.
  • the UAV when determining the status information based on the three-dimensional model information of the work area, the UAV can be controlled to collect information on the work area first, and the images, poses and postures of the cameras mounted on the UAV can be recorded during the collection process.
  • the three-dimensional model information is constructed according to the recorded information, where the three-dimensional model information can be any information used to represent the three-dimensional features of the work area, for example, three-dimensional point cloud information, three-dimensional map information, or elevation map information, and so on.
  • the three-dimensional model information can be input into the neural network model, and the density, type, and coverage of the work objects in the work area can be identified according to the neural network model.
  • the status information can be determined more accurately based on the three-dimensional model information, thereby ensuring smooth adjustment parameters determined by the subsequent use of the status information accuracy.
  • a smoothing parameter component corresponding to the density can be generated in a manner that the density is positively correlated with the smoothing parameter component. According to the negative correlation between the coverage rate and the smoothing parameter component, the smoothing parameter component corresponding to the coverage rate is generated.
  • the positive correlation between the density and the smoothing parameter component indicates that the greater the density, the greater the smoothing parameter component corresponding to the density.
  • the negative correlation between the coverage rate and the smoothing parameter component indicates that the greater the coverage rate, the smaller the smoothing parameter component corresponding to the coverage rate.
  • the concentration of work objects in the work area may be used as the input of the first preset generating function, and the output of the first preset generating function may be used as the smoothing parameter component corresponding to the concentration.
  • the coverage of the work object in the work area is used as the input of the second preset generating function, and the output of the second preset generating function is used as the smoothing parameter component corresponding to the coverage.
  • the first preset generating function is a preset function in which the independent variable is positively correlated with the dependent variable
  • the second preset generating function is a preset function in which the independent variable is negatively correlated with the dependent variable.
  • the smoothing parameter component corresponding to the topography of the work area can be determined according to the undulation degree of the topography of the work area; wherein the undulation degree of the topography is positively correlated with the smoothing parameter component corresponding to the topography.
  • the degree of undulation of the terrain may be obtained by using a neural network model to identify the three-dimensional model information of the work area.
  • the degree of undulation of the terrain of the work area may be used as the input of the third preset generating function, and the output of the third preset generating function may be used as the smoothing parameter component corresponding to the terrain.
  • the third preset generating function is a preset function in which the independent variable and the dependent variable are positively correlated, and the third preset generating function may be the same as or different from the aforementioned first preset function.
  • the smoothing parameter component of the type of the work object may be obtained according to the preset first correspondence between the type of the work object and the smoothing parameter component.
  • obtain the smoothing parameter component corresponding to the job type according to the preset second correspondence between the job type and the smoothing parameter component.
  • the job type may be determined according to the attributes of the job task set by the user. For example, if the attribute of the job task set by the user is spraying attribute, it can be determined that the job type is spraying.
  • the set attribute is aerial photography
  • the operation type is aerial photography.
  • the corresponding relationship can be preset according to actual conditions. Specifically, the smoothing parameter component corresponding to the type of the work object can be searched from the first correspondence, and the smoothing parameter component corresponding to the type of the work object can be searched from the second correspondence.
  • Sub-step (4) generating the smoothness adjustment parameter according to the smoothing parameter component.
  • the smoothing parameter component when only one smoothing parameter component is included, the smoothing parameter component may be determined as a smoothness adjustment parameter; when at least two smoothing parameter components are included, the smoothing parameter component may be determined based on at least two smoothing parameters.
  • the parameter component determines the smoothness adjustment parameter. For example, calculating the mean value or weighted sum of at least two smoothing parameter components to obtain the smoothing adjustment parameter.
  • the topography of the work area, the status information of the work object and the type of work will affect the execution process of the work task.
  • the smoothing parameter component is first determined according to the topography of the work area, the state information of the work object, and the work type, and the smoothness adjustment parameter is generated according to the smoothing parameter component, which can ensure the determined smoothing adjustment parameter to a certain extent. Can be more adapted to work tasks.
  • the smoothness adjustment parameter may also be generated according to the detected smoothness adjustment operation and the smoothness parameter component.
  • a first smoothing adjustment parameter may be generated according to a smoothness adjustment operation
  • a second smoothing adjustment parameter may be generated according to the smoothing parameter component, and according to a preset weight, the first smoothing adjustment parameter, and the second smoothing adjustment Parameter to calculate the smoothness adjustment parameter.
  • the smoothness value input by the user through the smoothness adjustment operation may be determined as the first smoothness adjustment parameter.
  • the second smoothing adjustment parameter is generated according to the smoothing parameter component
  • the mean value of the smoothing parameter component may be determined as the second smoothing adjustment parameter.
  • the smoothness adjustment parameter is generated by combining the smoothness adjustment operation and the smoothing parameter component, so that the smoothness adjustment parameter can simultaneously adapt to user needs and job tasks, thereby improving the effect of subsequent smoothing processing based on the smoothness adjustment parameter.
  • the smoothness adjustment parameter may include the route sampling distance
  • the step of smoothing the initial route according to the smoothing adjustment parameter to obtain the target route may include sub-step (5):
  • Sub-step (5) sampling the initial route according to the route sampling distance to obtain multiple waypoints in the initial route, wherein the target route includes adjacent ones of the multiple waypoints The flight route obtained by connecting the waypoints.
  • the route sampling distance may be used to indicate the distance between each waypoint when the waypoint sampling is performed.
  • the route sampling distance can also be called the altitude sampling distance.
  • the larger the route sampling distance the larger the distance between the sampled waypoints, and accordingly, the smoother the flight route obtained by connecting these waypoints.
  • the smaller the route sampling distance the smaller the distance between the sampled waypoints.
  • the flight route obtained by connecting these waypoints will follow the terrain more accurately.
  • the flight route obtained by connecting these waypoints will be more accurate.
  • FIG. 4 is a schematic diagram of a route provided by an embodiment of the present application
  • FIG. 5 is a schematic diagram of another route provided by an embodiment of the present application.
  • the solid line represents the flight route obtained by connecting adjacent waypoints among the multiple waypoints
  • the thick dashed line is used to represent the smoothness of the route
  • the thin dashed line is used to represent the position of the sampled waypoint.
  • the sampling distance of the route in Fig. 4 is greater than the sampling distance of the route in Fig. 5. It can be seen that the smoothness of the route in Fig. 4 is different from the smoothness of the route in Fig. 5.
  • the route in Figure 5 is more rugged and less smooth, and the route in Figure 4 is smoother.
  • the route in the actual application scene is generally a three-dimensional route, and for convenience, the shape of the route projected on the plane is shown in the schematic diagram. For example, it can show the form projected onto a vertical plane, so that it is convenient to show the ups and downs of the three-dimensional route.
  • the smoothness adjustment parameters in the embodiments of the present application are determined according to the terrain, status information, job type, and the user's smoothness adjustment operation, they are more adapted to the current job task and/or user needs, so that they are adjusted according to the smoothness
  • the sampling distance of the route included in the parameters, sampling the waypoints of the target route from the initial route can make the smoothness of the target route more suitable for the current operation tasks and/or user needs, thereby improving the follow-up The operating efficiency of the target route to perform the task.
  • the route sampling distance can be obtained through the following sub-steps (6) to (7):
  • Sub-step (6) Obtain sampling distance adjustment parameters, where the sampling distance adjustment parameters are based on the topography of the work area, the status information of the work object in the work area, and the work task performed on the work object One or more of the job type and the user’s smoothness adjustment operation.
  • the sampling distance adjustment parameter may be a parameter used to determine the sampling distance of the route.
  • the smoothness value input by the user through the smoothness adjustment operation can be determined as the sampling distance adjustment parameter, or it can be based on the topography of the work area, the status information of the work object in the work area, and the work performed on the work object.
  • the average value of the smoothing parameter component determined by the job type of the task is determined as the sampling distance adjustment parameter.
  • Sub-step (7) Determine the route sampling distance according to the sampling distance adjustment parameter.
  • the product of the sampling distance adjustment parameter and the first preset coefficient may be obtained first, and then the sum of the product and the second preset coefficient is determined as the route sampling distance.
  • the first preset coefficient and the second preset may be preset according to actual conditions.
  • the route sampling distance can be expressed as:
  • ⁇ represents the route sampling distance
  • ⁇ represents the sampling distance adjustment parameter
  • the first preset coefficient is 4.0
  • the second preset coefficient is 2.0.
  • the sampling distance adjustment parameter is obtained according to one or more of the topography of the work area, the status information of the work object, the job type of the work task, and the smoothness adjustment operation of the user, so that the sampling distance adjustment parameter can be expressed
  • the characteristics of user requirements and/or work tasks in this way, it can be ensured that a route sampling distance suitable for user requirements and/or work tasks is determined according to the sampling distance adjustment parameter.
  • the smoothness adjustment parameter may include a fitting accuracy parameter
  • the step of smoothing the initial route according to the smoothness adjustment parameter to obtain the target route may include sub-steps ( 8) ⁇ Substep (9):
  • Sub-step (8) Acquire multiple waypoints of the initial route.
  • the smoothness adjustment parameter may also include the route sampling distance.
  • the sampling distance of the route can be obtained, and the initial route is sampled according to the sampling distance of the route to obtain multiple waypoints of the initial route.
