WO2021217372A1

WO2021217372A1 - Control method and device for movable platform

Info

Publication number: WO2021217372A1
Application number: PCT/CN2020/087326
Authority: WO
Inventors: 许中研
Original assignee: 深圳市大疆创新科技有限公司
Priority date: 2020-04-27
Filing date: 2020-04-27
Publication date: 2021-11-04
Also published as: CN114096931A

Abstract

A control method and device for a movable platform. The method comprises: determining whether a target object is in a static state (S301); when the target object is in the static state, running a multi-view geometry algorithm according to a multi-frame image collected by a photographing apparatus so as to determine a first position of the target object, and according to the first position, controlling a movable platform to execute a working task on the target object (S302); and when the target object is in a motion state, determining a second position of the target object according to the image region size of the target object in an image collected by the photographing apparatus, and according to the second position, controlling the movable platform to execute the working task on the target object (S303). The present application improves the accuracy of determining the position of the target object in different states. Moreover, according to the foregoing positions, the movable platform is controlled to execute the working task on the target object, and thus, the execution effect of the working task is better.

Description

Control method and equipment of movable platform

Technical field

The embodiments of the present application relate to the technical field of movable platforms, and in particular, to a method and equipment for controlling a movable platform.

Background technique

After the drone selects a target, the drone can fly with reference to the target. For example, the drone can move according to a fixed trajectory relative to the target. Common scenarios are: automatic surround shooting, automatic inspection, autonomous monitoring, etc. Scenes.

Taking active surround shooting as an example, the drone needs to observe the position of the target and fly around the target according to the position of the target. The position of the observation target can be determined in the following way: the drone runs a multi-view geometric algorithm through the multi-frame images collected by the camera to determine the position of the target. However, this method is suitable when the target is at rest. If the target is in a moving state and the above method is still used, the determined position of the target is not accurate.

Summary of the invention

The embodiments of the present application provide a method and device for controlling a movable platform, which are used to accurately determine the position of a target object.

In a first aspect, an embodiment of the present application provides a method for controlling a movable platform, the movable platform includes a camera, and the method includes:

Determine whether the target object is stationary;

When the target object is in a static state, a multi-view geometric algorithm is run based on the multi-frame images collected by the shooting device to determine the first position of the target object, and the movable platform is controlled according to the first position. The target object performs work tasks;

When the target object is in a moving state, the second position of the target object is determined according to the size of the image area of the target object in the image captured by the shooting device, and the movable platform is controlled according to the second position Perform the work task on the target object.

In a second aspect, an embodiment of the present application provides a control device for a movable platform, the movable platform includes a photographing device, and the control device for the movable platform includes a memory and at least one processor;

The memory is used to store program code;

The at least one processor is configured to execute the program code for:

Determine whether the target object is stationary;

In a third aspect, an embodiment of the present application provides a movable platform that includes a camera and a control device of the movable platform described in the embodiment of the present application in the first aspect.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium with a computer program stored on the computer-readable storage medium; when the computer program is executed, the implementation of the The control method of the movable platform.

In a sixth aspect, an embodiment of the present application provides a program product, the program product includes a computer program, the computer program is stored in a readable storage medium, and at least one processor can read the A computer program, and the at least one processor executes the computer program to implement the control method of the movable platform according to the embodiment of the present application in the first aspect.

In summary, the mobile platform control method and device provided by the embodiments of the present application run a multi-view geometric algorithm according to the multi-frame images collected by the camera when the target object is in a static state to determine the first position of the target object When the target object is in a moving state, the second position of the target object is determined according to the size of the image area of the target object in the image collected by the shooting device, and the position of the target object is determined in different ways according to the different states of the target object, which improves Determine the accuracy of the location of the target object. Moreover, according to the above-mentioned position control of the movable platform to perform work tasks on the target object, the performance of the work tasks is better.

Description of the drawings

In order to more clearly describe the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description These are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work.

Fig. 1 is a schematic architecture diagram of an unmanned aerial system according to an embodiment of the present application;

Figure 2 is a schematic diagram of an application scenario provided by an embodiment of the application;

FIG. 3 is a flowchart of a method for controlling a movable platform according to an embodiment of the application;

4 is a schematic diagram of running a multi-view geometric algorithm based on multiple frames of images collected by a photographing device to determine the position of a stationary target object according to an embodiment of the application;

FIG. 5 is a schematic diagram of running a multi-view geometric algorithm to determine the position of a target object in a moving state according to a multi-frame image collected by a photographing device according to an embodiment of the application;

FIG. 6 is a schematic diagram of determining that the target object is in a static state according to an embodiment of the application;

FIG. 7 is a schematic diagram of determining that a target object is in a motion state according to an embodiment of the application;

FIG. 8 is a schematic structural diagram of a control device for a movable platform provided by an embodiment of the application;

FIG. 9 is a schematic structural diagram of a movable platform provided by an embodiment of this application;

FIG. 10 is a schematic structural diagram of a movable platform provided by another embodiment of this application.

Detailed ways

In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments It is a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of this application.

It should be noted that when a component is referred to as being "fixed to" another component, it can be directly on the other component or a centered component may also exist. When a component is considered to be "connected" to another component, it can be directly connected to the other component or there may be a centered component at the same time.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of this application. The terms used in the specification of the application herein are only for the purpose of describing specific embodiments, and are not intended to limit the application. The term "and/or" as used herein includes any and all combinations of one or more related listed items.

The embodiments of the present application provide a method and equipment for controlling a movable platform. Among them, the movable platform can be unmanned aerial vehicles, unmanned vehicles, unmanned ships, robots, handheld PTZ, etc. The following description of the mobile platform of this application uses drones as an example. It will be obvious to those skilled in the art that other types of drones can be used without restriction, and the embodiments of the present application can be applied to various types of drones. For example, the drone can be a small or large drone. In some embodiments, the drone may be a rotorcraft, for example, a multi-rotor drone propelled by multiple propulsion devices through the air, and the embodiments of the present application are not limited thereto.

Fig. 1 is a schematic architecture diagram of an unmanned aerial system according to an embodiment of the present application. In this embodiment, a rotary wing drone is taken as an example for description.

The unmanned aerial system 100 may include a drone 110, a display device 130, and a control terminal 140. Among them, the UAV 110 may include a power system 150, a flight control system 160, a frame, and a pan/tilt 120 carried on the frame. The drone 110 can wirelessly communicate with the control terminal 140 and the display device 130. Among them, the drone 110 further includes a battery (not shown in the figure), and the battery provides electrical energy for the power system 150. The UAV 110 may be an agricultural UAV or an industrial application UAV, and there is a need for cyclic operation. Correspondingly, the battery also has the need for cyclic operation.

The frame may include a fuselage and a tripod (also called a landing gear). The fuselage may include a center frame and one or more arms connected to the center frame, and the one or more arms extend radially from the center frame. The tripod is connected with the fuselage and used for supporting the UAV 110 when it is landed.

