CN108733076A - Method and device for grabbing target object by unmanned aerial vehicle and electronic equipment - Google Patents

Abstract

The embodiment of the present invention discloses a method, device and electronic equipment for an unmanned aerial vehicle to grab a target object. The method includes: obtaining the relative position information between the target object and the unmanned aerial vehicle in real time; The UAV tracks the planned path of the target object; the UAV is controlled to track the target object based on the planned path; when the relative distance between the UAV and the target object reaches a set threshold, the UAV is controlled to The machine and the mechanical arm act to grab the target object. By adopting the above technical solution, the UAV can effectively grasp the target object in the environment without a motion capture system, especially for the effective grasp of the moving target object.

Description

A method, device and electronic equipment for capturing a target object by an unmanned aerial vehicle

technical field

Embodiments of the present invention relate to the field of unmanned aerial vehicles, in particular to a method, device and electronic equipment for an unmanned aerial vehicle to grab a target object.

Background technique

With the rapid development of UAV technology represented by rotorcraft, UAVs have been widely used in aerial photography, reconnaissance, agriculture, express transportation, disaster relief and other fields.

However, the current drones are immature in capturing target objects, and are limited to relying on indoor motion capture systems, and are mainly aimed at capturing indoor stationary objects. When the target object is outdoors and there is no motion capture system It cannot be grasped effectively when it is in a different environment, especially when the grasped object is a moving object, it cannot be grasped accurately.

Contents of the invention

The present invention provides a method, device and electronic equipment for a drone to capture a target object, so as to realize the effective capture of the target object by the drone in an environment without a motion capture system.

In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:

In the first aspect, an embodiment of the present invention provides a method for a drone to grab a target object, the method comprising:

Real-time acquisition of relative position information between the target object and the UAV;

Determine the planned path of the UAV to track the target object according to the relative position information;

controlling the UAV to track the target object based on the planned path;

When the relative distance between the drone and the target object reaches a set threshold, the drone and the mechanical arm are controlled to grab the target object.

Further, the real-time acquisition of relative position information between the target object and the UAV includes:

Determine the abscissas corresponding to the imaging points of the target object on the left and right imaging planes corresponding to the binocular cameras loaded on the drone;

calculating the distance between the imaging points of the target object on the left and right imaging planes based on the abscissa;

According to the geometric relationship between the left and right imaging planes, in combination with the parameters of the binocular camera and the distance between the imaging points, calculate the relative depth information between the target object and the UAV;

Wherein, the parameters of the binocular camera include camera focal length and camera center distance.

Further, the determining the planned path of the UAV tracking the target object according to the relative position information includes:

Based on the pre-designed dynamic trajectory planning based on the relative depth information, calculate the planned path of the UAV tracking the target object in real time;

Wherein, the pre-designed dynamic trajectory planning is:

x _d (t)＝Δx(t)exp(-w ₁ *t)+∫v _Tx dt

y _d (t)=Δy(t)exp(-w ₂ *t)+∫v _Ty dt

z _d (t)=Δz(t)exp(-w ₃ *t)+∫v _Tz dt+ρ;

x _d (t), y _d (t), z _d (t) represent the planned path of the UAV in the directions of x, y, and z respectively, t represents the time, Δx(t), Δy(t), Δz( t) is the relative depth information between the target object and the drone, w ₁ , w ₂ , and w ₃ are the control parameters of the system, and v _Tx , v _Ty , v _Tz are the target object in the x, y, and z directions, respectively. When the target object is a stationary target object, v _Tx , v _Ty , and v _Tz are all 0, and ρ is the height of the target object.

Further, when the target object is a moving target object, before determining the planned path of the UAV tracking the target object according to the relative position information, it also includes:

The moving speed of the target object in the x, y, and z directions is calculated by the optical flow sensor mounted on the drone.