  • Sub-step (9) According to the fitting accuracy parameter, a fitting algorithm is executed on the multiple waypoints to obtain the target route corresponding to the multiple waypoints.
  • the fitting accuracy parameter can be used to limit the maximum vertical distance between the waypoint and the target route.
  • FIG. 6 is a schematic diagram of a route fitting provided by an embodiment of the present application
  • FIG. 7 is another schematic diagram of a route fitting provided by an embodiment of the present application.
  • line c represents the target route obtained by fitting.
  • the fitting accuracy parameter in Fig. 6 is greater than the fitting accuracy parameter in Fig. 7. It can be seen that the target route in Fig. 6 has lower accuracy and higher smoothness. , The target course in Figure 7 is more rugged, with higher accuracy and lower smoothness.
  • the fitting accuracy parameter may be generated according to one or more of the topography of the work area, the status information of the work object in the work area, the type of work task performed on the work object, and the smoothness adjustment operation of the user. of.
  • the fitting accuracy parameter can be adapted to the user's needs and/or the operation task, thereby ensuring that the target route that meets the user's needs and/or the operation task can be fitted according to the fitting accuracy parameter.
  • the smoothness value input by the user through the smoothness adjustment operation can be used as the obtaining fitting accuracy parameters.
  • the user can control the fitting accuracy parameters by controlling the slider control, and then control the route.
  • the smoothness Alternatively, the mean value of the smoothing parameter component may also be determined as the obtaining fitting accuracy parameter, which is not limited in the embodiment of the present application.
  • the fitting algorithm can be selected according to actual needs.
  • the fitting algorithm may be a least squares fitting algorithm.
  • the waypoints can be used as the input of the least squares fitting algorithm, and the waypoints are fitted according to the least squares fitting algorithm so that all the waypoints are in the pipeline with the fitting accuracy parameter as the radius, so as to ensure that the waypoints and The maximum vertical distance between target routes does not exceed the fitting accuracy parameter. Since the least squares fitting algorithm can fit the line with the smallest sum of squares of the distance from the known data according to the known point set, the least squares fitting algorithm is used to fit the target route, which can make the target route The deviation is smaller, thereby improving the accuracy of the fitted target route.
  • a fixed collinear threshold is often used as a smoothing adjustment parameter. Then filter the waypoints according to the collinear threshold. As an example, if the collinear threshold is 0.2 meters, one of the adjacent waypoints with a distance greater than 0.2 meters can be deleted to achieve filtering. Finally, the route formed by connecting the remaining waypoints after filtering is used as the target route. Because the waypoints are deleted, the accuracy of the final target route is often lower.
  • the target route is obtained by fitting all the sampled waypoints, so that the target route can take into account more waypoints, thereby improving the accuracy of the target route to a certain extent.
  • the initial route may include an operating route and a non-operating route, where the operating route is the route on which the operating equipment carried on the unmanned aerial vehicle is in working condition, and the operating route is not operating.
  • a route is a route in which the operating equipment carried on the unmanned aerial vehicle is in a non-working state and no operations are carried out.
  • FIG. 8 is a schematic diagram of an initial route provided by an embodiment of the present application, in which the solid line part represents the operating route, and the dashed line represents the non-operating route.
  • the steps of smoothing the initial route according to the smoothness adjustment parameter to obtain the target route may include:
  • Sub-step (10) smoothing the operation route according to the smoothness adjustment parameter to obtain a target operation route.
  • the operation route may be smoothed only according to the smoothness adjustment parameter, so as to ensure the operation accuracy and efficiency of the operation when the operation is performed on the operation route.
  • the smoothness adjustment parameter for non-operating routes, since there is no need for operations, it is possible to improve the smoothness of the non-operating routes as much as possible while ensuring flight safety, regardless of operating accuracy, so as to facilitate the control of unmanned aerial vehicles.
  • processing of non-operating routes may also be implemented according to the following sub-steps:
  • Sub-step (11) Obtain multiple waypoints on the non-operating route, where the multiple waypoints include the starting waypoint, the ending waypoint and the starting waypoint on the flight route , Intermediate waypoint between terminating waypoints.
  • the points at both ends of the non-operating route can be sampled to obtain the starting waypoint and the ending waypoint. Then sample the waypoints from the non-operating route between the starting waypoint and the ending waypoint to obtain the intermediate waypoint.
  • Sub-step (12) Determine the altitude of the intermediate waypoint as the target altitude, wherein the altitude of the intermediate waypoint is not less than the altitude of the intermediate waypoint on the initial route.
  • the height of the intermediate waypoint is determined as the target height, and the height of the intermediate waypoint can be increased to a certain extent, thereby realizing the convexity of the non-operating route and improving the smoothness of the non-operating segment.
  • the waypoint with the highest altitude among the multiple waypoints may be determined; the reference altitude of the intermediate waypoint is determined according to the altitude of the waypoint with the largest altitude ; Determine the target height of the intermediate waypoint by the larger value of the reference altitude and the altitude of the intermediate waypoint on the initial route.
  • the intermediate waypoint can be compared with the altitude of the initial route, and the waypoint with the highest altitude can be selected according to the comparison result.
  • the step of determining the reference altitude of the intermediate waypoint according to the altitude of the waypoint with the highest altitude may include:
  • Sub-step A When the intermediate waypoint is located between the starting waypoint and the waypoint with the largest altitude, according to the altitude of the starting waypoint on the initial route and the waypoint with the largest altitude The altitude of and the relative position parameter between the intermediate waypoint and the starting waypoint determine the reference altitude of the intermediate waypoint.
  • the relative position parameter may indicate the shortest straight-line distance between the intermediate waypoint and the starting waypoint
  • the relative position parameter between the intermediate waypoint and the starting waypoint may be between the first distance and the second distance
  • the first distance is the distance between the starting waypoint and the intermediate waypoint
  • the second distance is the distance between the starting waypoint and the waypoint with the highest altitude
  • the distance between the waypoints can be the distance between the waypoints.
  • the degree of the route between the points can also be the projection length of the route between the waypoints on the vertical plane.
  • the relative position parameter can be expressed as l_ax/l_am.
  • the reference height can be expressed as:
  • target height of the intermediate waypoint can be expressed as:
  • hx’ max(hx,(hm-ha)(l_ax/l_am)+ha)
  • Sub-step B When the intermediate waypoint is located between the ending waypoint and the waypoint with the largest altitude, according to the altitude of the ending waypoint on the initial route and the altitude of the waypoint with the largest altitude And the relative position parameter between the intermediate waypoint and the end waypoint to determine the reference altitude of the intermediate waypoint.
  • the relative position parameter between the intermediate waypoint and the ending waypoint may represent the shortest straight line distance between the intermediate waypoint and the ending waypoint
  • the relative position parameter between the intermediate waypoint and the ending waypoint may be the first The ratio between the third distance and the fourth distance, where the third distance can be the distance between the waypoint with the highest altitude and the intermediate waypoint, and the fourth distance is the distance between the waypoint with the highest altitude and the end waypoint.
  • the reference height can be expressed as:
  • target height of the intermediate waypoint can be expressed as:
  • hx’ max(hx,(hm-hb)(l_mx/l_mb)+hm)
  • Sub-step (13) Determine the starting waypoint, ending waypoint, and altitude as the target non-operating route.
  • the target non-operating route and the target operating route obtained in the foregoing steps may constitute the target route.
  • the reference altitude of the intermediate waypoint is determined according to the relative position parameter, and when the reference altitude is not less than the altitude of the intermediate waypoint in the initial route , Adjust the height of the intermediate waypoint to the reference altitude, and then achieve the height of the intermediate waypoint as much as possible within a safe range.
  • FIG. 9 is a schematic diagram of processing a non-operation route provided by an embodiment of the present application. As shown in FIG. 9, the line x represents the actual terrain undulation.
  • Line y represents the non-operating route corresponding to line x
  • line z represents the target non-operating route obtained after processing
  • the points between line y and line z are used to represent the waypoints on the non-operating route, and these points are actually located on line y , To facilitate viewing, these points are separated and expressed. It can be seen that the line z is smoother, so that it is more energy-efficient when flying according to the line z, and the control is easier to achieve.
  • the unmanned aerial vehicle Due to the poor smoothness of the route, repeated fluctuations of the route will cause the UAV to frequently adjust its flight attitude. Therefore, by acquiring the target non-operating route in the embodiments of the present application, the unmanned aerial vehicle will not perform unnecessary adjustments of the flight attitude when flying according to the target non-operating route, thereby avoiding the ineffective loss of the unmanned aerial vehicle’s power and improving Operational efficiency of unmanned aerial vehicles.
  • FIG. 10 is a block diagram of a route smoothing device for an unmanned aerial vehicle provided by an embodiment of the present application. As shown in FIG. 10, the device may include a memory 201 and a processor 202.
  • the memory 201 is used to store program codes.
  • the processor 202 calls the program code, and when the program code is executed, is used to perform the following operations: obtain the initial route of the unmanned aerial vehicle in the operation area. Acquire smoothness adjustment parameters, where the smoothness adjustment parameters are based on the topography of the work area, the status information of the work object in the work area, the type of work performed on the work object, and the user’s One or more of the smoothness adjustment operations are determined. Perform smoothing processing on the initial route according to the smoothness adjustment parameter to obtain a target route. Control the unmanned aerial vehicle to perform the operation task on the operation object in the operation area according to the target route.