The power system 150 may include one or more electronic governors (referred to as ESCs) 151, one or more propellers 153, and one or more motors 152 corresponding to the one or more propellers 153, wherein the motors 152 are connected to Between the electronic governor 151 and the propeller 153, the motor 152 and the propeller 153 are arranged on the arm of the UAV 110; the electronic governor 151 is used to receive the driving signal generated by the flight control system 160 and provide driving according to the driving signal Current is supplied to the motor 152 to control the speed of the motor 152. The motor 152 is used to drive the propeller to rotate, thereby providing power for the flight of the drone 110, and the power enables the drone 110 to realize one or more degrees of freedom of movement. In some embodiments, the drone 110 may rotate about one or more rotation axes. For example, the aforementioned rotation axis may include a roll axis (Roll), a yaw axis (Yaw), and a pitch axis (pitch). It should be understood that the motor 152 may be a DC motor or an AC motor. In addition, the motor 152 may be a brushless motor or a brushed motor.

The flight control system 160 may include a flight controller 161 and a sensing system 162. The sensing system 162 is used to measure the attitude information of the UAV, that is, the position information and state information of the UAV 110 in space, such as three-dimensional position, three-dimensional angle, three-dimensional velocity, three-dimensional acceleration, and three-dimensional angular velocity. The sensing system 162 may include, for example, at least one of sensors such as a gyroscope, an ultrasonic sensor, an electronic compass, an inertial measurement unit (IMU), a vision sensor, a global navigation satellite system, and a barometer. For example, the global navigation satellite system may be the Global Positioning System (GPS). The flight controller 161 is used to control the flight of the drone 110, for example, it can control the flight of the drone 110 according to the attitude information measured by the sensor system 162. It should be understood that the flight controller 161 can control the drone 110 according to pre-programmed program instructions, and can also control the drone 110 by responding to one or more remote control signals from the control terminal 140.

The pan/tilt head 120 may include a motor 122. The pan/tilt is used to carry a load, and the load may be, for example, the camera 123. The flight controller 161 can control the movement of the pan/tilt 120 through the motor 122. Optionally, as another embodiment, the pan/tilt head 120 may further include a controller for controlling the movement of the pan/tilt head 120 by controlling the motor 122. It should be understood that the pan-tilt 120 may be independent of the drone 110 or a part of the drone 110. It should be understood that the motor 122 may be a DC motor or an AC motor. In addition, the motor 122 may be a brushless motor or a brushed motor. It should also be understood that the pan/tilt may be located on the top of the drone or on the bottom of the drone.

The photographing device 123 may be, for example, a device for capturing images, such as a camera or a video camera, and the photographing device 123 may communicate with the flight controller and take pictures under the control of the flight controller. The imaging device 123 of this embodiment at least includes a photosensitive element, and the photosensitive element is, for example, a Complementary Metal Oxide Semiconductor (CMOS) sensor or a Charge-coupled Device (CCD) sensor. It can be understood that the camera 123 can also be directly fixed to the drone 110, so the pan/tilt 120 can be omitted.

The display device 130 is located on the ground end of the unmanned aerial vehicle 100, can communicate with the drone 110 in a wireless manner, and can be used to display the attitude information of the drone 110. In addition, the image photographed by the photographing device 123 may also be displayed on the display device 130. It should be understood that the display device 130 may be an independent device or integrated in the control terminal 140.

The control terminal 140 is located on the ground end of the unmanned aerial vehicle 100, and can communicate with the drone 110 in a wireless manner for remote control of the drone 110.

It should be understood that the above-mentioned naming of the components of the unmanned aerial system is only for identification purposes, and should not be construed as a limitation to the embodiments of the present application.

Fig. 2 is a schematic diagram of an application scenario provided by an embodiment of the application. As shown in Fig. 2, Fig. 2 shows a drone 201 and a control terminal 202 of the drone. The control terminal 202 of the drone 201 may be one or more of a remote control, a smart phone, a desktop computer, a laptop computer, and a wearable device (watch, bracelet). In the embodiment of the present application, the control terminal 202 is the remote controller 2021 and the terminal device 2022 as an example for schematic description. The terminal device 2022 is, for example, a smart phone, a wearable device, a tablet computer, etc., but the embodiment of the present application is not limited thereto.

The drone 201 includes a fuselage 2011 and a gimbal 2012 connected to the fuselage 2011, and the gimbal 2012 is used to carry a load 2013. Wherein, the load 2013 includes a camera, the drone transmits the image captured by the camera to the control terminal 202, and the control terminal 202 displays the image captured by the camera. In a scene where the drone 201 is tracking a target object or in a scene where the drone 201 is flying around the target object, the drone 201 needs to determine the position of the target object. Therefore, the present application proposes that the method of observing the position of the target object when the target object is in a stationary state is different from the method of observing the position of the target object when the target object is in a moving state. For example, when the target object is in a static state, the position of the target object is determined according to the multi-view geometric algorithm; when the target object is in a moving state, the position of the target object is determined according to the image area size of the target object in the collected image. In order to accurately determine the location of the target when the target is in different states.

FIG. 3 is a flowchart of a method for controlling a movable platform according to an embodiment of the application. The method of this embodiment can be applied to a control device of a movable platform. The control device of the movable platform may be arranged on the movable platform; or, a part of the control device of the movable platform is arranged on the movable platform, and the other part is arranged on the control terminal of the movable platform. In this embodiment, the control device of the movable platform is set on the movable platform as an example. As shown in FIG. 3, the method of this embodiment may include:

S301: Determine whether the target object is in a static state.

In this embodiment, the movable platform includes a photographing device, which is used to photograph the target object so that the target object is located in the image collected by the photographing device. The movable platform can determine whether the target object photographed by the camera is in a static state. If it is determined that the target object is in a static state, S302 is executed. If it is determined that the target object is not in a static state, for example, the target object is in a moving state, S303 is executed.

S302: When the target object is in a static state, run a multi-view geometric algorithm according to the multi-frame images collected by the shooting device to determine the first position of the target object, and control the movable platform to perform work tasks on the target object according to the first position.

In this embodiment, when the target object is in a static state, the photographing device may photograph an image including the target object. The movable platform runs the multi-view geometric algorithm according to the multi-frame images collected by the camera to determine the position of the target object, which is called the first position. The first position can be used to guide the movable platform to perform corresponding work tasks. Then, according to the first position, the movable platform is controlled to perform work tasks on the target object.

Among them, one way to implement multi-view geometry to determine the position of the target object based on the multi-frame images collected by the camera is: when the target object is in a static state, according to the principle of epipolar geometry, as shown in A in Figure 4, One frame of image collected by the camera is taken as the first frame of image. The shooting device can determine the position of the target object through the observation of a single frame of image. On a ray connecting the shooting device and the target object, the direction of the target object can be determined, but the first frame image cannot determine the distance between the shooting device and the target object. the distance. As shown in B in FIG. 4, the next frame image of the first frame image collected by the camera is called the second frame image. According to the second frame of image, a ray that characterizes the direction of the target object can be determined. According to the determined intersection of the two rays, the position of the target object is obtained, that is, the position of the target object determined according to the first frame and the second frame image . The camera continues to capture the third frame of image, and according to the position of the target object determined above, the target object is projected into the first frame image, the second frame image, and the third frame image to obtain 3 projection positions respectively. According to these 3 The projection position (for example, the sum of the reprojection errors corresponding to the three projection positions is the smallest) optimizes the position of the above-mentioned target object, and obtains the optimized position of the target object. The camera continues to capture the fourth frame of image, and according to the above optimized target object position, the target object is respectively projected into the first frame image, the second frame image, the third frame image, and the fourth frame image to obtain 4 projection positions respectively. , Optimize the position of the target object according to the four projection positions (for example, the sum of the reprojection errors corresponding to the four projection positions is the smallest), and obtain the optimized position of the target object again. By analogy, the position of the target object is optimized, so that the accurate position of the target object when it is in a static state can be obtained through multiple frames of images. Optionally, the above-mentioned method may also be referred to as a triangulation ranging method.