Further, when the relative distance between the UAV and the target object reaches a set threshold, the UAV and the mechanical arm are controlled to grasp the target object, including:

When the relative distance between the drone and the target object in the x direction and the y direction reaches a first set threshold, control the mechanical arm of the drone to adjust the state to prepare for grabbing;

When the adjustment state of the robotic arm of the UAV is completed, the UAV is controlled to descend;

When the drone drops to a set height, and the relative distance between the drone and the target object in the x direction and the y direction reaches the first set threshold, control the drone and the mechanical arm to grab the target object.

Further, the control of the unmanned aerial vehicle and the mechanical arm to grab the target object includes:

Controlling the UAV and the robotic arm to grab the target object based on the adaptive sliding film control algorithm, wherein the control amount for controlling the UAV and the robotic arm to grab the target object includes:

q _k ′=q _d ′+λe

Among them, F represents the lift force of the UAV, τ _x , τ _y and τ _z respectively represent the three torques of the UAV about the x, y, and z axes in the UAV body coordinate system, and τ _n×1 is zero The control quantities, R, Q, and I of the rotation angles of the n motors on the human-machine manipulator are respectively the transformation matrix of the system, is the roll angle and pitch angle of the UAV, Ψ is the yaw angle of the UAV, is the prediction and estimation of the system matrix, A and K are positive definite gain matrices of the system, s is the synovial surface, q _d is the expected state matrix of the UAV manipulator composite system, λ is a positive definite matrix, e is the UAV manipulator The error matrix between the actual state and the expected state of the composite system.

Further, when the control drone captures the target object, it also includes:

Control the UAV to carry the target object to the preset position.

In the second aspect, an embodiment of the present invention provides a device for a drone to grab a target object, the device comprising:

The obtaining module is used to obtain the relative position information between the target object and the UAV in real time;

A determining module, configured to determine the planned path of the UAV tracking the target object according to the relative position information;

a tracking module, configured to control the UAV to track the target object based on the planned path;

The grabbing module is used to control the action of the drone and the mechanical arm to grab the target object when the relative distance between the drone and the target object reaches a set threshold.

In a third aspect, an embodiment of the present invention provides an electronic device, including a first memory, a first processor, and a computer program stored in the memory and operable on the first processor, and the first processor executes the The computer program realizes the method for the drone to grab the target object as described in the first aspect above.

In a fourth aspect, an embodiment of the present invention provides a storage medium containing computer-executable instructions, and when the computer-executable instructions are executed by a computer processor, the UAV captures the target object as described in the first aspect above. Methods.

A method for capturing a target object by a UAV provided in an embodiment of the present invention obtains the relative position information between the target object and the UAV in real time, and determines the planned path for the UAV to track the target object according to the relative position information , controlling the UAV to track the target object based on the planned path, and when the relative distance between the UAV and the target object reaches a set threshold, control the UAV and the mechanical arm to grab the target object The technical means of describing the target object realizes the effective capture of the target object by the UAV in the environment without a motion capture system, especially for the effective capture of the moving target object.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings that need to be used in the description of the embodiments of the present invention. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention , for those skilled in the art, other drawings can also be obtained according to the content of the embodiment of the present invention and these drawings without any creative effort.

FIG. 1 is a schematic flowchart of a method for a drone to grab a target object provided by Embodiment 1 of the present invention;

FIG. 2 is a schematic diagram of a pixel coordinate system and an image coordinate system provided by Embodiment 1 of the present invention;

FIG. 3 is a schematic diagram of a camera imaging principle provided by Embodiment 1 of the present invention;

Fig. 4 is a principle diagram of binocular ranging provided by Embodiment 1 of the present invention;

5 is a schematic flowchart of a method for a drone to grab a target object according to Embodiment 2 of the present invention;

FIG. 6 is a schematic structural diagram of a robotic arm of a drone provided by Embodiment 2 of the present invention;

FIG. 7 is a schematic structural diagram of a drone and a three-degree-of-freedom mechanical arm provided in Embodiment 2 of the present invention;

FIG. 8 is a schematic flowchart of another method for a drone to grab a target object provided by Embodiment 2 of the present invention;

FIG. 9 is a schematic structural diagram of a device for grabbing a target object by a drone provided in Embodiment 3 of the present invention;

FIG. 10 is a schematic structural diagram of an electronic device provided by Embodiment 4 of the present invention.

