CN119596915B - UAV tactile teleoperation control method, device, equipment and medium - Google Patents
UAV tactile teleoperation control method, device, equipment and mediumInfo
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- CN119596915B CN119596915B CN202411767512.0A CN202411767512A CN119596915B CN 119596915 B CN119596915 B CN 119596915B CN 202411767512 A CN202411767512 A CN 202411767512A CN 119596915 B CN119596915 B CN 119596915B
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/20—Control system inputs
- G05D1/22—Command input arrangements
- G05D1/221—Remote-control arrangements
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Abstract
本申请涉及一种无人机触觉遥操作控制方法、装置、设备及介质，方法包括：位置增量型运动控制器获取目标无人机的当前位置信息、操纵杆位移增量以及操纵杆工作空间的最大半径，根据操纵杆位移增量以及操纵杆工作空间的最大半径与操纵杆位移增量之间的比值以确定目标无人机相对应的位移增量；位置增量型运动控制器根据操纵杆的初始位置以及操纵杆位移增量计算确定目标无人机的避障位姿，并根据当前位置信息确定目标无人机的目标位置以及偏航角；微分平坦控制器根据避障位姿、目标位置以及偏航角生成目标无人机相对应的飞行控制指令，以驱动目标无人机进行自动避障，以完成无人机触觉遥操作的控制。本申请显著提高了无人机在复杂环境中的操作安全性。
The present application relates to a method, apparatus, device, and medium for tactile teleoperation control of a drone. The method includes: a position-increment motion controller obtains the current position information of a target drone, a joystick displacement increment, and the maximum radius of the joystick's workspace, and determines the corresponding displacement increment of the target drone based on the ratio between the joystick displacement increment and the maximum radius of the joystick's workspace and the joystick displacement increment; the position-increment motion controller calculates and determines the obstacle avoidance posture of the target drone based on the initial position of the joystick and the joystick displacement increment, and determines the target position and yaw angle of the target drone based on the current position information; a differential flat controller generates flight control instructions corresponding to the target drone based on the obstacle avoidance posture, target position, and yaw angle, to drive the target drone to automatically avoid obstacles and complete the control of the drone's tactile teleoperation. This application significantly improves the operational safety of drones in complex environments.
Description
Technical Field
The application relates to the field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle touch teleoperation control method, a corresponding device, electronic equipment and a computer readable storage medium.
Background
Unmanned aerial vehicle touch teleoperation is widely applied to complex environments, particularly under task scenes which are difficult to realize in full automation, such as collapse building risk inspection after natural disasters, dangerous area detection, industrial equipment maintenance and the like. In general, teleoperational systems can be divided into two parts, motion control and force feedback. The motion control part includes a method of mapping position information or position change rate information of the haptic handles to position commands and speed commands of the unmanned aerial vehicle, and a direct control method of directly mapping to torque and euler angles of the unmanned aerial vehicle.
In the aspect of haptic force feedback, the traditional force feedback method is mainly based on some physical models, including force-stiffness feedback, artificial potential field force feedback and the like. These methods provide a relatively intuitive feedback effect through a physical model, but have the disadvantage of poor adaptability to complex environments, especially in variable or dynamic environments, where the feedback effect is not ideal.
In summary, the present inventors have made a corresponding search for solving the problem that the haptic force feedback in the prior art has poor adaptability to complex environments, especially in a changeable or dynamic environment, and the feedback effect is not ideal enough.
Disclosure of Invention
The present application is directed to solving the above-mentioned problems and providing a method for controlling haptic teleoperation of an unmanned aerial vehicle, a corresponding apparatus, an electronic device, and a computer-readable storage medium.
In order to meet the purposes of the application, the application adopts the following technical scheme:
One of the objects of the present application is to propose a control method for haptic teleoperation of an unmanned aerial vehicle, comprising:
The method comprises the steps that a target unmanned aerial vehicle is detected to enter a non-safety area to respond to an unmanned aerial vehicle touch teleoperation control instruction, a model prediction controller in touch control equipment adopts a preset second derivative to determine feedback force for driving a control lever in the touch control equipment to generate displacement change according to a position kinematic model, a gesture kinematic model, a function model and an obstacle function corresponding to the model prediction controller corresponding to the target unmanned aerial vehicle, and the control lever displacement increment of the control lever is determined according to the feedback force;
The position increment type motion controller obtains the current position information of the target unmanned aerial vehicle, the operating lever displacement increment and the maximum radius of the operating lever working space, and determines the corresponding displacement increment of the target unmanned aerial vehicle according to the operating lever displacement increment and the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment;
The position increment type motion controller calculates and determines the obstacle avoidance pose of the target unmanned aerial vehicle according to the initial position of the control lever and the displacement increment of the control lever, and determines the target position and the yaw angle of the target unmanned aerial vehicle according to the current position information;
And the differential flat controller generates a flight control instruction corresponding to the target unmanned aerial vehicle according to the obstacle avoidance pose, the target position and the yaw angle so as to drive the target unmanned aerial vehicle to automatically avoid the obstacle, thereby completing the control of the unmanned aerial vehicle touch teleoperation.