S303: When the target object is in a moving state, determine the second position of the target object according to the size of the image area of the target object in the image captured by the shooting device, and control the movable platform to perform work tasks on the target object according to the second position.

When the target object is in a moving state, if the multi-view geometric algorithm is run to determine the position of the target object based on the multi-frame images collected by the camera, as shown in Figure 5, two rays are determined according to the two frames of images collected by the camera. The intersection of the two rays is not located at the position of the target object, so the position of the target object in the moving state cannot be obtained by the above-mentioned method when the target object is in a static state.

In this embodiment, when the target object is in a moving state, the photographing device may also photograph an image including the target object. The target object is located in the image collected by the photographing device and occupies a part of the image area in the image. The movable platform determines the position of the target object according to the size of the image area of the target object in the image collected by the shooting device, and this position is called the second position. The second position can be used to guide the movable platform to perform corresponding work tasks. Then, according to the second position, the movable platform is controlled to perform work tasks on the target object.

Among them, one way to determine the position of the target object according to the size of the image area in the image captured by the shooting device is: the single frame image of the shooting device can determine the ray that characterizes the direction of the target object; The size of the image area in the image collected by the camera and the priori information of the target object (such as the prior size, for example, the priori size of the target object is a car and the target object is different), to determine the distance between the target object and the camera , According to the distance and the direction of the target object, the position of the target object can be determined.

In this embodiment, the first position of the target object is determined by running the multi-view geometric algorithm according to the multi-frame images collected by the shooting device when the target object is in a static state. The size of the image area in the obtained image determines the second position of the target object, and the position of the target object is determined in different ways for different states of the target object, which improves the accuracy of the determined position of the target object. Moreover, according to the above-mentioned position control of the movable platform to perform work tasks on the target object, the performance of the work tasks is better.

In some embodiments, the work task is at least one of a circle flight task and a tracking task. If the work task surrounds the flight task, the movable platform is controlled to fly around the target object according to the first position or the second position. Wherein, the trajectory of the movable platform flying around the target object may be an involute line, or a spiral line, or an arc line with a constant radius (or a circular line). This embodiment can accurately surround the target object and can also quickly follow the target object.

In some embodiments, when the target object is in a static state, after the first position of the target object is obtained, the first position of the target object is no longer updated. That is, the multi-view geometric algorithm is no longer run based on the multiple frames of images collected by the camera to update the first position of the target object. Even if the camera continues to capture images, the first position of the target object is no longer optimized based on the image. It not only saves processing resources, avoids the influence of the noise of a certain frame of image on the shooting effect, but also ensures that when the target object is in a static state, the movable platform is controlled according to the same fixed first position to perform work tasks on the target object to improve the work task Implementation effect. For example, the center of the movable platform around the target object is fixed to ensure the smoothness of the surrounding path.

In some embodiments, when the target object is in a motion state, after obtaining the second position of the target object, the second position of the target object is updated. In order to improve the accuracy of the position determined when the target object is in motion, the performance of the work task is improved.

In some embodiments, a possible implementation of S302 above is: running a multi-view geometric algorithm based on the multi-frame images collected by the shooting device to determine the first distance between the target object and the shooting device, and according to the first distance Determine the first position of the target object.

In this embodiment, the distance between the target object and the shooting device can be determined by running the multi-view geometric algorithm according to the multiple frames of images collected by the shooting device, and this distance is called the first distance.

Optionally, the first distance is determined as the first position of the target object, where the position can be represented by the magnitude of the distance. Or, because the shooting device captures the target object, the target object occupies an image area in the image captured by the shooting device, the direction of the target object can be determined according to the image area, and the direction of the target object and the first distance are determined. The first position.

In addition, when the target object is in a static state, the distance between the target object and the shooting device can also be determined according to the size of the image area of the target object in the image captured by the shooting device, which is called the second distance. The specific implementation process can be referred to the above The description of, I won’t repeat it here. Among them, for the same target object, if the image size of the target object in the image collected by the shooting device is smaller, it indicates that the distance between the target object and the shooting device is farther, on the contrary, if the target object is in the image collected by the shooting device The larger the image size in, the closer the distance between the target object and the camera. However, in this embodiment, since the a priori size of the target object needs to be used in determining the distance between the target object and the shooting device, there may be a deviation between the a priori size and the actual size of the target object. In comparison, it is closer to the actual distance between the target object and the camera. Therefore, there is a distance deviation between the first distance and the second distance obtained in different ways.

Therefore, the movable platform of this embodiment can also obtain a distance correction deviation, which is used to characterize the distance deviation between the first distance and the second distance.

Correspondingly, a possible implementation of S303 above is: determining the third distance between the target object and the shooting device according to the size of the image area of the target object in the image captured by the shooting device, and correcting the deviation according to the third distance and the distance Determine the second position of the target object.

In this embodiment, when the target object is in a moving state, the distance between the target object and the photographing device is determined according to the size of the image area of the target object in the image collected by the photographing device, and this distance is called the third distance. However, as described above, the a priori size of the target object needs to be referred to in the process of determining the third distance, so there is an error between the third distance and the distance between the target object and the photographing device. Also, since the multi-view geometric algorithm is run based on the multi-frame images collected by the shooting device to determine that the distance between the target object and the shooting device is closer to the distance between the target object and the shooting device, the deviation is corrected according to the above-mentioned distance, and the third distance When the target object is in a moving state, it is equivalent to the distance between the target object and the shooting device determined by running the multi-view geometric algorithm based on the multi-frame images collected by the shooting device, and this distance is called the corrected distance. The corrected distance is closer to the distance between the target object and the photographing device, and then the second position of the target object is determined according to the corrected distance. Since the deviation of the third distance is corrected in this embodiment, the correction accuracy is higher, so that the obtained second position is closer to the actual position of the target object, which improves the accuracy of determining the position of the target object when the target object is in motion. sex.

Optionally, the corrected distance is determined as the second position of the target object, where the position can be represented by the magnitude of the distance. Or, because the shooting device captures the target object, the target object occupies an image area in the image captured by the shooting device, and the direction of the target object can be determined based on the image area, and the direction of the target object and the corrected distance are determined. The second position.

Several possible implementations of obtaining the distance correction deviation are described below with examples.

In a possible implementation manner, when the target object is in a static state, the second distance between the target object and the shooting device is determined according to the size of the image area of the target object in the image collected by the shooting device; according to the first distance and the second distance The distance determines the distance to correct the deviation. When the target object is in a static state, the multi-view geometric algorithm is run based on the multi-frame images collected by the camera to determine the first distance between the target object and the camera, which is closer to the target object when the target object is in a stationary state The distance from the camera. In order to obtain the distance between the target object and the shooting device determined by the multi-view geometric algorithm, the distance deviation from the distance between the target object and the shooting device determined according to the size of the image area, in this embodiment, when the target object is in a static state, The second distance between the target object and the shooting device is determined according to the size of the image area of the target object in the image collected by the shooting device. Then, according to the distance between the target object and the shooting device obtained in different ways under the same state of the target object, that is, the above-mentioned distance correction deviation is determined according to the first distance and the second distance.