Detailed ways

In order to make the technical problems solved by the present invention, the technical solutions adopted and the technical effects achieved clearer, the technical solutions of the embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only the technical solutions of the present invention. Some, but not all, embodiments. The embodiments of the present invention, and all other embodiments obtained by those skilled in the art without creative efforts, all belong to the protection scope of the present invention.

Embodiment one

FIG. 1 is a schematic flowchart of a method for a drone to grab a target object according to Embodiment 1 of the present invention. The method for grabbing a target object by a drone disclosed in this embodiment can be applied to an outdoor environment, and can effectively grab a stationary object or a moving object without relying on a motion capture system. The method can be executed by a device for grabbing a target object by a drone, wherein the device can be implemented by software and/or hardware, and can be integrated in the body of the drone or integrated in a server dedicated to serving the drone. Specifically referring to shown in Figure 1, the method may include the following steps:

110. Obtain the relative position information between the target object and the UAV in real time.

Wherein, the purpose of obtaining the relative position information between the target object and the UAV in real time is to adjust the path of the UAV tracking the target object according to the relative position information in real time, so that the UAV continuously approaches the target object.

Specifically, the relative position information between the target object and the UAV can be obtained in real time in the following ways:

Determine the abscissas corresponding to the imaging points of the target object on the left and right imaging planes corresponding to the binocular cameras loaded on the drone;

calculating the distance between the imaging points of the target object on the left and right imaging planes based on the abscissa;

According to the geometric relationship between the left and right imaging planes, in combination with the parameters of the binocular camera and the distance between the imaging points, calculate the relative depth information between the target object and the UAV;

Wherein, the parameters of the binocular camera include the focal length of the camera and the center distance of the camera, and the relative depth information between the target object and the UAV represents the relative positional relationship between the target object and the UAV.

In the imaging process of the binocular camera, there are four coordinate systems, namely: pixel coordinate system, image coordinate system, camera coordinate system and world coordinate system. Refer to the schematic diagram of the pixel coordinate system and the image coordinate system shown in Figure 2. The pixel coordinate system takes the upper left corner of the image as the origin O _o , and the horizontal and vertical coordinates (u, v) respectively represent the number of columns and rows of the pixel in the image number; xO ₁ y is the image coordinate system, and its origin O ₁ is the intersection point of the optical axis of the camera and the image plane, generally the center of the image plane, also known as the principal point of the image, according to the relationship between the pixel coordinate system and the image coordinate system , the points in the two coordinate systems can be converted to each other. Referring to the camera imaging principle diagram shown in Figure 3, O is the optical center of the camera, Z _C is the optical axis of the camera, the intersection point of the optical axis and the image plane is O ₁ , and the coordinate system OX _C Y _C Z _C is the camera coordinate system, O _W -X _W Y _W Z _W is the world coordinate system, and the distance between OO ₁ is the focal length f of the camera.

The 3D estimation of the target object in the actual scene can be determined by binocular stereo vision technology. Specifically, refer to the schematic diagram of binocular distance measurement shown in Figure 4. _OL and _OR are the optical centers of the left and right cameras, respectively, and the left , the optical axis of the right camera and their respective imaging planes are shown in Figure 4, the distance between the optical centers of the left and right cameras is B, that is, the distance between the centers of the cameras is B, the two cameras are on the same plane, and the distance between the left and right cameras is B. The Y coordinates of the projection center are equal, and the imaging points of the space point P(x, y, z) on the left and right camera imaging planes at the same time are X _L and X _R respectively. According to the triangular geometric relationship:

Among them, the coordinate system of each quantity in the above formula is: X _L , X _R and Y are respectively under the image planes of the left and right cameras, that is, the coordinates under the image plane coordinate system, and the origins are the light beams of the left and right cameras respectively. The intersection of the axis and the image plane, f and B are constants, respectively the focal length of the camera and the center distance of the camera, x, y, z are the coordinates in the left camera coordinate system, and the origin is _OL . The parallax d is the distance between the imaging points X _L and X _R , and according to the geometric relationship:

d=B-(X _L -X _R )

That is, the relative depth information x, y and z of the spatial point P are obtained.

120. Determine a planned path for the drone to track the target object according to the relative position information.

Specifically, the planned path for the UAV to track the target object is determined according to the relative position information, including:

Based on the pre-designed dynamic trajectory planning based on the relative depth information, calculate the planned path of the UAV tracking the target object in real time;

Wherein, the pre-designed dynamic trajectory planning is:

x _d (t)＝Δx(t)exp(-w ₁ *t)+∫v _Tx dt

y _d (t)=Δy(t)exp(-w ₂ *t)+∫v _Ty dt

z _d (t)=Δz(t)exp(-w ₃ *t)+∫v _Tz dt+ρ;

Among them, x _d (t), y _d (t), z _d (t) represent the planned path of the UAV in the directions of x, y, and z respectively, t represents time, Δx(t), Δy(t), Δz(t) is the relative depth information between the target object and the UAV, w ₁ , w ₂ , and w ₃ are the control parameters of the system, w ₁ , w ₂ , and w ₃ usually take 0.5, and v _Tx , v _Ty , v _Tz is the moving speed of the target object in the x, y, and z directions respectively. When the target object is a stationary target object, v _Tx , v _Ty , and v _Tz are all 0, and ρ is the height of the target object.

The moving speeds v _Tx , v _Ty , and v _Tz of the target object in the x, y, and z directions can be calculated by the optical flow sensor mounted on the drone to obtain the moving speeds of the target object in the x, y, and z directions.

130. Control the UAV to track the target object based on the planned path.

While controlling the UAV to track the target object based on the planned path, continuously detect and acquire real-time relative position information between the target object and the UAV, so as to adjust the UAV's planned path for tracking the target object in real time, thereby Realize that the drone can quickly and accurately catch up with the target object.

140. When the relative distance between the drone and the target object reaches a set threshold, control the drone and the mechanical arm to grab the target object.

Usually, the relative distance between the UAV and the target object specifically refers to the relative distance in the Z direction, that is, the UAV first tracks the target object on the horizontal plane, and when the UAV and the target object are kept at When on the same horizontal plane, approach the target object in the vertical direction.

The method for the UAV to capture the target object provided by this embodiment is to obtain the relative depth information between the target object and the UAV in real time through the binocular camera, and then obtain the UAV according to the preset trajectory planning according to the depth information. Track the path of the target object, and then control the drone to track the target object. When the drone is close to the target object, control the movement of the drone and the mechanical arm, so that the drone can track the target object without a motion capture system. Effective grasping, and effective grasping for moving target objects.

Embodiment two

FIG. 5 is a schematic flowchart of a method for a drone to grab a target object according to Embodiment 2 of the present invention. On the basis of the above-mentioned embodiments, this embodiment optimizes the above-mentioned step 140, and the advantage of the optimization is to further improve the accuracy of the UAV grabbing the target object. Referring to FIG. 5 for details, the method includes: .

510. Acquiring relative position information between the target object and the drone in real time.

520. Determine a planned path for the drone to track the target object according to the relative position information.

530. Control the UAV to track the target object based on the planned path.

540. When the relative distances between the drone and the target object in the x-direction and the y-direction reach a first set threshold, control the robotic arm of the drone to adjust its state so as to be ready for grasping.