  • the status information of the work objects in the work area includes at least one of the following: the density of work objects in the work area, the type of work objects in the work area, and the location of the work objects in the work area. Coverage in the work area.
  • the status information of the work object in the work area is determined according to the three-dimensional model information of the work area.
  • the processor 202 is specifically configured to: detect the smoothness adjustment operation of the user. According to the detected smoothness adjustment operation, the smoothness adjustment parameter is generated.
  • the processor 202 is further configured to: display a smoothness setting interface on the interactive device. For example, the processor 202 may control the display module of the interactive device to display the smoothness setting interface.
  • the processor 202 is specifically configured to: detect a smoothness setting operation performed by a user on the smoothness setting interface.
  • the smoothness adjustment parameter includes a route sampling distance
  • the processor 202 is specifically configured to: sample the initial route according to the route sampling distance to obtain multiple routes in the initial route. Point, wherein the target route includes a flight route obtained by connecting adjacent waypoints among the multiple waypoints.
  • the processor 202 is specifically configured to: obtain a sampling distance adjustment parameter, where the sampling distance adjustment parameter is based on the topography of the work area, the status information of the work object in the work area, and the It is generated by one or more of the job type of the job task performed by the job object and the smoothness adjustment operation of the user. Determine the route sampling distance according to the sampling distance adjustment parameter.
  • the processor 202 is specifically configured to: obtain the product of the sampling distance adjustment parameter and the first preset coefficient. The sum of the product and the second preset coefficient is determined as the route sampling distance.
  • the smoothness adjustment parameter includes a fitting accuracy parameter.
  • the processor 202 is specifically configured to obtain multiple waypoints of the initial route. According to the fitting accuracy parameter, a fitting algorithm is executed on the multiple waypoints to obtain the target route corresponding to the multiple waypoints.
  • the processor 202 is specifically configured to: obtain a route sampling distance, and sample the initial route according to the route sampling distance to obtain multiple waypoints of the initial route.
  • the fitting accuracy parameter is used to limit the maximum vertical distance between the waypoint and the target route.
  • the fitting algorithm is a least squares fitting algorithm.
  • the initial route includes an operating route and a non-operating route.
  • the processor 202 is specifically configured to: perform smoothing processing on the operation route according to the smoothness adjustment parameter to obtain a target operation route.
  • the processor 202 is further configured to obtain multiple waypoints on the non-operating route, where the multiple waypoints include the starting waypoint, the ending waypoint, and the starting waypoint on the flight route.
  • the altitude of the intermediate waypoint is determined as the target altitude, wherein the altitude of the intermediate waypoint is not less than the altitude of the intermediate waypoint on the initial route.
  • the flight route obtained by connecting the adjacent waypoints among the multiple intermediate waypoints whose starting waypoint, ending waypoint and altitude are determined as the target altitude is determined as the target non-operational route.
  • the processor 202 is specifically configured to determine the waypoint with the largest height among the multiple waypoints.
  • the reference altitude of the intermediate waypoint is determined according to the altitude of the waypoint with the highest altitude.
  • the target altitude of the intermediate waypoint is determined by the larger value of the reference altitude and the altitude of the intermediate waypoint on the initial route.
  • the processor 202 is specifically configured to:
  • the altitude of the starting waypoint on the initial route, the altitude of the waypoint with the largest altitude, and the The relative position parameter between the intermediate waypoint and the starting waypoint determines the reference altitude of the intermediate waypoint.
  • the altitude of the ending waypoint on the initial route the altitude of the waypoint with the largest altitude and the intermediate
  • the relative position parameter between the waypoint and the ending waypoint determines the reference altitude of the intermediate waypoint.