Optionally, the step of determining, by using a model predictive controller in the haptic control device, a feedback force for driving a joystick in the haptic control device to change in displacement according to a position kinematic model, an attitude kinematic model, a function model corresponding to the model predictive controller, and an obstacle function corresponding to the target unmanned aerial vehicle by using a preset second derivative, includes:
first, the global coordinate system of the system is F W:{xW,yW,zW, and the organism reference system is F B：{xB,yB,zB. Wherein B represents a variable in the body coordinate system, the other variables are represented in the world (inertial) coordinate system, and the rotation matrix from the world coordinate system F w to the body coordinate system F B is represented by quaternion q= [ q w,qx,qy,qz ] ∈so (3);
the expression of the position kinematic model is as follows:
wherein ζ w is the displacement of the unmanned aerial vehicle in the world coordinate system, and v w is the speed of the unmanned aerial vehicle in the world coordinate system;
The expression of the gesture kinematic model is as follows:
w=W·ΩB,
wherein w represents three attitude angles of the target unmanned aerial vehicle, and comprises Omega B＝[p,q,r]T, W is expressed as angular velocity in world coordinate system.
Optionally, the step of determining, by using a model predictive controller in the haptic control device, a feedback force for driving a joystick in the haptic control device to change in displacement according to a position kinematic model, an attitude kinematic model, a function model corresponding to the model predictive controller, and an obstacle function corresponding to the target unmanned aerial vehicle by using a preset second derivative, includes:
The expression of the function model corresponding to the model predictive controller comprises the following steps:
Xk＝xk-xk,r,
Uk＝uk-uk,r,
XN＝xn-xn,r,
s.t.u∈[umin,umax],
x0＝xinit,
xk+1＝f(xk,uk),
Wherein, the Expressed as a state space, k is a time step, T is a transpose, u is defined as a set of v w and Ω B, x k+1＝f(xk,uk) is a kinematic model of the drone, Q u is a weighting matrix of the input u, Q and Q n are diagonal matrices with the weighting matrix as diagonal elements, and the subscript r represents the desired value.
Optionally, the step of determining, by using a model predictive controller in the haptic control device, a feedback force for driving a joystick in the haptic control device to change in displacement according to a position kinematic model, an attitude kinematic model, a function model corresponding to the model predictive controller, and an obstacle function corresponding to the target unmanned aerial vehicle by using a preset second derivative, includes:
the expression of the barrier function is:
d(x)-psec≥0,
Where d (x) represents the physical region of the secure space, and p sec represents the secure region threshold;
the expression of the second derivative is:
Where K f1、Kf2 and K f3 are constant parameters for adjusting the magnitude of the haptic feedback.
Optionally, determining the corresponding displacement increment of the target unmanned aerial vehicle according to the joystick displacement increment and the ratio between the maximum radius of the joystick working space and the joystick displacement increment comprises:
the expression of the displacement increment corresponding to the target unmanned aerial vehicle is as follows:
Wherein a represents an input signal of a touch device button, K m is a scaling matrix with positive diagonal line, the scaling matrix is used for controlling displacement increment of the unmanned aerial vehicle in different directions, q j (t) represents a distance between the tail end of the operating lever and the origin of the operating lever working space, delta q s (t) represents a corresponding displacement increment of the unmanned aerial vehicle, r represents the maximum radius of the operating lever working space, when the operating lever displacement increment q j (t) is smaller than the maximum radius r of the operating lever working space, the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment is larger than 1, and the corresponding displacement increment of the unmanned aerial vehicle is the product of the scaling matrix with positive diagonal line and the operating lever displacement increment.