Specifically, at this time, the mechanical arm that mainly controls the drone is adjusted to the grasping state. For example, refer to the structural schematic diagram of the UAV mechanical arm shown in FIG. 62 is folded together, and simultaneously mechanical claw 63 and 64 are also the state of gathering. When the UAV catches up with the target object on the horizontal plane, that is, when the relative distance between the UAV and the target object in the x direction and the y direction reaches the first set threshold, control the upper arm 61 and the lower arm 62 of the mechanical arm Stretch out, control mechanical claw 63 and 64 to open simultaneously. The control of the state of the mechanical arm is specifically realized by controlling the rotation angle of each motor of the mechanical arm.

At this time, adjusting the state of the robotic arm compared to adjusting the state of the robotic arm when the drone is also very close to the target object in the z direction can further improve the accuracy of the drone grabbing the target object. If the drone is in the z direction It is also very close to the target object and then adjust the mechanical arm, it is easy to miss the best grasping time, especially when the target object is a moving object, the effect is more obvious.

550. When the state adjustment of the mechanical arm of the drone is completed, control the drone to descend.

560. When the drone descends to a set height, and the relative distance between the drone and the target object in the x-direction and y-direction reaches the first set threshold, control the drone and the mechanical arm to grab the the target object.

Specifically, the control of the drone and the mechanical arm to grab the target object includes:

Controlling the UAV and the robotic arm to grab the target object based on the adaptive sliding film control algorithm, wherein the control amount for controlling the UAV and the robotic arm to grab the target object includes:

q _k ′=q _d ′+λe

Among them, F represents the lift force of the UAV, τ _x , τ _y and τ _z respectively represent the three torques of the UAV about the x, y, and z axes in the UAV body coordinate system, and τ _n×1 is zero The control amount of the rotation angle of n motors on the man-machine manipulator can be equipped with manipulators with different degrees of freedom according to the needs of specific scenarios. The control of the manipulator can be realized only by changing the specific value of n, so that the system has Strong scalability; R, Q, I are the transformation matrix of the system, is the roll angle and pitch angle of the UAV, Ψ is the yaw angle of the UAV, is the prediction and estimation of the system matrix, A and K are positive definite gain matrices of the system, s is the synovial surface, q _d is the expected state matrix of the UAV manipulator composite system, λ is a positive definite matrix, e is the UAV manipulator The error matrix between the actual state and the expected state of the composite system, τ ₍₃₎ represents the third quantity in the matrix τ, τ _(n+6) represents the n+6th quantity in the matrix τ, and the matrix τ is a A vector with multiple rows and one column, sgn(x) is a sign function, when x>0, sgn(x)=1; when x<0, sgn(x)=-1; when x=0, sgn(x )=0. Fig. 7 shows the schematic structural view of unmanned aerial vehicle and three-degree-of-freedom mechanical arm, wherein, label 710 represents the body of unmanned aerial vehicle, label 720 represents mechanical arm, η ₁ , η ₂ and η ₃ represent respectively control mechanical arm action The rotation angle of the motor, θ is the pitch angle of the UAV, f represents the total lift of the UAV, f ₁ and f ₂ represent the lift generated by the propeller rotation at the corresponding position, and M3 represents the torque to control the pitch angle θ of the UAV, L ₁ , L ₂ and L ₃ represent the length of the corresponding section of the manipulator, P represents the position of the UAV in the world inertial coordinate system, P ₁ , P ₂ and P ₃ represent the corresponding manipulator arm in the world inertial coordinate system position of the linkage.

Further, when the control drone captures the target object, it also includes:

Control the UAV to carry the target object to the preset position to complete the capture of the target object.