  • an embodiment of the present application also provides a control terminal, the control terminal includes the above-mentioned unmanned aerial vehicle's route smoothing processing device; the unmanned aerial vehicle's route smoothing processing device is used to perform each step in the route smoothing processing method , And can achieve the same technical effect, in order to avoid repetition, I will not repeat it here.
  • an embodiment of the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the method for smoothing the flight path of the above-mentioned unmanned aerial vehicle.
  • a processor executes the method for smoothing the flight path of the above-mentioned unmanned aerial vehicle.
  • the device embodiments described above are merely illustrative, where the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • the various component embodiments of the present application may be implemented by hardware, or by software modules running on one or more processors, or by a combination of them.
  • a microprocessor or a digital signal processor may be used in practice to implement some or all of the functions of some or all of the components in the computing processing device according to the embodiments of the present application.
  • This application can also be implemented as a device or device program (for example, a computer program and a computer program product) for executing part or all of the methods described herein.
  • Such a program for implementing the present application may be stored on a computer-readable medium, or may have the form of one or more signals.
  • FIG. 11 is a block diagram of a computing processing device provided by an embodiment of this application. As shown in FIG. 11, FIG. 11 shows a computing processing device that can implement the method according to this application.
  • the computing processing device traditionally includes a processor 310 and a computer program product in the form of a memory 320 or a computer readable medium.
  • the memory 320 may be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, hard disk, or ROM.
  • the memory 320 has a storage space 330 for executing program codes of any method steps in the above methods.
  • the storage space 330 for program codes may include various program codes respectively used to implement various steps in the above method.
  • These program codes can be read from or written into one or more computer program products.
  • These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks.
  • Such a computer program product is usually a portable or fixed storage unit as described with reference to FIG. 12.
  • the storage unit may have storage segments, storage spaces, etc., arranged similarly to the memory 320 in the computing processing device of FIG. 11.
  • the program code can be compressed in a suitable form, for example.
  • the storage unit includes computer-readable codes, that is, codes that can be read by, for example, a processor such as 310, which, when run by a computing processing device, causes the computing processing device to perform each of the methods described above. step.
  • a processor such as 310
  • the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same or similar parts between the various embodiments can be referred to each other.
  • the “one embodiment”, “an embodiment” or “one or more embodiments” referred to herein means that a specific feature, structure, or characteristic described in combination with the embodiment is included in at least one embodiment of the present application.
  • the word examples "in one embodiment” here do not necessarily all refer to the same embodiment.

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Abstract

一种无人飞行器（10）的航线平滑处理方法、装置及控制终端（30），航线平滑处理方法可以获取无人飞行器（10）在作业区域的初始航线（101），获取平滑度调整参数；平滑度调整参数是根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户（20）的平滑度调整操作中的一种或多种确定的（102），根据平滑度调整参数，对初始航线进行平滑处理以得到目标航线（103），根据目标航线控制无人飞行器（10）对作业区域中的作业对象执行作业任务（104）。相较于直接使用预先配置的固定平滑调整参数，可以适应无人飞行器（10）在各种不同情况对航线的平滑度的不同要求。

Description

无人飞行器的航线平滑处理方法、装置及控制终端 技术领域
本发明属于飞行技术领域，特别是涉及一种无人飞行器的航线平滑处理方法、装置及控制终端。
背景技术
目前，无人飞行器的应用越来越广泛，例如，用户经常会使用无人飞行器执行航拍、农业植保、勘测等各种各样的作业任务。在利用无人飞行器执行作业任务时，为了确保无人飞行器基于航线执行作业任务时的效率，会对规划得到的作业区域的初始航线进行平滑处理以获取目标航线，再根据所述目标航线控制无人飞行器对作业区域中的作业对象进行作业。
现有技术中，在进行平滑处理时，通常是直接读取预先配置的固定平滑调整参数，基于该平滑调整参数进行平滑处理。这样，会使得不同情况中的目标航线的平滑度都是相同的，其中，平滑度用于表征目标航线与初始航线之间的差异或者目标航线跟随初始航线的精准程度。然而，无人飞行器可能在不同的作业场景(例如山地、丘陵或者平原)中根据规划好的航线来对作业区域中的不同类型的作业对象(例如果树、稻谷或者建筑)进行不同的作业任务(例如喷洒或拍摄)。不同情况(不同的作业场景、不同类型的作业任务和不同类型的作业对象)对平滑度的要求各不相同，现有技术中的方案不能适应各种不同情况对平滑度的不同要求。
发明内容
本发明提供一种无人飞行器的航线平滑处理方法、装置及控制终端，以适应无人飞行器在各种不同情况对航线的平滑度的不同要求。
为了解决上述技术问题，本发明是这样实现的：
第一方面，本发明实施例提供了一种无人飞行器的航线平滑处理方法，该方法包括：
获取无人飞行器在作业区域的初始航线；
获取平滑度调整参数，其中，所述平滑度调整参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的；
根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线；
根据所述目标航线控制所述无人飞行器对所述作业区域中的作业对象执行所述作业任务。
第二方面，本发明实施例提供了一种无人飞行器的航线平滑处理装置，所述装置包括：存储器和处理器，
所述存储器，用于存储程序代码；
所述处理器，调用所述程序代码，当所述程序代码被执行时，用于执行以下操作：
获取无人飞行器在作业区域的初始航线；
获取平滑度调整参数，其中，所述平滑度调整参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的；
根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线；
根据所述目标航线控制所述无人飞行器对所述作业区域中的作业对象执行所述作业任务。
第三方面，本发明实施例提供了一种控制终端，所述控制终端包括：上述无人飞行器的航线平滑处理装置。
第四方面，本发明实施例提供了一种计算机可读存储介质，所述计算机可读存储介质上存储计算机程序，所述计算机程序被处理器执行时实现上述无人飞行器的航线平滑处理方法。