Optionally, the first distance is subtracted from the second distance to obtain the above-mentioned distance correction deviation. Correspondingly, the above-mentioned corrected distance is, for example, equal to the sum of the third distance and the distance correction deviation.

Optionally, the first distance is compared to the second distance to obtain the above-mentioned distance correction deviation. Correspondingly, the above-mentioned corrected distance is, for example, equal to the product of the third distance and the distance corrected deviation.

Optionally, the first distance is subtracted from the second distance and then compared to the second distance to obtain the aforementioned distance correction deviation. Correspondingly, the above-mentioned corrected distance is, for example, equal to the sum of the third distance and (the product of the third distance and the distance corrected deviation).

It should be noted that the manifestation of the distance correction deviation is not limited to this.

Optionally, when the target object is in a static state, multiple frames of images collected by the shooting device are acquired, and the second distance between the target object and the shooting device is determined according to the size of the image area of the target object in each frame of the image collected by the shooting device, according to The first distance and the multiple second distances determine the above-mentioned distance correction deviation. For example: determine the average value of a plurality of second positions, and then determine the above-mentioned distance correction deviation according to the first distance and the average value. Alternatively, the distance correction deviation is determined according to the first distance and each second distance, and then the mean value of the multiple distance correction deviations is determined to be the final distance correction deviation.

In this embodiment, when the target object is in a stationary state, the above-mentioned distance correction deviation is calculated, and the distance correction deviation more accurately reflects the deviation between the target object and the photographing device obtained in different ways under the same state of the target object. Then, when the target object is in a motion state, the deviation is corrected according to the distance to obtain a more accurate position of the target object.

In another possible implementation manner, one or more reference distance correction deviations are pre-stored in the local storage device of the movable platform. The movable platform of this embodiment may obtain at least one reference distance correction deviation from the local storage device of the movable platform, and then determine the aforementioned distance correction deviation according to the obtained at least one reference distance correction deviation. If a reference distance correction deviation is obtained from the local storage device of the movable platform, the reference distance correction deviation is determined as the aforementioned distance correction deviation. If multiple reference distance correction deviations are obtained from the local storage device of the movable platform, the mean value, or the maximum value, or the minimum value, or the median of the multiple reference distance correction deviations is determined as the above-mentioned distance Correct the deviation.

Since the distance correction deviation of this embodiment is pre-stored in the local storage device of the movable platform, the distance correction deviation can be obtained from the local storage device, and there is no need to calculate and obtain it when the target object is in a static state, which saves processing resources.

Several implementations of obtaining at least one reference distance correction deviation from the local storage device of the movable platform and determining the distance correction deviation according to the at least one reference distance correction deviation will be described below with examples.

In a possible implementation manner, the local storage device of the movable platform pre-stores reference distance correction deviations corresponding to multiple object types, and the multiple object types include cars, people, and so on. Each object type corresponds to a reference distance correction deviation. Optionally, it is also possible that each object type corresponds to multiple reference distance correction deviations. The reference distance correction deviation corresponding to different object types may be different. In this embodiment, the movable platform determines the object type of the target object according to the image collected by the camera, and obtains the reference distance matching the object type of the target object from the local storage device of the movable platform according to the object type of the target object. Correct the deviation, and determine the reference distance correction deviation as the above-mentioned distance correction deviation. Here, the object type of the target object is a car as an example. In this embodiment, the reference distance correction deviation corresponding to the car is obtained from multiple reference distance correction deviations corresponding to cars, people, etc. pre-stored in the local storage device of the movable platform. . If the reference distance correction deviation corresponding to the car obtained from the local storage device of the movable platform is one, the reference distance correction deviation is determined as the aforementioned distance correction deviation. If there are multiple reference distance correction deviations corresponding to the car obtained from the local storage device of the movable platform, then the average or maximum or minimum value or median of the multiple reference distance correction deviations is determined as the aforementioned distance correction deviation .

In another possible implementation manner, multiple reference distance correction deviations corresponding to multiple reference distances are pre-stored in the local storage device of the movable platform. Each reference distance corresponds to a reference distance correction deviation. Optionally, it is also possible that each reference distance corresponds to multiple reference distance correction deviations. The reference distance correction deviations corresponding to different reference distances may be different.

Optionally, the movable platform determines the first distance between the target object and the photographing device through the foregoing solutions when the target object is in a static state. Then, the reference distance correction deviation corresponding to the at least one reference distance is acquired from the local storage device of the movable platform according to the first distance, and the distance correction deviation is determined according to the reference distance correction deviation. If the multiple reference distances include the first distance, one or more pre-stored reference distance correction deviations corresponding to the first distance are obtained from the local storage device of the movable platform. If the first distance is not included in the multiple reference distances, in this embodiment, the pre-stored one or more reference distance correction deviations corresponding to the reference distance closest to the first distance are obtained from the local storage device of the movable platform. Or, if the first distance is not included in the multiple reference distances, in this embodiment, one or more pre-stored two reference distances adjacent to the first distance are obtained from the local storage device of the movable platform. Correct the deviation with reference to the distance.

If the reference distance correction deviation obtained from the local storage device of the movable platform according to the first distance is one, the reference distance correction deviation is determined as the aforementioned distance correction deviation. If there are multiple reference distance correction deviations corresponding to the car obtained from the local storage device of the movable platform according to the first distance, then the average or maximum value or minimum value or median of the multiple reference distance correction deviations is determined as the above The distance correction deviation.

Optionally, in this embodiment, when the target object is in a static state, the movable platform determines the second distance between the target object and the shooting device according to the size of the image area of the target object in the image captured by the shooting device . The reference distance correction deviation corresponding to at least one reference distance is acquired from the local storage device of the movable platform according to the second distance, and the distance correction deviation is determined according to the reference distance correction deviation. For the specific implementation process, please refer to the above-mentioned related description about the first distance to determine the distance correction deviation, which will not be repeated here.

Optionally, in this embodiment, the movable platform determines the third distance between the target object and the shooting device in the above-mentioned manner when the target object is in a motion state. Then, the reference distance correction deviation corresponding to the at least one reference distance is acquired from the local storage device of the movable platform according to the third distance, and the distance correction deviation is determined according to the reference distance correction deviation. For the specific implementation process, please refer to the above description about the first distance to determine the distance correction deviation, which will not be repeated here.

In any of the foregoing embodiments, a possible implementation manner for determining whether the target object is in a static state is to obtain multiple frames of images containing the target object collected by the photographing device, and determine whether the target object is in a static state according to the multiple frames of images. In this embodiment, the photographing device may collect multiple frames of images, and the multiple frames of images include the target object. Then, according to the multi-frame image, it is determined whether the target object is in a static state. Therefore, it can quickly and stably detect whether the target object is in a static state or a moving state, and at the same time, it can avoid the influence of the noise of a certain frame of image on the result.

An example of how to determine whether the target is in a static state according to the multiple frames of images will be described below.

In a possible implementation manner, a multi-view geometric algorithm is run based on multiple frames of images to determine the fourth position of the target object at multiple moments; it is determined whether the multiple fourth positions meet the preset position convergence conditions; when they are satisfied, Determine that the target object is in a static state, otherwise, determine that the target object is in a moving state.