Optionally, the step of determining the obstacle avoidance pose of the target unmanned aerial vehicle by the position incremental motion controller according to the initial position of the operating lever and the operating lever displacement increment calculation includes:
the expression of the obstacle avoidance pose of the target unmanned aerial vehicle is as follows:
Wherein, ζ n represents the initial position of the control lever, N represents the control times of the control lever, and ζ (t) represents the obstacle avoidance pose of the target unmanned aerial vehicle.
Optionally, the step of determining, by using a model predictive controller in the haptic control device, a feedback force for driving a joystick in the haptic control device to change in displacement according to a position kinematic model, an attitude kinematic model, a function model corresponding to the model predictive controller, and an obstacle function corresponding to the target unmanned aerial vehicle by using a preset second derivative, includes:
And responding to the safety obstacle avoidance warning command, outputting the feedback force to a force feedback controller in the driving touch control equipment so as to enable an operator to sense the feedback force, and warning the operator to drive the target unmanned aerial vehicle away from a non-safety area.
A haptic teleoperation control device for an unmanned aerial vehicle according to another object of the present application comprises:
The feedback force determining module is used for detecting that the target unmanned aerial vehicle enters a non-safety area and responding to an unmanned aerial vehicle touch teleoperation control instruction, and a model prediction controller in the touch control equipment adopts a preset second derivative to determine feedback force for driving a control lever in the touch control equipment to generate displacement change according to a position kinematic model, a gesture kinematic model, a function model and an obstacle function corresponding to the model prediction controller corresponding to the target unmanned aerial vehicle, and determines the control lever displacement increment of the control lever according to the feedback force;
The displacement increment determining module is set to obtain the current position information of the target unmanned aerial vehicle, the displacement increment of the operating lever and the maximum radius of the operating lever working space by the position increment type motion controller, and the corresponding displacement increment of the target unmanned aerial vehicle is determined according to the operating lever displacement increment and the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment;
The obstacle avoidance pose determining module is arranged as a position increment type motion controller for determining the obstacle avoidance pose of the target unmanned aerial vehicle according to the initial position of the operating lever and the displacement increment calculation of the operating lever, and determining the target position and the yaw angle of the target unmanned aerial vehicle according to the current position information;
and the teleoperation control module is arranged to generate a flight control instruction corresponding to the target unmanned aerial vehicle by the differential flat controller according to the obstacle avoidance pose, the target position and the yaw angle so as to drive the target unmanned aerial vehicle to automatically avoid the obstacle and complete the control of the unmanned aerial vehicle touch teleoperation.
An electronic device adapted to another object of the present application comprises a central processor and a memory, said central processor being adapted to invoke the steps of running a computer program stored in said memory for performing the method of controlling haptic teleoperation of a drone according to the present application.
A computer-readable storage medium adapted to another object of the present application stores, in the form of computer-readable instructions, a computer program implemented according to the unmanned aerial vehicle haptic teleoperation control method, which when invoked by a computer, performs the steps comprised by the corresponding method.
Compared with the prior art, the application aims at the problems of poor adaptability of the tactile force feedback to complex environments, and particularly unsatisfactory feedback effect in changeable or dynamic environments, and the like in the prior art, and comprises but is not limited to the following beneficial effects:
firstly, the unmanned aerial vehicle touch teleoperation control method improves the control performance of the system in a complex environment, is suitable for tasks requiring high-precision and fine operation, such as accurate positioning, inspection, carrying and the like, remarkably improves the operation safety of the unmanned aerial vehicle in the complex environment, reduces risks caused by control errors or environmental uncertainty, and provides higher safety guarantee for operators, particularly in dangerous areas or highly uncertain environments.
Secondly, the unmanned aerial vehicle touch teleoperation control method reduces the cognitive load of an operator on control through position increment type motion control and smooth force feedback, so that the operator can concentrate on tasks without paying attention to complicated control details, and meanwhile, the system can easily finish operation when facing high-difficulty tasks through intelligent obstacle avoidance and dynamic feedback optimization.
Thirdly, according to the unmanned aerial vehicle touch teleoperation control method, the system can improve the control precision and the reliability of unmanned aerial vehicle execution tasks in complex task environments through accurate control and force feedback optimization. For example, in medical transportation, hazardous area reconnaissance, etc., fine control and reliable feedback can ensure successful completion of the task, minimizing the risk of accident.