The method for grabbing the target object by the drone provided in this embodiment, when the drone catches up with the target object on the horizontal plane, starts to control the adjustment state of the robotic arm of the drone, and when the adjustment state of the robotic arm of the drone is completed, Then control the UAV to descend. When it descends to the set height, control the movement of the UAV and the mechanical arm to grab the target object, which improves the accuracy of the UAV to grab the target object. By using the adaptive sliding film control algorithm Control the UAV and the robotic arm system to grab the target object, which improves the anti-interference performance and robustness of the entire system; and the system is highly scalable, and can be equipped with different degrees of freedom of robotic arms and robotic arms according to the needs of specific scenarios. claw.

On the basis of the above technical solution, taking a target object moving in the air as an example, Figure 8 provides a schematic flow chart of another method for a UAV to grab a target object, as shown in Figure 8, the method includes:

810. The drone takes off.

The UAV first takes off to the set height, and can hover or not hover to detect the target through the camera, predict the relative position of the target and the UAV, and feed back the detected data information to the controller, so that the control The controller controls the UAV to track the target object on the horizontal plane.

820. The camera detects the target object.

830. Predict the relative position.

840. UAV horizontal plane tracking.

850. Determine whether the drone catches up with the target on the horizontal plane, that is, determine whether Δx(t)≈0 and Δy(t)≈0, if yes, continue to execute step 860, otherwise return to step 820 to continue sequential execution.

Among them, Δx(t) represents the relative distance between the UAV and the target in the x direction, and Δy(t) represents the relative distance between the UAV and the target in the y direction.

860. Adjust the state of the mechanical arm.

When the UAV catches up with the target on the horizontal plane, keep the UAV directly above (or directly below) the target and adjust the state of the mechanical arm.

870. Determine whether the mechanical state adjustment is completed, if yes, continue to execute step 880, otherwise return to step 820 to continue sequential execution.

880. The drone descends.

After the state adjustment of the mechanical arm is completed, the UAV begins to descend and approach the target object.

890. Determine whether the drone has descended to the set height and the drone is at the same level as the target, if yes, continue to execute step 8910, otherwise return to step 820 to continue sequential execution.

8910. Robotic arm grabbing.

When the drone descends to the set height, it controls the robotic arm to grab the target.

8920. Fly to the target location.

Finally, the drone carries the target and flies to the preset position, thereby completing the grabbing of the moving target by the robotic arm of the drone.

In the process of controlling the robot arm to grab the target, keep real-time detection of the position error between the drone and the target, that is, step 8930, detect the position error between the drone and the target in real time through the sensor, and control The controller controls the grasping action of the robotic arm in real time according to the error.

In the embodiment of the present invention, by designing a vision-based method for the UAV to grab the target object, the UAV is no longer affected by the environment, and can autonomously and accurately grab the moving object, and the stability and robustness of the system The flexibility enables the UAV to adapt to various harsh situations autonomously. At the same time, the scope of application of drones is also wider. While being able to capture stationary targets, it can not only capture moving targets on the ground, but also capture moving targets in the air. In this way, in situations where humans or other traditional UAVs cannot operate, such as flood relief, aerial pick-up and other fields, the method for grabbing target objects by UAVs provided by the embodiments of the present invention can be successfully used to solve the problem.

Embodiment three

FIG. 9 is a schematic structural diagram of a device for grabbing a target object by a drone provided in Embodiment 3 of the present invention. Referring to FIG. 9 , the device includes: an acquisition module 910 , a determination module 920 , a tracking module 930 and a capture module 940 ;

Wherein, the acquisition module 910 is used to acquire the relative position information between the target object and the drone in real time; the determination module 920 is used to determine the planned path of the drone to track the target object according to the relative position information; the tracking module 930 is used to control The drone tracks the target object based on the planned path; the grasping module 940 is used to control the drone and the mechanical arm when the relative distance between the drone and the target object reaches a set threshold to grab the target object.

The device for grabbing a target object by a drone provided in this embodiment obtains the relative depth information between the target object and the drone in real time through a binocular camera, and then obtains the drone according to the preset trajectory planning according to the depth information. Track the path of the target object, and then control the drone to track the target object. When the drone is close to the target object, control the movement of the drone and the mechanical arm, so that the drone can track the target object without a motion capture system. Effective grasping, and effective grasping for moving target objects.