Optionally, each frame of image may correspond to a moment, and a possible implementation of running a multi-view geometric algorithm based on multiple frames of images to determine the fourth position of the target object at multiple moments is: the photographing device sequentially collects multiple frames of images, After the second frame of image is captured by the imaging device at the second time, the fourth position of the target object at the second time can be determined according to the first frame of image and the second frame of image. After the imaging device at the third time captures the third frame of image, the fourth position of the target object at the third time can be determined according to the first frame of image, the second frame of image, and the third frame of image. After the fourth frame of image is captured by the camera at the fourth time, the fourth position of the target object at the fourth time can be determined according to the first frame of image, the second frame of image, the third frame of image, and the fourth frame of image. By analogy, the fourth position of the target object at multiple moments can be obtained. For details on how to obtain the foregoing fourth position, reference may be made to the related description of S302 in the embodiment shown in FIG. 3, which will not be repeated here. Then it is determined whether the multiple fourth positions meet the preset position convergence condition, for example, whether the multiple fourth positions converge to the same position, for example, it is determined that the multiple fourth positions are located within a preset range area, and the preset range area can indicate The covariance of the fourth position convergence. When the multiple fourth positions meet the preset position convergence condition, it indicates that the position of the target object has basically not changed at these moments, and it is determined that the target object is in a static state. When the multiple fourth positions do not satisfy the preset position convergence condition, it indicates that the position of the target object is changing, and it is determined that the target object is in a moving state.

Optionally, each frame of image may correspond to a moment, and another possible implementation manner for determining the fourth position of the target object at multiple moments is: in this implementation manner, a cyclic triangulation ranging scheme is proposed, that is, multiple instantiations at one time. A triangulation range finder, updated over time, the oldest triangulation range finder will be deleted in real time, and the latest triangulation range finder will be supplemented at the same time. Specifically, a triangulation rangefinder is instantiated based on two adjacent frames of images.

For example, run a multi-view geometric algorithm to obtain a position based on at least two frames of images, and obtain multiple positions in the same way. The following takes two frames of images to obtain a position as an example, but this embodiment is not limited to two frames of images.

The photographing device sequentially collects multiple frames of images, taking 8 frames of images photographed by the photographing device at 8 moments as an example. After the camera captures the first frame image at the first moment and the second frame image at the second moment, a fourth position of the target object can be determined based on the first frame image and the second frame image (for example, see Figure 4 Shown in B). After acquiring the third frame image at the third time and the fourth frame image at the fourth time, a fourth position of the target object can be determined according to the third frame image and the fourth frame image. After the fifth frame of image is collected at the 5th moment and the 6th frame of image is collected at the 6th moment, a fourth position of the target object can be determined according to the 5th frame of image and the 6th frame of image. After the 7th frame image is collected at the 7th moment and the 8th frame image is collected at the 8th moment, a fourth position of the target object can be determined based on the 7th frame image and the 8th frame image.

When the target object is stationary, the position of the target object is basically unchanged. As shown in FIG. 6, it can be determined that the four fourth positions of the target object converge within the same preset range area, which indicates that the target object is in a static state.

When the target object is in motion, the position of the target object changes. As shown in FIG. 7, it can be determined that the fourth position of the target object cannot converge within the same preset range area at the above 4 moments, which indicates that the target object is in a motion state.

In another possible implementation, after acquiring multiple frames of images, each frame of the image may include the target object, and the target object occupies an image area in each frame of the image. In this embodiment, the target object may be included in each frame of the image. The size of the image area determines whether the target object is stationary. For example, if the target object is moving, the image size of the target object in the image is different. Therefore, it can be judged whether the difference between the size of the image area of the target object in each frame of the image is smaller than the preset difference, if so, the target object is determined to be in a static state, otherwise the target object is determined to be in a moving state.

In any of the foregoing embodiments, the movable platform determines whether the target object is switched from a stationary state to a moving state during the process of controlling the movable platform to perform work tasks on the target object according to the first position described above.

In this embodiment, when the target object is in a static state, after the first position is determined, the target object can be moved to perform work tasks on the target object according to the first position control. Because the first position is used for the movable platform to perform work tasks when the target object is stationary. If the target object is in a motion state, the first position can not be used to control the movable platform to perform the work task, otherwise the movable platform cannot perform the above-mentioned work task on the target object. Therefore, in the process of controlling the movable platform to perform work tasks on the target object according to the first position, it is determined whether the target object is switched from a stationary state to a moving state. If it is determined that the target object has not switched from the stationary state to the moving state, it means that the target object is still in the stationary state, and then the movable platform is continuously controlled to perform work tasks on the target object according to the first position. If it is determined that the target object is switched from a static state to a moving state, it means that the target object is in a moving state, the second position of the target object is determined according to the size of the image area of the target object in the image captured by the photographing device, and the second position is determined according to the second position Control the movable platform to perform work tasks on the target object.

Among them, one possible implementation of determining whether the target object is switched from a static state to a moving state is: acquiring a multi-frame image collected by a photographing device; and identifying the position of the target object in the multi-frame image; The object is projected into multiple frames of images to obtain the projection position of the target object in the image; according to the recognized position and projection position, it is determined whether the target object is switched from a static state to a moving state.

In this embodiment, in the process of controlling the movable platform to perform work tasks on the target object according to the first position, multiple frames of images collected by the shooting device are acquired, and then the position of the target object in each frame of the image is recognized (where, how To identify the position of the target object in the image, please refer to the description in the neural network model or image tracking and other related technologies, which will not be repeated here), and project the target object into each frame of image according to the above-mentioned first position to obtain the target object Is the projection position in each frame of the image. For each frame of image, determine the deviation between the recognized position and the projection position, which can be called re-projection error. According to the re-projection errors (ie multiple re-projection errors) corresponding to multiple frames of images, it is determined whether the target object is switched from a static state to a moving state.

For example, it is judged whether multiple reprojection errors are preset error convergence conditions, that is, whether these multiple reprojection errors converge to the same error. For example, it is determined that the multiple reprojection errors are within a preset error range. If multiple reprojection errors meet the preset error convergence conditions, it means that the position of the target object has basically not changed, and it is determined that the target object is still in a static state. When multiple reprojection errors do not meet the preset error convergence condition, it means that the position of the target object is beginning to change, it is determined that the target object starts to move, and the target object switches from a static state to a moving state.

For example, if it is determined that the re-projection error is getting larger and larger according to multiple re-projection errors, it is determined that the target object starts to move. Or, for example, some of the multiple re-projection errors are small, and some of the re-projection errors are large, then it is determined that the target object starts to move. Thus, it is determined that the target object is switched from a stationary state to a moving state.

Therefore, through the above methods of this embodiment, it can be detected in real time and quickly that the target object is switched from a stationary state to a moving state. Then it can seamlessly switch to: determine the second position of the target object according to the size of the image area of the target object in the image captured by the shooting device, and control the movable platform to perform the work task on the target object according to the second position . Avoid sudden changes in the determined position when switching from a stationary state to a moving state. Therefore, the path is smooth when the movable platform performs work tasks on the target object, and there is no sudden jitter.

Optionally, the photographing device in the foregoing embodiments may be a monocular camera.

An embodiment of the present application also provides a computer storage medium, the computer storage medium stores program instructions, and the program execution may include some or all of the steps of the movable platform control method in any of the above embodiments. .