在本申请实施例中，可以获取无人飞行器在作业区域的初始航线，获取平滑度调整参数；其中，平滑度调整参数是根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的，然后，根据平滑度调整参数，对初始航线进行平滑处理以得到目标航线，最后，根据目标航线控制无人飞行器对作业区域中的作业对象执行作业任务。相较于直接使用预先配置的固定平滑调整参数，根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定平滑调整参数，使得平滑调整参数可以更加适配当前的作业任务和/或用户需求，这样，适应无人飞行器在各种不同情况对航线的平滑度的不同要求。
附图说明
图1是本申请实施例提供的一种无人飞行器的航线平滑处理方法的应用场景示意图；
图2是本申请实施例提供的一种无人飞行器的航线平滑处理方法的步骤流程图；
图3是本申请实施例提供的一种平滑度设置界面的示意图；
图4是本申请实施例提供的一种航线示意图；
图5是本申请实施例提供的另一种航线示意图；
图6是本申请实施例提供的一种航线拟合示意图；
图7是本申请实施例提供的另一种航线拟合示意图；
图8是本申请实施例提供的一种初始航线示意图；
图9是本申请实施例提供的一种非作业航线的处理示意图；
图10是本申请实施例提供的一种无人飞行器的航线平滑处理装置的框图；
图11为本申请实施例提供的一种计算处理设备的框图；
图12为本申请实施例提供的一种便携式或者固定存储单元的框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述， 显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
为了便于理解本申请，下面先对本申请实施例涉及的场景进行说明。图1是本申请实施例提供的一种无人飞行器的航线平滑处理方法的应用场景示意图。该应用场景中可以包括：无人飞行器10、用户20、控制终端30及农田所在区域40。用户20在利用无人飞行器10为农田所在区域40执行喷洒农药的作业任务时，可以先针对作业任务规划初始航线。其中，初始航线可以表征农田所在区域40中的作业对象可以被覆盖的飞行路径。用户20使用控制终端30，控制无人飞行器10根据该初始航线进行飞行及喷洒，可以实现对农田所在区域40中的作业对象喷洒农药。
进一步地，由于航线的平滑度会影响无人飞行器的在飞行中的姿态调整，例如，对平滑度要求较高时，即要求平滑度较低时，无人飞行器在按照航线执行作业任务的过程中，可能会频繁调整飞行姿态以使目标航线精准地跟随所述初始航线。因此，在得到初始航线之后，往往会对初始航线进行平滑处理。具体的，用户20可以通过控制终端30获取无人飞行器在作业区域，例如，农田所在区域40，的初始航线，然后获取平滑度调整参数，其中，该平滑度调整参数根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的，根据平滑度调整参数，对初始航线进行平滑处理以得到目标航线，最后根据该目标航线控制无人飞行器10执行作业任务。
相较于直接使用预先配置的固定平滑调整参数，该应用场景中，通过根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定平滑调整参数，使得平滑调整参数可以更加适配当前的作业场景、作业对象、作业任务和/或用户需求，这样，可以适应各种不同情况对平滑度的不同要求，一定程度上可以提高对初始航线进行平滑处理的效果，进而提高根据该目标航线执行作业任务的作业效率。
下面对该无人飞行器的航线平滑处理方法进行详细说明。
图2是本申请实施例提供的一种无人飞行器的航线平滑处理方法的步骤流程图，如图2所示，该方法可以包括：
步骤101、获取无人飞行器在作业区域的初始航线。
本申请实施例中提供的航线平滑处理方法可应用于无人飞行器的航线平滑装置。在某些情况中，该航线平滑装置可以是设置在无人飞行器上的设备。在某些情况中，所述航线平滑装置也可以能够设置在与无人飞行器无线通讯的独立设备上，例如，控制终端，即控制终端包括所述航线平滑装置。其中，所述控制终端可以是进行飞行航线规划的终端，实际应用中该终端可以为台式电脑、笔记本电脑、智能手机、可穿戴设备、遥控器中的任意一种或多种。
进一步地，作业区域可以是无人飞行器执行作业任务的区域。示例的，假设无人飞行器执行的作业任务为给农田A喷洒农药，那么农田A所在的区域可以为作业区域。
获取初始航线时，可以是直接读取之前规划好的初始航线，也可以是根据作业区域及作业任务实时规划初始航线。示例的，规划初始航线的过程可以为：先识别作业区域及作业区域中的作业对象，以获得识别结果。然后，根据作业区域和作业对象识别结果，生成往返式覆盖路径，接着，根据作业区域中的障碍物信息，调整往返式覆盖路径，以对障碍物进行避障。删除路径中共线、前后距离较近的路径点、起伏较大的路径点，进而得到初始航线。需要说明的是，实际应用场景中，还可以根据用户设置，对路径进行路径插值、路径点高度值采样，以设置作业任务的属性，例如，设置喷洒属性。本申请实施例对此不作限定。
步骤102、获取平滑度调整参数，其中，所述平滑度调整参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的。
本申请实施例中，可以先确定作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种，然后根据其中的一种或多种确定平滑度调整参数。这样，相较于直接读取预设设置的固定滑度调整参数，一定程度上可以使确定的平滑度调整参数更加适配当前当前任务情况和/或用户需求。
步骤103、根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线。
本申请实施例中，平滑度调整参数可以决定对初始航线进行平滑处理后得到的目标航线的平滑度。根据不同的平滑度调整参数，对同一初始航线进行平滑处理后得到的目标航线的平滑度可以不同。由于本申请实施例中的平滑度调整参数，是根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种，因此，根据该平滑度调整参数，得到的目标航线的平滑度一定程度上可以更加适配当前任务情况和/或用户需求。
步骤104、根据所述目标航线控制所述无人飞行器对所述作业区域中的作业对象执行所述作业任务。
本申请实施例中，可以控制无人飞行器按照目标航线进行飞行，以实现对作业区域中的作业对象执行所述作业任务。在使用固定的平滑度调整参数进行平滑处理的方式中，相对于需要执行的作业任务或用户实际需求而言，得到的目标航线的平滑度可能较低，仿地精度过高，这样，就会出现航线反复起伏，进而会造成无人飞行器电量的无效损失，降低无人飞行器的作业效率。同时，导致无人飞行器在山坡等地形起伏较大的场景，极易发出避障刹停等操作，进而导致无人飞行器的稳定性较差。又或者，相对于需要执行的作业任务或用户实际需求而言，得到的目标航线的平滑度可能较高，这样，就会出现航线过于平滑，仿地精度过低，进而导致作业效果较差，无法全面的覆盖作业对象。本申请实施例中，通过获取更加适配当前任务情况和/ 或用户需求的平滑度调整参数，一定程度上可以使得根据该平滑度调整参数得到的目标航线的平滑度能够更加适配当前实际情况，进而确保后续无人飞行器根据目标航线进行作业的作业效率以及无人飞行器的稳定性。这样，适应无人飞行器在各种不同情况对航线的平滑度的不同要求。
综上所述，本申请实施例提供的无人飞行器的航线平滑处理方法，可以获取无人飞行器在作业区域的初始航线，获取平滑度调整参数；其中，平滑度调整参数是根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的，然后，根据平滑度调整参数，对初始航线进行平滑处理以得到目标航线，最后，根据目标航线控制无人飞行器对作业区域中的作业对象执行作业任务。相较于直接使用预先配置的固定平滑调整参数，根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定平滑调整参数，使得平滑调整参数可以更加适配当前的作业任务和/或用户需求，适应无人飞行器在各种不同情况对航线的平滑度的不同要求。
可选的，在本申请实施例的一种实现方式中，获取平滑度调整参数的操作可以包括子步骤(1)～子步骤(2)：
子步骤(1)：检测用户的平滑度调整操作。
本申请实施例中，平滑度调整操作可以是用户根据实际需求设定平滑度的操作。实际应用场景中，针对同一作业区域，航线的仿地精度越高，航线的平滑度会越低。航线的仿地精度越低，航线的平滑度会越高。而不同用户对于精度的要求可能不同，即，不同用户对平滑度的需求可能不同。因此，本申请实施例中，可以在获取平滑度调整参数时，可以先检测用户的平滑度调整操作，以了解用户的真实需求。
可选的，本申请实施例可以在检测平滑度调整操作之前，在交互装置上显示平滑度设置界面。相应地，检测用户的平滑度调整操作可以为：检测用户对平滑度设置界面的平滑度设置操作。
其中，交互装置可以是用于和用户进行交互的装置，该交互装置可以设置在控制终端上，即控制终端可以包括交互装置。平滑度设置界面可以是用于设置平滑度的界面。示例的，该平滑度设置界面可以显示有用于设置平滑度的控件，平滑度设置操作可以为用户可以对该控件执行的设置操作。
实际应用场景中，不同用户对于不同的作业场景，对航线规划的需求往往不同。例如，在平坦的稻田里面，由于稻田大多是高度一致的平坦的地面，这种情况下用户往往需要航线具有较高的平滑度，从而尽可能提高无人飞行器的作业效率。在山区的果树喷洒作业场景下，由于不同果树区域的高度不同，为了保持相同的喷洒高度，无人飞行器需要反复起伏上升，准确的跟随地形的起伏规划航线。这种情况下，用户往往需要航线具有较低的平滑度、较高的仿地精 度。同时，对于不同果树，用户对于起伏的误差容忍度不同，即，对仿地精度的具体要求也不相同。例如预设喷洒高度3m，某些场景下实际喷洒高度在2.5～3.5m之间用户才能接受，而有些场景下实际喷洒高度在2.0～4.0m之间用户即可接受。这样，如果使用固定的平滑度调整参数就无法满足用户多样化的需求。因此，本申请实施例中，通过显示平滑度设置界面，使得用户可以便捷的根据真实需求设置平滑度，进而可以生成能够满足用户在不同作业场景下不同作业需求的航线。同时，用户通过平滑度设置界面即可完成设置，一定程度上可以提高用户操作效率。
示例的，图3是本申请实施例提供的一种平滑度设置界面的示意图，如图3所示，该平滑度设置界面中包括用于设置平滑度的滑条控件05，用户执行的平滑度设置操作可以为对滑条控件05中的选项051的拖动操作，或者是对滑条控件05中的选项052或053的点击操作，对滑条控件05中的选项054的输入操作。
子步骤(2)：根据检测到的所述平滑度调整操作，生成所述平滑度调整参数。
本申请实施例中，可以先获取检测到的平滑度调整操作对应的平滑度值，例如，获取用户拖动选项051之后，滑条控件05对应的平滑度值0.5。然后根据平滑度值生成平滑度调整参数。由于平滑度设置操作往往是用户根据实际需求执行的，这样，通过检测用户的平滑度设置操作，根据平滑度设置操作生成平滑度调整参数，使得平滑度调整参数可以适配用户需求，进而提高后续基于该平滑度调整参数进行平滑处理得到的目标航线。
可选的，在本申请实施例的另一种实现方式中，获取平滑度调整参数的操作可以包括如下子步骤(3)～子步骤(4)：
子步骤(3)：分别确定所述作业区域的地形、所述作业区域中的作业对象的状态信息及对所述作业对象执行的作业任务的作业类型对应的平滑参数分量。
可选的，作业区域中的作业对象的状态信息可以包括以下至少一种：作业区域中的作业对象的密集程度、作业区域中作业对象的类型和作业对象在作业区域中的覆盖率。作业区域中作业对象的状态信息可以是根据作业区域的三维模型信息确定的。