Embodiment Four

FIG. 10 is a schematic structural diagram of an electronic device provided by Embodiment 4 of the present invention. As shown in Figure 10, the electronic device includes: a first processor 1070, a first memory 1071, and a computer program stored on the first memory 1071 and operable on the first processor 1070; wherein, the first processor 1070 The number can be one or more, and a first processor 1070 is taken as an example in FIG. method. As shown in FIG. 10 , the electronic device may further include a first input device 1072 and a first output device 1073 . The first processor 1070, the first memory 1071, the first input device 1072, and the first output device 1073 may be connected via a bus or in other ways, and connection via a bus is taken as an example in FIG. 10 .

As a computer-readable storage medium, the first memory 1071 can be used to store software programs, computer-executable programs and modules, such as the device/module for a drone to grab a target object in the embodiment of the present invention (for example, a drone grabs acquisition module 910 and determination module 920 etc. in the device for obtaining the target object). The first processor 1070 executes various functional applications and data processing of the electronic device by running the software programs, instructions and modules stored in the first memory 1071 , that is, realizes the above-mentioned method for the drone to grab the target object.

The first memory 1071 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required by a function; the data storage area may store data created according to the use of the terminal, and the like. In addition, the first memory 1071 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage devices. In some examples, the first storage 1071 may further include storages that are set remotely relative to the first processor 1070, and these remote storages may be connected to electronic devices/storage media through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The first input device 1072 can be used to receive input numbers or character information, and generate key signal input related to user settings and function control of the electronic device. The first output device 1073 may include a display device such as a display screen.

Embodiment five

Embodiment 5 of the present invention also provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute a method for a drone to grab a target object when executed by a computer processor. The method includes:

Real-time acquisition of relative position information between the target object and the UAV;

Determine the planned path of the UAV to track the target object according to the relative position information;

controlling the UAV to track the target object based on the planned path;

When the relative distance between the drone and the target object reaches a set threshold, the drone and the mechanical arm are controlled to grab the target object.

Of course, a storage medium containing computer-executable instructions provided by an embodiment of the present invention, the computer-executable instructions are not limited to the method operations described above, and can also perform the drone grabbing provided by any embodiment of the present invention. Operations related to the target object.

Through the above description about the implementation mode, those skilled in the art can clearly understand that the present invention can be realized by means of software and necessary general-purpose hardware, and of course it can also be realized by hardware, but in many cases the former is a better implementation mode . In this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, Read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), flash memory (FLASH), hard disk or optical disc, etc., including several instructions to make a computer device (which can be a personal computer, store media, or network equipment, etc.) to implement the various embodiments of the present invention.

Note that the above are only preferred embodiments of the present invention and applied technical principles. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and can also include more other equivalent embodiments without departing from the concept of the present invention, and the present invention The scope is determined by the scope of the appended claims.

Claims (10)