FIG. 8 is a schematic structural diagram of a control device for a movable platform provided by an embodiment of the application. The movable platform includes a photographing device. As shown in FIG. 8, the control device 800 for the movable platform includes: at least one processor 801. A processor 801 is shown as an example in the figure.

The at least one processor 801 is configured to:

Determine whether the target object is stationary;

Optionally, when the target object is in a static state, the first position of the target object is no longer updated.

Optionally, when the at least one processor 801 runs a multi-view geometric algorithm according to the multi-frame images collected by the camera to determine the first position of the target object, it is specifically configured to:

Run a multi-view geometric algorithm according to the multi-frame images collected by the shooting device to determine the first distance between the target object and the shooting device, and determine the first position of the target object according to the first distance .

The at least one processor 801 is further configured to: obtain a distance correction deviation, where the distance correction deviation is used to characterize the distance deviation between the first distance and the second distance, and the second distance is the distance between the first distance and the second distance. The distance between the target object and the photographing device is determined according to the size of the image area of the target object in the image collected by the photographing device when the object is in a static state.

The at least one processor 801 is specifically configured to: when determining the second position of the target object according to the size of the image area of the target object in the image captured by the photographing device:

The third distance between the target object and the shooting device is determined according to the size of the image area of the target object in the image captured by the shooting device, and the third distance between the target object and the shooting device is determined according to the third distance and the distance correction deviation. The second position of the target object.

Optionally, the at least one processor 801 is specifically configured to: when the target object is in a static state, determine the target object according to the size of the image area of the target object in the image captured by the photographing device The second distance from the camera; the distance correction deviation is determined according to the first distance and the second distance.

Optionally, one or more reference distance correction deviations are pre-stored in the local storage device of the movable platform, and the at least one processor 801 is specifically configured to:

Acquire at least one reference distance correction deviation from a local storage device of the movable platform, and determine the distance correction deviation according to the at least one reference distance correction deviation.

Optionally, the local storage device of the movable platform pre-stores reference distance correction deviations corresponding to multiple object types, and the at least one processor 801 is further configured to: determine according to the image collected by the photographing device The object type of the target object.

The at least one processor 801, when acquiring at least one reference distance correction deviation from the local storage device of the movable platform, and determining the distance correction deviation according to the at least one reference distance correction deviation, is specifically configured to:

Acquire a reference distance correction deviation matching the object type of the target object from a local storage device of the movable platform according to the object type of the target object, and determine the reference distance correction deviation as the distance correction deviation.

Optionally, a plurality of reference distance correction deviations corresponding to the reference distance are pre-stored in the local storage device of the movable platform. The at least one processor 801 is specifically configured to: obtain a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the first distance, and determine the reference distance correction deviation according to the reference distance correction deviation The distance correction deviation.

Optionally, the distance correction deviation corresponding to a plurality of pre-stored reference distances is acquired from a local storage device of the movable platform. The at least one processor 801 is further configured to: when the target object is in a static state, determine the difference between the target object and the shooting device according to the size of the image area of the target object in the image captured by the shooting device The second distance between.

Acquire a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the second distance, and determine the distance correction deviation according to the reference distance correction deviation.

Optionally, the distance correction deviation corresponding to a plurality of pre-stored reference distances is acquired from a local storage device of the movable platform.

The at least one processor 801 is specifically configured to: obtain a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the third distance, and determine the reference distance correction deviation according to the reference distance correction deviation The distance correction deviation.

Optionally, the at least one processor 801 is specifically configured to: acquire a multi-frame image including a target object collected by the photographing device; and determine whether the target is in a static state according to the multi-frame image.

Optionally, the at least one processor 801 is specifically configured to: run a multi-view geometric algorithm according to the multi-frame images to determine the fourth position of the target object at multiple moments; and determine whether the multiple fourth positions satisfy The preset position convergence condition; when it is met, it is determined that the target object is in a static state, otherwise, it is determined that the target object is in a moving state.

Optionally, the at least one processor 801 is further configured to:

In the process of controlling the movable platform to perform work tasks on the target object according to the first position, it is determined whether the target object is switched from a stationary state to a moving state.

Optionally, the at least one processor 801 is specifically configured to: acquire a multi-frame image collected by a photographing device; identify the position of a target object in the multi-frame image; Projecting into the multi-frame image to obtain the projection position of the target object in the image; determining whether the target object is switched from a static state to a moving state according to the recognized position and the projection position.

Optionally, the work task is at least one of a circle flight task and a tracking task.

Optionally, the control device 800 of the movable platform of this embodiment may further include a memory 802. The memory 802 is used to store program codes. The at least one processor 801 calls the program code, and when the program code is executed, it is used to implement the foregoing methods.

The control device of the movable platform of this embodiment can be used to implement the technical solutions of the foregoing method embodiments of the present application, and the implementation principles and technical effects are similar, and will not be repeated here.

FIG. 9 is a schematic structural diagram of a movable platform provided by an embodiment of the application. The movable platform 900 includes a camera 901 and at least one processor 902. The figure shows one processor 902 as an example.

The at least one processor 902 is configured to: determine whether the target object is in a static state; when the target object is in a static state, run a multi-view geometric algorithm according to the multi-frame images collected by the photographing device 901 to determine the The first position of the target object, and according to the first position, the movable platform 900 is controlled to perform work tasks on the target object; when the target object is in a moving state, the shooting device 901 captures the target object according to the target object. The size of the image area in the obtained image determines the second position of the target object, and the movable platform 900 is controlled to perform the work task on the target object according to the second position.

Optionally, when the at least one processor 902 runs a multi-view geometric algorithm according to the multi-frame images collected by the photographing device 901 to determine the first position of the target object, it is specifically configured to:

Run a multi-view geometric algorithm based on the multi-frame images collected by the shooting device 901 to determine the first distance between the target object and the shooting device 901, and determine the first distance of the target object according to the first distance One location.

The at least one processor 902 is further configured to: obtain a distance correction deviation, where the distance correction deviation is used to characterize the distance deviation between the first distance and the second distance, and the second distance is the distance between the first distance and the second distance. The distance between the target object and the photographing device 901 is determined according to the size of the image area of the target object in the image collected by the photographing device 901 when the object is in a static state.

The at least one processor 902 is specifically configured to determine the second position of the target object according to the size of the image area of the target object in the image captured by the photographing device 901:

Determine the third distance between the target object and the shooting device 901 according to the size of the image area of the target object in the image captured by the shooting device 901, and correct the deviation according to the third distance and the distance Determine the second position of the target object.

Optionally, the at least one processor 902 is specifically configured to: when the target object is in a static state, determine the target according to the size of the image area of the target object in the image captured by the photographing device 901 The second distance between the object and the camera 901; the distance correction deviation is determined according to the first distance and the second distance.

Optionally, the mobile platform 900 in this embodiment locally further includes a storage device 903. One or more reference distance correction deviations are pre-stored in the local storage device 903 of the movable platform 900, and the at least one processor 902 is specifically configured to:

At least one reference distance correction deviation is acquired from the local storage device 903 of the movable platform 900, and the distance correction deviation is determined according to the at least one reference distance correction deviation.

Optionally, the local storage device 903 of the movable platform 900 pre-stores reference distance correction deviations corresponding to multiple object types, and the at least one processor 902 is further configured to: The image determines the object type of the target object.