其中，作业对象的密集程度用于表示作业区域中作业对象之间的间距。作业对象之间的间距越大，密集程度越低。作业对象之间的间距越小，密集程度越大。作业对象的类型可以表示作业对象的属性，不同类型的作业对象具有不同的属性。类型可以是预先根据不同作业对象的特性划分，例如，类型可以分为草本植物、木本植物，或者，也可以分为有生命对象、无生命对象，等等。作业对象在作业区域中的覆盖率用于表示作业对象在作业区域中的占比。作业对象在作业区域中的占比越大，覆盖率越高，作业对象在作业区域中的占比越小，覆盖率越低。由于作业区域中作业对象的密集程度、类型和覆盖率会影响作业任务的执行过程，两者存在关联。例如，针对不同类型的作业对象，在作业对象的密集程度、覆盖率不同的情况下，执行喷洒任务时的喷洒过程可能不同。因此，本申请实施例中，以密集程度、类型及覆盖率作为状态信息，一定程度上可以确保后续根据这些状态信息确定的平滑调整参数可以更加适配作业任务。
进一步地，根据作业区域的三维模型信息确定状态信息时，可以先控制无人飞行器对作业区域进行信息采集，并记录下采集过程中的图像、位姿及无人飞行器搭载的相机的姿态。根据记录的信息构建三维模型信息，其中，该三维模型信息可以是任何用于表示作业区域的三维特征的信息，例如，三维点云信息、三维地图信息或者高程图信息，等等。接着，可以将三维模型信息输入神经网络模型中，根据该神经网络模型识别出作业区域中作业对象的密集程度、类型和覆盖率。由于三维模型信息可以较为精准的表示作业区域的三维特征，因此，本申请实施例中，根据三维模型信息可以更为精准的确定出状态信息，进而可以确保后续使用状态信息确定的平滑调整参数的准确性。
可选的，确定平滑参数分量时，可以按照密集程度与平滑参数分量正相关的方式，生成密集程度对应的平滑参数分量。按照覆盖率与平滑参数分量负相关的方式，生成覆盖率对应的平滑参数分量。
其中，密集程度与平滑参数分量正相关表示密集程度越大，密集程度对应的平滑参数分量越大。覆盖率与平滑参数分量负相关表示覆盖率越大，覆盖率对应的平滑参数分量越小。示例的，可以将作业区域中的作业对象的密集程度作为第一预设生成函数的输入，将该第一预设生成函数的输出作为密集程度对应的平滑参数分量。将作业对象在作业区域中的覆盖率作为第二预设生成函数的输入，将该第二预设生成函数的输出作为覆盖率对应的平滑参数分量。其中，第一预设生成函数是预先设置的自变量与因变量正相关的函数，第二预设生成函数是预先设置的自变量与因变量负相关的函数。
进一步地，可以根据作业区域的地形的起伏程度，确定作业区域的地形对应的平滑参数分量；其中，地形的起伏程度与地形对应的平滑参数分量正相关。本申请实施例中，地形的起伏程度可以是利用神经网络模型对作业区域的三维模型信息进行识别得到的。示例的，可以将作业区域的地形的起伏程度作为第三预设生成函数的输入，将该第三预设生成函数的输出作为地形对应的平滑参数分量。其中，第三预设生成函数是预先设置的自变量与因变量正相关的函数，第三预设生成函数可以与前述第一预设函数相同，也可以不同。进一步地，可以根据预设的作业对象的类型与平滑参数分量之间的第一对应关系，获取作业对象的类型的平滑参数分量。以及，根据预设的作业类型与平滑参数分量之间的第二对应关系，获取作业类型对应的平滑参数分量。本申请实施例中，作业类型可以是根据用户设置的作业任务的属性确定的。例如，用户设置的作业任务的属性为喷洒属性，则可以确定作业类型为喷洒。设置的属性为航拍属性，则可以确定作业类型为航拍。对应关系可以是根据实际情况预先设置的。具体的，可以从第一对应关系中查找该作业对象的类型对应的平滑参数分量，以及从第二对应关系中查找该作业对象的类型对应的平滑参数分量。
子步骤(4)：根据所述平滑参数分量，生成所述平滑度调整参数。
示例的，本申请实施例可以在仅包含一个平滑参数分量的情况下，将该平滑参数分量，确 定为平滑度调整参数；在包含至少两种平滑参数分量的情况下，则根据至少两种平滑参数分量，确定平滑度调整参数。例如，计算至少两种平滑参数分量的均值或加权和，获取平滑度调整参数。由于作业区域的地形、作业对象的状态信息及作业类型会影响作业任务的执行过程。因此，本申请实施例中，先根据作业区域的地形、作业对象的状态信息及作业类型确定平滑参数分量，根据平滑参数分量生成所述平滑度调整参数，一定程度上可以确保确定的平滑调整参数可以更加适配作业任务。
可选的，本申请实施例中，还可以根据检测到的所述平滑度调整操作以及平滑参数分量，生成平滑度调整参数。示例的，可以根据平滑度调整操作生成第一平滑调整参数，以及，根据所述平滑参数分量生成第二平滑调整参数，根据预设权重、所述第一平滑调整参数及所述第二平滑调整参数，计算所述平滑度调整参数。其中，根据平滑度调整操作生成第一平滑调整参数时，可以是将用户通过平滑度调整操作输入的平滑值确定为第一平滑调整参数。根据平滑参数分量生成第二平滑调整参数时，可以是将平滑参数分量的均值确定为第二平滑调整参数。这样，通过结合平滑度调整操作以及平滑参数分量，生成平滑度调整参数，使得平滑度调整参数可以同时适配用户需求及作业任务，进而提高后续根据平滑度调整参数进行平滑处理的效果。
可选的，在一种实现方式中，平滑度调整参数可以包括航线采样距离，根据平滑调整参数，对初始航线进行平滑处理，以得到目标航线的步骤可以包括子步骤(5)：
子步骤(5)：根据所述航线采样距离，对所述初始航线进行采样以获取所述初始航线中的多个航点，其中，所述目标航线包括所述多个航点中相邻的航点连接得到的飞行航线。
本申请实施例中，航线采样距离可以用于表示进行航点采样时各个航点之间的间距。对初始航线进行采样时，可以按照航线采样距离等间距依次采样初始航线上的航点，以获得多个航点。其中，航线采样距离又可以称为高度采样距离。航线采样距离越大，采样到的航点之间的间距越大，相应地，根据这些航点连接得到的飞行航线越平滑。反之，航线采样距离越小，采样到的航点之间的间距越小，相应地，根据这些航点连接得到的飞行航线跟随地形的精度越高，相应地，根据这些航点连接得到的飞行航线的平滑度越差。示例的，图4是本申请实施例提供的一种航线示意图，图5是本申请实施例提供的另一种航线示意图。其中，实线表示多个航点中相邻的航点连接得到的飞行航线，粗虚线用于表示该航线的平滑度，细虚线用于表示采样的航点的位置。图4中的航线采样距离大于图5中的航线采样距离，可以看出，图4中航线的平滑度与图5中航线的平滑度不同。图5中的航线更加崎岖，平滑度较差，图4中的航线更加平滑。需要说明的是，实际应用场景中航线一般为三维航线，为方便示意图中示出航线投影在平面上的形态。例如，可以示出投影到垂直平面上的形态，这样，可以方便展示三维航线的高低起伏程度。
相较于采用固定的航线采样距离生成目标航线的方式，例如，每次均间隔2m采样航点。由于本申请实施例中平滑度调整参数是根据地形、状态信息、作业类型、用户的平滑度调整操作 确定的，因此，更加适配当前的作业任务和/或用户需求，这样，根据平滑度调整参数中包括的航线采样距离，从初始航线中采样用于组成目标航线的航点，一定程度上可以使得目标航线的平滑度更加适配当前的作业任务和/或用户需求，进而提高后续根据该目标航线执行作业任务的作业效率。
可选的，在一种实现方式中，航线采样距离可以通过下述子步骤(6)～子步骤(7)获取：
子步骤(6)：获取采样距离调节参数，其中，所述采样距离调节参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种生成的。
本申请实施例中，采样距离调节参数可以是用于确定航线采样距离的参数。示例的，本步骤可以将用户通过平滑度调整操作输入的平滑度值确定为采样距离调节参数，或者是将根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型确定的平滑参数分量的均值确定为采样距离调节参数。
子步骤(7)：根据所述采样距离调节参数，确定所述航线采样距离。
可选的，本申请实施例中，可以先获取采样距离调节参数与第一预设系数的乘积，然后将乘积与第二预设系数之和，确定为航线采样距离。其中，第一预设系数及第二预设可以是根据实际情况预先设置的。示例的，航线采样距离可以表示为：
Δ＝2.0+θ*4.0
其中，Δ表示航线采样距离，θ表示采样距离调节参数，第一预设系数为4.0，第二预设系数为2.0。
本申请实施例中，根据作业区域的地形、作业对象的状态信息、作业任务的作业类型和用户的平滑度调整操作中的一种或多种获取采样距离调节参数，使得采样距离调节参数可以表示用户需求和/或作业任务的特征，这样，可以确保根据该采样距离调节参数确定出适配用户需求和/或作业任务的航线采样距离。
可选的，在本申请的另一种实现方式中，平滑度调整参数可以包括拟合精度参数，根据平滑度调整参数，对初始航线进行平滑处理，以得到目标航线的步骤可以包括子步骤(8)～子步骤(9)：
子步骤(8)：获取所述初始航线的多个航点。
可选的，平滑度调整参数还可以包括航线采样距离。获取航点时，可以获取航线采样距离，根据航线采样距离对初始航线进行采样，以获取初始航线的多个航点。其中，获取航线采样距离的方式以及采样的方式可以参照前述步骤中的相关描述，本申请实施例在此不作赘述。
子步骤(9)：根据所述拟合精度参数，对所述多个航点执行拟合算法以得到所述多个航点对应的所述目标航线。
可选的，拟合精度参数可以用于限定航点与目标航线之间的最大垂直距离。拟合精度参数 越大，拟合得到的目标航线越平滑。反之，拟合精度参数越小，拟合得到的目标航线的平滑度越差。示例的，图6是本申请实施例提供的一种航线拟合示意图，图7是本申请实施例提供的另一种航线拟合示意图。其中，线条c表示拟合得到的目标航线，图6中的拟合精度参数大于图7中的拟合精度参数，可以看出，图6中目标航线的仿地精度更低，平滑度更高，图7中目标航线更加崎岖，仿地精度更高，平滑度更低。
进一步地，拟合精度参数可以是根据作业区域的地形、作业区域中的作业对象的状态信息、对作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种生成的。这样，可以使得拟合精度参数可以适配用户需求和/或作业任务，进而可以确保根据该拟合精度参数拟合出满足用户需求和/或作业任务的目标航线。示例的，获取拟合精度参数时，可以将用户通过平滑度调整操作输入的平滑度值作为获取拟合精度参数，这样，用户通过控制滑块控件，即可控制拟合精度参数，进而控制航线的平滑度。或者，也可以是将平滑参数分量的均值确定为获取拟合精度参数，本申请实施例对此不作限定。
进一步地，拟合算法可以是根据实际需求选择的。可选的，拟合算法可以为最小二乘拟合算法。本申请实施例中，可以将航点作为最小二乘拟合算法的输入，根据最小二乘拟合算法拟合出使航点均处于以拟合精度参数为半径的管道内，确保航点与目标航线之间的最大垂直距离不超过拟合精度参数。由于最小二乘拟合算法可以根据已知点集拟合出与已知数据之间的距离的平方和最小的线条，因此，采用最小二乘拟合算法拟合目标航线，可以使得目标航线的偏差更小，进而提高拟合出的目标航线的准确性。
在现有的一种实现方式中，根据航点拟合目标航线时，往往是以固定的共线阈值作为平滑调整参数。然后根据共线阈值对航点进行过滤，示例的，假设共线阈值为0.2米，可以删除距离大于0.2米的相邻航点中的一个航点，以实现过滤。最后将过滤后剩余的航点连接形成的航线，作为目标航线。由于删除了航点，这样最终生成的目标航线的精度往往会较低。而本申请实施例中无需删除航点，根据采样的所有航点拟合得到目标航线，使得目标航线可以兼顾更多的航点，进而一定程度上可以提高目标航线的精度。
可选的，在本申请的又一种实现方式中，初始航线可以包括作业航线和非作业航线，其中，作业航线为无人飞行器上携带的作业设备处于工作状态，进行作业的航线，非作业航线为无人飞行器上携带的作业设备处于非工作状态，不进行作业的航线。示例的，图8是本申请实施例提供的一种初始航线示意图，其中，实线部分表示作业航线，虚线部分表示非作业航线。
相应地，根据平滑度调整参数，对初始航线进行平滑处理，以得到目标航线的步骤可以包括：
子步骤(10)：根据所述平滑度调整参数，对所述作业航线进行平滑处理，以得到目标作业航线。