1. A method for unmanned aerial vehicle to grab target object, it is characterized in that, comprising: Real-time acquisition of relative position information between the target object and the UAV; Determine the planned path of the UAV to track the target object according to the relative position information; controlling the UAV to track the target object based on the planned path; When the relative distance between the drone and the target object reaches a set threshold, the drone and the mechanical arm are controlled to grab the target object. 2. The method according to claim 1, wherein the real-time acquisition of relative position information between the target object and the unmanned aerial vehicle comprises: Determine the abscissas corresponding to the imaging points of the target object on the left and right imaging planes corresponding to the binocular cameras loaded on the drone; calculating the distance between the imaging points of the target object on the left and right imaging planes based on the abscissa; According to the geometric relationship between the left and right imaging planes, in combination with the parameters of the binocular camera and the distance between the imaging points, calculate the relative depth information between the target object and the UAV; Wherein, the parameters of the binocular camera include camera focal length and camera center distance. 3. The method according to claim 2, wherein said determining the planned path of the drone tracking the target object according to the relative position information comprises: Based on the pre-designed dynamic trajectory planning based on the relative depth information, calculate the planned path of the UAV tracking the target object in real time; Wherein, the pre-designed dynamic trajectory planning is: x _d (t)＝Δx(t)exp(-w ₁ *t)+∫v _Tx dt y _d (t)=Δy(t)exp(-w ₂ *t)+∫v _Ty dt z _d (t)=Δz(t)exp(-w ₃ *t)+∫v _Tz dt+ρ; x _d (t), y _d (t), z _d (t) represent the planned path of the UAV in the directions of x, y, and z respectively, t represents the time, Δx(t), Δy(t), Δz( t) is the relative depth information between the target object and the drone, w ₁ , w ₂ , and w ₃ are the control parameters of the system, and v _Tx , v _Ty , v _Tz are the target object in the x, y, and z directions, respectively. When the target object is a stationary target object, v _Tx , v _Ty , and v _Tz are all 0, and ρ is the height of the target object. 4. The method according to claim 3, wherein, when the target object is a moving target object, before determining the planned path of the UAV tracking the target object according to the relative position information, further comprising: The moving speed of the target object in the x, y, and z directions is calculated by the optical flow sensor mounted on the drone. 5. The method according to claim 1, wherein when the relative distance between the drone and the target object reaches a set threshold, the drone and the mechanical arm are controlled to grab the target object ,include: When the relative distance between the drone and the target object in the x direction and the y direction reaches a first set threshold, control the mechanical arm of the drone to adjust the state to prepare for grabbing; When the adjustment state of the robotic arm of the UAV is completed, the UAV is controlled to descend; When the drone drops to a set height, and the relative distance between the drone and the target object in the x direction and the y direction reaches the first set threshold, control the drone and the mechanical arm to grab the target object. 6. The method according to claim 5, wherein the controlling the drone and the mechanical arm to grab the target object comprises: Controlling the UAV and the robotic arm to grab the target object based on the adaptive sliding film control algorithm, wherein the control amount for controlling the UAV and the robotic arm to grab the target object includes: q _k ′=q _d ′+λe Among them, F represents the lift force of the UAV, τ _x , τ _y and τ _z respectively represent the three torques of the UAV about the x, y, and z axes in the UAV body coordinate system, and τ _n×1 is zero The control quantities of the rotation angles of n motors on the human-machine manipulator, R, Q, I are the transformation matrix of the system, θ _d , is the roll angle and pitch angle of the UAV, Ψ is the yaw angle of the UAV, is the prediction and estimation of the system matrix, A and K are positive definite gain matrices of the system, s is the synovial surface, q _d is the expected state matrix of the UAV manipulator composite system, λ is a positive definite matrix, e is the UAV manipulator The error matrix between the actual state and the expected state of the composite system. 7. The method according to any one of claims 1-5, characterized in that, after the control drone catches the target object, it also includes: Control the UAV to carry the target object to the preset position. 8. A device for an unmanned aerial vehicle to grab a target object, wherein the device comprises: The obtaining module is used to obtain the relative position information between the target object and the UAV in real time; A determining module, configured to determine the planned path of the UAV tracking the target object according to the relative position information; a tracking module, configured to control the UAV to track the target object based on the planned path; The grabbing module is used to control the action of the drone and the mechanical arm to grab the target object when the relative distance between the drone and the target object reaches a set threshold. 9. An electronic device, comprising a first memory, a first processor, and a computer program stored on the memory and operable on the first processor, characterized in that, when the first processor executes the computer program Realize the method for grabbing a target object by an unmanned aerial vehicle as described in any one of claims 1-7. 10. A storage medium containing computer-executable instructions, the computer-executable instructions implement the method for grabbing a target object by a drone according to any one of claims 1-7 when executed by a computer processor.