The at least one processor 902 is specifically configured to obtain at least one reference distance correction deviation from the local storage device 903 of the movable platform 900, and to determine the distance correction deviation according to the at least one reference distance correction deviation :

The reference distance correction deviation matching the object type of the target object is obtained from the local storage device 903 of the movable platform 900 according to the object type of the target object, and the reference distance correction deviation is determined as the distance correction deviation.

Optionally, the local storage device 903 of the movable platform 900 pre-stores reference distance correction deviations corresponding to multiple reference distances.

The at least one processor 902 is specifically configured to: obtain a reference distance correction deviation corresponding to at least one reference distance from the local storage device 903 of the movable platform 900 according to the first distance, and correct the deviation according to the reference distance Determine the distance correction deviation.

Optionally, the local storage device 903 of the movable platform 900 obtains the distance correction deviation corresponding to multiple pre-stored reference distances, and the at least one processor 902 is further configured to:

When the target object is in a static state, the second distance between the target object and the photographing device 901 is determined according to the size of the image area of the target object in the image collected by the photographing device 901.

The reference distance correction deviation corresponding to at least one reference distance is acquired from the local storage device 903 of the movable platform 900 according to the second distance, and the distance correction deviation is determined according to the reference distance correction deviation.

Optionally, the local storage device 903 of the movable platform 900 obtains the distance correction deviation corresponding to multiple pre-stored reference distances. The at least one processor 902 is specifically configured to: obtain a reference distance correction deviation corresponding to at least one reference distance from the local storage device 903 of the movable platform 900 according to the third distance, and correct the deviation according to the reference distance Determine the distance correction deviation.

Optionally, the at least one processor 902 is specifically configured to: acquire a multi-frame image including a target object collected by the photographing device 901; and determine whether the target is in a static state according to the multi-frame image.

Optionally, the at least one processor 902 is specifically configured to: run a multi-view geometric algorithm according to the multi-frame images to determine the fourth position of the target object at multiple moments; and determine whether the multiple fourth positions satisfy The preset position convergence condition; when it is met, it is determined that the target object is in a static state, otherwise, it is determined that the target object is in a moving state.

Optionally, the at least one processor 902 is further configured to:

In the process of controlling the movable platform 900 to perform work tasks on the target object according to the first position, it is determined whether the target object is switched from a stationary state to a moving state.

Optionally, the at least one processor 902 is specifically configured to: acquire a multi-frame image captured by the photographing device 901; identify the position of the target object in the multi-frame image; The object is projected into the multi-frame image to obtain the projection position of the target object in the image; according to the identified position and the projection position, it is determined whether the target object is switched from a static state to a motion state.

Optionally, the movable platform 900 of this embodiment may further include a memory (not shown in the figure). The memory is used to store program codes. The at least one processor 902 calls the program code, and when the program code is executed, it is used to implement the foregoing methods.

The memory and the aforementioned storage device 903 may be the same component or different components.

The movable platform of this embodiment can be used to implement the technical solutions of the foregoing method embodiments of the present application, and its implementation principles and technical effects are similar, and will not be repeated here.

FIG. 10 is a schematic structural diagram of a movable platform provided by another embodiment of the application. The movable platform 1000 includes a camera 1001 and a control device 1002 of the movable platform.

Wherein, the control device 1002 of the movable platform may adopt the structure of the device embodiment shown in FIG. 8, and correspondingly, it may execute the technical solution provided by any of the foregoing method embodiments, which will not be repeated here.

Optionally, the movable platform 1000 further includes a storage device 1003. The storage device 1003 is configured to pre-store one or more reference distance correction deviations.

A person of ordinary skill in the art can understand that all or part of the steps in the above method embodiments can be implemented by a program instructing relevant hardware. The foregoing program can be stored in a computer readable storage medium. When the program is executed, it is executed. Including the steps of the foregoing method embodiment; and the foregoing storage medium includes: read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disks or optical disks, etc., which can store program codes Medium.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the application, not to limit them; although the application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the technical solutions described in the foregoing embodiments, or equivalently replace some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present application. Scope.

Claims

A method for controlling a movable platform, wherein the movable platform includes a camera, and the method includes:

Determine whether the target object is stationary;

When the target object is in a static state, a multi-view geometric algorithm is run based on the multi-frame images collected by the shooting device to determine the first position of the target object, and the movable platform is controlled according to the first position. The target object performs work tasks;

When the target object is in a moving state, the second position of the target object is determined according to the size of the image area of the target object in the image captured by the shooting device, and the movable platform is controlled according to the second position Perform the work task on the target object.
The method according to claim 1, wherein when the target object is in a static state, the first position of the target object is no longer updated.
The method according to claim 1 or 2, wherein the running a multi-view geometric algorithm according to the multi-frame images collected by the shooting device to determine the first position of the target object comprises:

Run a multi-view geometric algorithm according to the multi-frame images collected by the shooting device to determine the first distance between the target object and the shooting device, and determine the first position of the target object according to the first distance ；

The method further includes: obtaining a distance correction deviation, wherein the distance correction deviation is used to characterize a distance deviation between the first distance and a second distance, and the second distance is when the target object is in a static state The distance between the target object and the photographing device is determined according to the size of the image area of the target object in the image collected by the photographing device;

The determining the second position of the target object according to the size of the image area of the target object in the image captured by the photographing device includes:

The third distance between the target object and the shooting device is determined according to the size of the image area of the target object in the image captured by the shooting device, and the third distance between the target object and the shooting device is determined according to the third distance and the distance correction deviation. The second position of the target object.
The method according to claim 3, wherein said obtaining the distance correction deviation comprises:

When the target object is in a static state, determining the second distance between the target object and the photographing device according to the size of the image area of the target object in the image collected by the photographing device;

The distance correction deviation is determined according to the first distance and the second distance.
The method according to claim 3, wherein one or more reference distance correction deviations are pre-stored in the local storage device of the movable platform, and the obtaining the distance correction deviations comprises:

Acquire at least one reference distance correction deviation from a local storage device of the movable platform, and determine the distance correction deviation according to the at least one reference distance correction deviation.
The method according to claim 5, wherein the local storage device of the movable platform pre-stores reference distance correction deviations corresponding to multiple object types, and the method further comprises:

Determining the object type of the target object according to the image collected by the photographing device;

The acquiring at least one reference distance correction deviation from a local storage device of the movable platform, and determining the distance correction deviation according to the at least one reference distance correction deviation includes:

Acquire a reference distance correction deviation matching the object type of the target object from a local storage device of the movable platform according to the object type of the target object, and determine the reference distance correction deviation as the distance correction deviation.
The method according to claim 5, characterized in that a plurality of reference distance correction deviations corresponding to the reference distance are pre-stored in the local storage device of the movable platform;

Obtaining at least one reference distance correction deviation from the local storage device of the movable platform, and determining the distance correction deviation according to the at least one reference distance correction deviation includes:

Acquire a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the first distance, and determine the distance correction deviation according to the reference distance correction deviation.
The method according to claim 5, characterized in that obtaining the distance correction deviation corresponding to a plurality of pre-stored reference distances from a local storage device of the movable platform, the method further comprising:

When the target object is in a static state, determining the second distance between the target object and the photographing device according to the size of the image area of the target object in the image collected by the photographing device;