具体的根据平滑度调整参数进行平滑处理的实现过程可以参照前述步骤中的相关描述，本 申请实施例在此不作赘述。
由于执行作业任务时，仅在作业航线上进行作业，无需在非作业航线上进行作业，即，非作业航线上没有地形跟随的需求。因此，本申请实施例中可以仅根据平滑度调整参数对作业航线进行平滑处理，以确保在作业航线上进行作业时的作业精度以及作业效率。对于非作业航线，由于不需要作业，因此，可以不考虑作业精度，在保证飞行安全的情况下尽可能提高非作业航线的平滑度，以方便控制无人飞行器。
可选的，本申请实施例中还可以根据下述子步骤实现对非作业航线的处理：
子步骤(11)：获取所述非作业航线上的多个航点，其中，所述多个航点中包括在所述飞行航线上的起始航点、终止航点和位于起始航点、终止航点之间的中间航点。
本申请实施例中，可以采样非作业航线两端的点，得到起始航点和终止航点。然后从起始航点与终止航点之间的非作业航线上采样航点，得到中间航点。或者，也可以是从前述步骤中采样的航点中，获取位于非作业航线两端的航点，以及位于起始航点与终止航点之间的航点，得到非作业航线上的多个航点。
子步骤(12)：将所述中间航点的高度确定为目标高度，其中，所述中间航点的高度不小于所述中间航点在所述初始航线的高度。
本申请实施例中，将中间航点的高度确定为目标高度，一定程度上可以调高中间航点的高度，进而实现将非作业航线凸化，提高非作业航段的平滑度。可选的，将中间航点的高度确定为目标高度时，可以确定所述多个航点中高度最大的航点；根据所述高度最大的航点的高度确定所述中间航点的参考高度；将所述参考高度和中间航点在所述初始航线上的高度中较大值确定所述中间航点的目标高度。
可选的，可以将中间航点在初始航线的高度进行比对，根据比对结果选择高度最大的航点。进一步地，根据高度最大的航点的高度确定中间航点的参考高度的步骤可以包括：
子步骤A、当所述中间航点位于所述起始航点和所述高度最大的航点之间时，根据所述起始航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述起始航点之间的相对位置参数确定所述中间航点的参考高度。
本申请实施例中，相对位置参数可以表示中间航点与起始航点之间最短直线距离，中间航点与起始航点之间的相对位置参数可以为第一距离与第二距离之间的比值，其中，第一距离为起始航点与中间航点之间的距离，第二距离为起始航点与高度最大的航点之间的距离，航点之间的距离可以为航点之间航线的程度，也可以为航点之间航线在垂直平面上的投影长度。
示例的，假设高度最大的航点为M，M在初始航线中的高度为hm，起始航点为A，A在初始航线中的高度为ha，起始航点A与高度最大的航点M之间的距离为l_am，起始航点A与中间航点X之间的距离为l_ax。那么相对位置参数可以表示为l_ax/l_am。进一步地，确定中间航点的参考高度时，可以先计算相对位置参数与起始航点在初始航线上的高度之间的和值，以及 计算高度最大的航点在初始航线上的高度与起始航点在初始航线上的高度之间的差值。最后计算和值与差值的乘积，得到参考高度。该参考高度可以表示为：
(hm-ha)(l_ax/l_am)+ha)
进一步地，可以中间航点的目标高度可以表示为：
hx’＝max(hx,(hm-ha)(l_ax/l_am)+ha)
子步骤B、当所述中间航点位于所述终止航点和所述高度最大的航点之间时，根据所述终止航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述终止航点之间的相对位置参数，确定所述中间航点的参考高度。
本申请实施例中，中间航点与终止航点之间的相对位置参数可以表示中间航点与终止航点之间最短直线距离，中间航点与终止航点之间的相对位置参数可以为第三距离与第四距离之间的比值，其中，第三距离可以为高度最大的航点与中间航点之间的距离，第四距离为高度最大的航点与终止航点之间的距离。
示例的，假设高度最大的航点为M，M在初始航线中的高度为hm，终止航点为B，B在初始航线中的高度为hb，高度最大的航点M与终止航点B之间的距离为l_mb，高度最大的航点M与中间航点X之间的距离为l_mx。那么参考高度可以表示为：
(hm-hb)(l_mx/l_mb)+hm)
进一步地，可以中间航点的目标高度可以表示为：
hx’＝max(hx,(hm-hb)(l_mx/l_mb)+hm)
子步骤(13)：将起始航点、终止航点和高度确定为目标高度的多个中间航点中相邻的航点连接得到的飞行航线确定为目标非作业航线。
本申请实施例中，目标非作业航线和前述步骤中得到的目标作业航线可以构成目标航线。通过计算表示中间航点与起始航点之间最短直线距离的相对位置参数，根据相对位置参数确定中间航点的参考高度，并在参考高度不小于中间航点在初始航线中高度的情况下，将中间航点的高度调整为参考高度，进而实现在安全范围内，尽可能提高中间航点的高度。进一步地，根据起始航点、终止航点和中间航点可以使得根据起始航点、终止航点和高度确定为目标高度的多个中间航点确定目标非作业航线，可以使得目标非作业航线拥有较大的平滑度。图9是本申请实施例提供的一种非作业航线的处理示意图，如图9所示，线条x表示实际地形起伏。线条y表示线条x对应的非作业航线，线条z表示处理后得到的目标非作业航线，线条y和线条z之间的点用于表示非作业航线上的航点，这些点实际位于线条y上，为方便观看，将这些点分离出来表示。可以看出，线条z的更加平滑，这样，根据线条z飞行时更节能，控制上更容易实现。
由于航线平滑度较差，航线反复的起伏时，会导致无人飞行器频繁的调整飞行姿态。因此，本申请实施例中通过获取目标非作业航线，使得无人飞行器根据目标非作业航线飞行时，不会 执行不必要的调整飞行姿态的操作，进而可以避免无人飞行器电量的无效损失，提高无人飞行器的作业效率。
图10是本申请实施例提供的一种无人飞行器的航线平滑处理装置的框图，如图10所示，该装置可以包括：存储器201和处理器202。
所述存储器201，用于存储程序代码。所述处理器202，调用所述程序代码，当所述程序代码被执行时，用于执行以下操作：获取无人飞行器在作业区域的初始航线。获取平滑度调整参数，其中，所述平滑度调整参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的。根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线。根据所述目标航线控制所述无人飞行器对所述作业区域中的作业对象执行所述作业任务。
可选的，所述作业区域中的作业对象的状态信息包括以下至少一种：所述作业区域中的作业对象的密集程度、所述作业区域中作业对象的类型和所述作业对象在所述作业区域中的覆盖率。可选的，所述作业区域中作业对象的状态信息是根据所述作业区域的三维模型信息确定的。可选的，所述处理器202，具体用于：检测用户的平滑度调整操作。根据检测到的所述平滑度调整操作，生成所述平滑度调整参数。可选的，所述处理器202还用于：在交互装置上显示平滑度设置界面。示例的，处理器202可以控制交互装置的显示模组显示平滑度设置界面。
所述处理器202，具体用于：检测用户对所述平滑度设置界面的平滑度设置操作。可选的，所述平滑度调整参数包括航线采样距离，所述处理器202，具体用于：根据所述航线采样距离，对所述初始航线进行采样以获取所述初始航线中的多个航点，其中，所述目标航线包括所述多个航点中相邻的航点连接得到的飞行航线。
可选的，所述处理器202，具体用于：获取采样距离调节参数，其中，所述采样距离调节参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种生成的。根据所述采样距离调节参数，确定所述航线采样距离。
可选的，所述处理器202，具体用于：获取所述采样距离调节参数与所述第一预设系数的乘积。将所述乘积与所述第二预设系数之和，确定为所述航线采样距离。可选的，所述平滑度调整参数包括拟合精度参数。所述处理器202，具体用于：获取所述初始航线的多个航点。根据所述拟合精度参数，对所述多个航点执行拟合算法以得到所述多个航点对应的所述目标航线。可选的，所述处理器202，具体用于：获取航线采样距离，根据所述航线采样距离对所述初始航线进行采样，以获取所述初始航线的多个航点。可选的，所述拟合精度参数用于限定所述航点与所述目标航线之间的最大垂直距离。可选的，所述拟合算法为最小二乘拟合算法。可选的，所述初始航线包括作业航线和非作业航线。所述处理器202，具体用于：根据所述平滑度调整参数，对所述作业航线进行平滑处理，以得到目标作业航线。
所述处理器202还用于：获取所述非作业航线上的多个航点，其中，所述多个航点中包括在所述飞行航线上的起始航点、终止航点和位于起始航点、终止航点之间的中间航点。将所述中间航点的高度确定为目标高度，其中，所述中间航点的高度不小于所述中间航点在所述初始航线的高度。
将起始航点、终止航点和高度确定为目标高度的多个中间航点中相邻的航点连接得到的飞行航线确定为目标非作业航线。
可选的，所述处理器202，具体用于：确定所述多个航点中高度最大的航点。
根据所述高度最大的航点的高度确定所述中间航点的参考高度。
将所述参考高度和中间航点在所述初始航线上的高度中较大值确定所述中间航点的目标高度。
可选的，所述处理器202，具体用于：
当所述中间航点位于所述起始航点和所述高度最大的航点之间时，根据所述起始航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述起始航点之间的相对位置参数，确定所述中间航点的参考高度。
当所述中间航点位于所述终止航点和所述高度最大的航点之间时，根据所述终止航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述终止航点之间的相对位置参数，确定所述中间航点的参考高度。
上述装置执行操作与上述方法中的各个对应步骤类似，且能达到相同的技术效果，为避免重复，这里不再赘述。进一步地，本申请实施例还提供一种控制终端，所述控制终端包含上述无人飞行器的航线平滑处理装置；所述无人飞行器的航线平滑处理装置用于执行航线平滑处理方法中的各个步骤，且能达到相同的技术效果，为避免重复，这里不再赘述。进一步地，本申请实施例还提供一种计算机可读存储介质，所述计算机可读存储介质上存储计算机程序，所述计算机程序被处理器执行时实现上述无人飞行器的航线平滑处理方法中的各个步骤，且能达到相同的技术效果，为避免重复，这里不再赘述。以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。本申请的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器来实现根据本申请实施例的计算处理设备中的一些或者全部部件的一些或者全部功能。本申请还可以实现为用于执行这里所描述的方法的一部分或者全部的设备或者装置程序(例如，计算机程序和计算机程序产品)。这样的实现本申请的程序可以存储在计算机可读介质上，或者可以具有一个或者多个 信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。例如，图11为本申请实施例提供的一种计算处理设备的框图，如图11所示，图11示出了可以实现根据本申请的方法的计算处理设备。该计算处理设备传统上包括处理器310和以存储器320形式的计算机程序产品或者计算机可读介质。存储器320可以是诸如闪存、EEPROM(电可擦除可编程只读存储器)、EPROM、硬盘或者ROM之类的电子存储器。存储器320具有用于执行上述方法中的任何方法步骤的程序代码的存储空间330。例如，用于程序代码的存储空间330可以包括分别用于实现上面的方法中的各种步骤的各个程序代码。这些程序代码可以从一个或者多个计算机程序产品中读出或者写入到这一个或者多个计算机程序产品中。这些计算机程序产品包括诸如硬盘，紧致盘(CD)、存储卡或者软盘之类的程序代码载体。这样的计算机程序产品通常为如参考图12所述的便携式或者固定存储单元。该存储单元可以具有与图11的计算处理设备中的存储器320类似布置的存储段、存储空间等。程序代码可以例如以适当形式进行压缩。通常，存储单元包括计算机可读代码，即可以由例如诸如310之类的处理器读取的代码，这些代码当由计算处理设备运行时，导致该计算处理设备执行上面所描述的方法中的各个步骤。本说明书中的各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似的部分互相参见即可。本文中所称的“一个实施例”、“实施例”或者“一个或者多个实施例”意味着，结合实施例描述的特定特征、结构或者特性包括在本申请的至少一个实施例中。此外，请注意，这里“在一个实施例中”的词语例子不一定全指同一个实施例。在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本申请的实施例可以在没有这些具体细节的情况下被实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。在权利要求中，不应将位于括号之间的任何参考符号构造成对权利要求的限制。单词“包含”不排除存在未列在权利要求中的元件或步骤。位于元件之前的单词“一”或“一个”不排除存在多个这样的元件。本申请可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。最后应说明的是：以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。

Claims (30)

  1. 一种无人飞行器的航线平滑处理方法，其特征在于，所述方法包括：
    获取无人飞行器在作业区域的初始航线；
    获取平滑度调整参数，其中，所述平滑度调整参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的；
    根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线；
    根据所述目标航线控制所述无人飞行器对所述作业区域中的作业对象执行所述作业任务。
  2. 根据权利要求1所述方法，其特征在于，所述作业区域中的作业对象的状态信息包括以下至少一种：所述作业区域中的作业对象的密集程度、所述作业区域中作业对象的类型和所述作业对象在所述作业区域中的覆盖率。
  3. 根据权利要求1或2所述的方法，其特征在于，所述作业区域中作业对象的状态信息是根据所述作业区域的三维模型信息确定的。
  4. 根据权利要求1-3任一项所述方法，其特征在于，所述获取平滑度调整参数，包括：
    检测用户的平滑度调整操作；
    根据检测到的所述平滑度调整操作，生成所述平滑度调整参数。
  5. 根据权利要求4所述的方法，其特征在于，所述方法还包括：
    在交互装置上显示平滑度设置界面；
    所述检测用户的平滑度调整操作，包括：
    检测用户对所述平滑度设置界面的平滑度设置操作。
  6. 根据权利要求1-5任一项所述的方法，其特征在于，所述平滑度调整参数包括航线采样距离，所述根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线，包括：
    根据所述航线采样距离，对所述初始航线进行采样以获取所述初始航线中的多个航点，其中，所述目标航线包括所述多个航点中相邻的航点连接得到的飞行航线。
  7. 根据权利要求6所述的方法，其特征在于，所述获取平滑度调整参数，包括：
    获取采样距离调节参数，其中，所述采样距离调节参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种生成的；
    根据所述采样距离调节参数，确定所述航线采样距离。
  8. 根据权利要求1-5任一项所述方法，其特征在于，所述平滑度调整参数包括拟合精度参数；
    所述根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线，包括：
    获取所述初始航线的多个航点；
    根据所述拟合精度参数，对所述多个航点执行拟合算法以得到所述多个航点对应的所述目标航线。
  9. 根据权利要求8所述方法，其特征在于，所述获取所述初始航线的多个航点，包括：
    获取航线采样距离，根据所述航线采样距离对所述初始航线进行采样，以获取所述初始航线的多个航点。
  10. 根据权利要8或9所述的方法，其特征在于，所述拟合精度参数用于限定所述航点与所述目标航线之间的最大垂直距离。
  11. 根据权利要求8至10中任一所述方法，其特征在于，所述拟合算法为最小二乘拟合算法。
  12. 根据权利要求1-11任一项所述方法，其特征在于，所述初始航线包括作业航线和非作业航线；
    所述根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线，包括：
    根据所述平滑度调整参数，对所述作业航线进行平滑处理，以得到目标作业航线；
    所述方法还包括：
    获取所述非作业航线上的多个航点，其中，所述多个航点中包括在所述飞行航线上的起始航点、终止航点和位于起始航点、终止航点之间的中间航点；
    将所述中间航点的高度确定为目标高度，其中，所述中间航点的高度不小于所述中间航点在所述初始航线的高度；
    将起始航点、终止航点和高度确定为目标高度的多个中间航点中相邻的航点连接得到的飞行航线确定为目标非作业航线。
  13. 根据权利要求12所述的方法，其特征在于，所述将所述中间航点的高度确定为目标高度，包括：
    确定所述多个航点中高度最大的航点；
    根据所述高度最大的航点的高度确定所述中间航点的参考高度；
    将所述参考高度和中间航点在所述初始航线上的高度中较大值确定所述中间航点的目标高度。
  14. 根据权利要求13所述的方法，其特征在于，所述根据所述高度最大的航点的高度确定所述中间航点的参考高度，包括：
    当所述中间航点位于所述起始航点和所述高度最大的航点之间时，根据所述起始航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述起始航点之间的相对位置参数，确定所述中间航点的参考高度；
    当所述中间航点位于所述终止航点和所述高度最大的航点之间时，根据所述终止航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述终止航点之间的相对位置 参数，确定所述中间航点的参考高度。
  15. 一种无人飞行器的航线平滑处理装置，其特征在于，所述装置包括：存储器和处理器，
    所述存储器，用于存储程序代码；
    所述处理器，调用所述程序代码，当所述程序代码被执行时，用于执行以下操作：
    获取无人飞行器在作业区域的初始航线；
    获取平滑度调整参数，其中，所述平滑度调整参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种确定的；
    根据所述平滑度调整参数，对所述初始航线进行平滑处理，以得到目标航线；
    根据所述目标航线控制所述无人飞行器对所述作业区域中的作业对象执行所述作业任务。
  16. 根据权利要求15所述装置，其特征在于，所述作业区域中的作业对象的状态信息包括以下至少一种：所述作业区域中的作业对象的密集程度、所述作业区域中作业对象的类型和所述作业对象在所述作业区域中的覆盖率。
  17. 根据权利要求15或16所述的装置，其特征在于，所述作业区域中作业对象的状态信息是根据所述作业区域的三维模型信息确定的。
  18. 根据权利要求15-17任一项所述装置，其特征在于，所述处理器，具体用于：
    检测用户的平滑度调整操作；
    根据检测到的所述平滑度调整操作，生成所述平滑度调整参数。
  19. 根据权利要求18所述的装置，其特征在于，所述处理器还用于：
    在交互装置上显示平滑度设置界面；
    所述处理器，具体用于：
    检测用户对所述平滑度设置界面的平滑度设置操作。
  20. 根据权利要求15-19任一项所述的装置，其特征在于，所述平滑度调整参数包括航线采样距离，所述处理器，具体用于：
    根据所述航线采样距离，对所述初始航线进行采样以获取所述初始航线中的多个航点，其中，所述目标航线包括所述多个航点中相邻的航点连接得到的飞行航线。
  21. 根据权利要求20所述的装置，其特征在于，所述处理器，具体用于：
    获取采样距离调节参数，其中，所述采样距离调节参数是根据所述作业区域的地形、所述作业区域中的作业对象的状态信息、对所述作业对象执行的作业任务的作业类型和用户的平滑度调整操作中的一种或多种生成的；
    根据所述采样距离调节参数，确定所述航线采样距离。
  22. 根据权利要求15-19任一项所述装置，其特征在于，所述平滑度调整参数包括拟合精度参数；
    所述处理器，具体用于：
    获取所述初始航线的多个航点；
    根据所述拟合精度参数，对所述多个航点执行拟合算法以得到所述多个航点对应的所述目标航线。
  23. 根据权利要求22所述装置，其特征在于，所述处理器，具体用于：
    获取航线采样距离，根据所述航线采样距离对所述初始航线进行采样，以获取所述初始航线的多个航点。
  24. 根据权利要22或23所述的装置，其特征在于，所述拟合精度参数用于限定所述航点与所述目标航线之间的最大垂直距离。
  25. 根据权利要求22至24中任一所述装置，其特征在于，所述拟合算法为最小二乘拟合算法。
  26. 根据权利要求15-25任一项所述装置，其特征在于，所述初始航线包括作业航线和非作业航线；
    所述处理器，具体用于：
    根据所述平滑度调整参数，对所述作业航线进行平滑处理，以得到目标作业航线；
    所述处理器还用于：
    获取所述非作业航线上的多个航点，其中，所述多个航点中包括在所述飞行航线上的起始航点、终止航点和位于起始航点、终止航点之间的中间航点；
    将所述中间航点的高度确定为目标高度，其中，所述中间航点的高度不小于所述中间航点在所述初始航线的高度；
    将起始航点、终止航点和高度确定为目标高度的多个中间航点中相邻的航点连接得到的飞行航线确定为目标非作业航线。
  27. 根据权利要求26所述的装置，其特征在于，所述处理器，具体用于：
    确定所述多个航点中高度最大的航点；
    根据所述高度最大的航点的高度确定所述中间航点的参考高度；
    将所述参考高度和中间航点在所述初始航线上的高度中较大值确定所述中间航点的目标高度。
  28. 根据权利要求27所述的装置，其特征在于，所述处理器，具体用于：
    当所述中间航点位于所述起始航点和所述高度最大的航点之间时，根据所述起始航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述起始航点之间的相对位置参数，确定所述中间航点的参考高度；
    当所述中间航点位于所述终止航点和所述高度最大的航点之间时，根据所述终止航点在初始航线上的高度、所述高度最大的航点的高度和所述中间航点与所述终止航点之间的相对位置参数，确定所述中间航点的参考高度。
  29. 一种控制终端，其特征在于，包括：权利要求15至28中任一项所述的无人飞行器的航线平滑处理装置。
  30. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上存储计算机程序，所述计算机程序被处理器执行时实现如权利要求1-14任一项所述的无人飞行器的航线平滑处理方法。
PCT/CN2020/092463 2020-05-27 2020-05-27 无人飞行器的航线平滑处理方法、装置及控制终端 WO2021237485A1 (zh)

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