Obtaining at least one reference distance correction deviation from the local storage device of the movable platform, and determining the distance correction deviation according to the at least one reference distance correction deviation includes:

Acquire a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the second distance, and determine the distance correction deviation according to the reference distance correction deviation.
The method according to claim 5, wherein the distance correction deviation corresponding to a plurality of pre-stored reference distances is obtained from a local storage device of the movable platform;

Obtaining at least one reference distance correction deviation from the local storage device of the movable platform, and determining the distance correction deviation according to the at least one reference distance correction deviation includes:

Acquire a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the third distance, and determine the distance correction deviation according to the reference distance correction deviation.
The method according to any one of claims 1-9, wherein the determining whether the target object is in a static state comprises:

Acquiring multiple frames of images containing the target object collected by the photographing device;

Determine whether the target is in a static state according to the multiple frames of images.
The method according to claim 10, wherein the determining whether the target is in a static state according to the multi-frame images comprises:

Running a multi-view geometric algorithm according to the multi-frame images to determine the fourth position of the target object at multiple moments;

Determining whether the multiple fourth positions meet a preset position convergence condition;

When it is satisfied, it is determined that the target object is in a static state; otherwise, it is determined that the target object is in a moving state.
The method according to any one of claims 1-11, wherein the method further comprises:

In the process of controlling the movable platform to perform work tasks on the target object according to the first position, it is determined whether the target object is switched from a stationary state to a moving state.
The method according to claim 12, wherein the determining whether the target object is switched from a stationary state to a moving state comprises:

Acquiring multiple frames of images collected by the shooting device;

Identifying the position of the target object in the multiple frames of images;

Projecting the target object into the multiple frames of images according to the first position to obtain the projection position of the target object in the image;

It is determined whether the target object is switched from a stationary state to a moving state according to the recognized position and the projection position.
The method according to any one of claims 1-13, wherein the work task is at least one of a circle flight task and a tracking task.
A control device for a movable platform, characterized in that the movable platform includes a photographing device, and the control device for the movable platform includes a memory and at least one processor;

The memory is used to store program code;

The at least one processor is configured to execute the program code for:

Determine whether the target object is stationary;

When the target object is in a static state, a multi-view geometric algorithm is run based on the multi-frame images collected by the shooting device to determine the first position of the target object, and the movable platform is controlled according to the first position. The target object performs work tasks;

When the target object is in a moving state, the second position of the target object is determined according to the size of the image area of the target object in the image captured by the shooting device, and the movable platform is controlled according to the second position Perform the work task on the target object.
The control device according to claim 15, wherein when the target object is in a static state, the first position of the target object is no longer updated.
The control device according to claim 15 or 16, wherein the at least one processor runs a multi-view geometric algorithm to determine the first position of the target object according to the multi-frame images collected by the shooting device When, specifically used for:

Run a multi-view geometric algorithm according to the multi-frame images collected by the shooting device to determine the first distance between the target object and the shooting device, and determine the first position of the target object according to the first distance ；

The at least one processor is further configured to: obtain a distance correction deviation, where the distance correction deviation is used to characterize the distance deviation between the first distance and the second distance, and the second distance is the distance between the target The distance between the target object and the photographing device determined according to the size of the image area of the target object in the image collected by the photographing device when the object is in a static state;

The at least one processor is specifically configured to determine the second position of the target object according to the size of the image area of the target object in the image captured by the photographing device:

The third distance between the target object and the shooting device is determined according to the size of the image area of the target object in the image captured by the shooting device, and the third distance between the target object and the shooting device is determined according to the third distance and the distance correction deviation. The second position of the target object.
The control device according to claim 17, wherein the at least one processor is specifically configured to:

When the target object is in a static state, determining the second distance between the target object and the photographing device according to the size of the image area of the target object in the image collected by the photographing device;

The distance correction deviation is determined according to the first distance and the second distance.
The control device according to claim 17, wherein one or more reference distance correction deviations are pre-stored in the local storage device of the movable platform, and the at least one processor is specifically configured to:

Acquire at least one reference distance correction deviation from a local storage device of the movable platform, and determine the distance correction deviation according to the at least one reference distance correction deviation.
The control device according to claim 19, wherein the local storage device of the movable platform pre-stores reference distance correction deviations corresponding to multiple object types, and the at least one processor is further configured to:

Determining the object type of the target object according to the image collected by the photographing device;

The at least one processor, when acquiring at least one reference distance correction deviation from the local storage device of the movable platform, and determining the distance correction deviation according to the at least one reference distance correction deviation, is specifically configured to:

Acquire a reference distance correction deviation matching the object type of the target object from a local storage device of the movable platform according to the object type of the target object, and determine the reference distance correction deviation as the distance correction deviation.
The control device according to claim 19, wherein the local storage device of the movable platform pre-stores a plurality of reference distance correction deviations corresponding to the reference distance;

The at least one processor is specifically configured to: obtain a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the first distance, and determine the reference distance correction deviation according to the reference distance correction deviation Distance correction deviation.
The control device according to claim 19, wherein the distance correction deviation corresponding to a plurality of pre-stored reference distances is obtained from the local storage device of the movable platform, and the at least one processor is further configured to :

When the target object is in a static state, determining the second distance between the target object and the photographing device according to the size of the image area of the target object in the image collected by the photographing device;

The at least one processor, when acquiring at least one reference distance correction deviation from the local storage device of the movable platform, and determining the distance correction deviation according to the at least one reference distance correction deviation, is specifically configured to:

Acquire a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the second distance, and determine the distance correction deviation according to the reference distance correction deviation.
The control device according to claim 19, wherein the distance correction deviation corresponding to a plurality of pre-stored reference distances is acquired from a local storage device of the movable platform;

The at least one processor is specifically configured to: obtain a reference distance correction deviation corresponding to at least one reference distance from a local storage device of the movable platform according to the third distance, and determine the reference distance correction deviation according to the reference distance correction deviation Distance correction deviation.
The control device according to any one of claims 15-23, wherein the at least one processor is specifically configured to:

Acquiring multiple frames of images containing the target object collected by the photographing device;

Determine whether the target is in a static state according to the multiple frames of images.
The control device according to claim 24, wherein the at least one processor is specifically configured to:

Running a multi-view geometric algorithm according to the multi-frame images to determine the fourth position of the target object at multiple moments;

Determining whether the multiple fourth positions meet a preset position convergence condition;

When it is satisfied, it is determined that the target object is in a static state; otherwise, it is determined that the target object is in a moving state.
The control device according to any one of claims 15-25, wherein the at least one processor is further configured to:

In the process of controlling the movable platform to perform work tasks on the target object according to the first position, it is determined whether the target object is switched from a stationary state to a moving state.
The control device according to claim 26, wherein the at least one processor is specifically used for:

Acquiring multiple frames of images collected by the shooting device;

Identifying the position of the target object in the multiple frames of images;

Projecting the target object into the multiple frames of images according to the first position to obtain a projection position of the target object in the image;

It is determined whether the target object is switched from a stationary state to a moving state according to the recognized position and the projection position.
The control device according to any one of claims 15-27, wherein the work task is at least one of a circle flight task and a tracking task.
A movable platform, characterized in that the movable platform comprises a camera and a control device of the movable platform according to any one of claims 15-28.
A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium; when the computer program is executed, the portable platform according to any one of claims 1-14 is realized的控制方法。 Control methods.