Furthermore, the unmanned aerial vehicle touch teleoperation control method based on position increment and model predictive control optimization effectively improves the controllability, the perceptibility, the safety and the operation precision of the system through various innovations such as precise control, smooth force feedback, intelligent obstacle avoidance and the like, not only enhances the operation performance of the unmanned aerial vehicle in a complex environment, but also obviously lightens the burden of operators and improves the working efficiency, thereby providing a more superior solution for various teleoperation tasks with high precision and high risk.
Drawings
The foregoing and/or additional aspects and advantages of the application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is an exemplary network architecture for use with the unmanned aerial vehicle haptic teleoperation control method of the present application;
FIG. 2 is a flow chart of a method for controlling haptic teleoperation of a drone according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a joystick displacement change in a haptic control device according to an embodiment of the present application;
FIG. 4 is a schematic block diagram of a haptic teleoperation control device for an unmanned aerial vehicle in an embodiment of the present application;
Fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the application.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by those skilled in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.
It will be understood by those skilled in the art that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs unless defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
As used herein, "client," "terminal device," and "terminal device" are understood by those skilled in the art to include both devices that include only wireless signal receivers without transmitting capabilities and devices that include receiving and transmitting hardware capable of two-way communication over a two-way communication link. Such devices may include cellular or other communication devices such as Personal computers, tablet computers, cellular or other communication devices having a single-wire or multi-wire display or no multi-wire display, PCS (Personal Communications Service, personal communication system) which may combine voice, data processing, facsimile and/or data communication capabilities, PDA (Personal DIGITAL ASSISTANT ) which may include a radio frequency receiver, pager, internet/intranet access, web browser, notepad, calendar and/or GPS (Global Positioning System ) receiver, conventional laptop and/or palmtop computer or other device having and/or including a radio frequency receiver. As used herein, "client," "terminal device" may be portable, transportable, installed in a vehicle (aeronautical, maritime, and/or land-based), or adapted and/or configured to operate locally and/or in a distributed fashion, at any other location(s) on earth and/or in space. As used herein, a "client," "terminal device," or "terminal device" may also be a communication terminal, an internet terminal, or a music/video playing terminal, for example, may be a PDA, a MID (Mobile INTERNET DEVICE ), and/or a Mobile phone with a music/video playing function, or may also be a device such as a smart tv, a set top box, or the like.
The application refers to hardware such as a server, a client, a service node, and the like, which essentially is an electronic device with personal computer and other functions, and is a hardware device with necessary components disclosed by von neumann principles such as a central processing unit (including an arithmetic unit and a controller), a memory, an input device, an output device, and the like, wherein a computer program is stored in the memory, and the central processing unit calls the program stored in the memory to run, executes instructions in the program, and interacts with the input and output devices, thereby completing specific functions.
It should be noted that the concept of the present application, called "server", is equally applicable to the case of server clusters. The servers should be logically partitioned, physically separate from each other but interface-callable, or integrated into a physical computer or group of computers, according to network deployment principles understood by those skilled in the art. Those skilled in the art will appreciate this variation and should not be construed as limiting the implementation of the network deployment approach of the present application.
One or more technical features of the present application, unless specified in the clear, may be deployed either on a server for implementation and the client remotely invokes an online service interface provided by the acquisition server for implementation of the access, or may be deployed and run directly on the client for implementation of the access.
The neural network model cited or possibly cited in the application can be deployed on a remote server and can be used for implementing remote call on a client, or can be deployed on a client with sufficient equipment capability for direct call, unless specified by plaintext, and in some embodiments, when the neural network model runs on the client, the corresponding intelligence can be obtained through migration learning so as to reduce the requirement on the running resources of the hardware of the client and avoid excessively occupying the running resources of the hardware of the client.
The various data related to the present application, unless specified in the plain text, may be stored either remotely in a server or in a local terminal device, as long as it is suitable for being invoked by the technical solution of the present application.
It will be appreciated by those skilled in the art that the various methods of the application, although described based on the same concepts as one another in common, may be performed independently of one another unless otherwise indicated. Similarly, for the various embodiments disclosed herein, all concepts described herein are presented based on the same general inventive concept, and thus, concepts described herein with respect to the same general inventive concept, and concepts that are merely convenient and appropriately modified, although different, should be interpreted as equivalents.
The various embodiments of the present application to be disclosed herein, unless the plain text indicates a mutually exclusive relationship with each other, the technical features related to the various embodiments may be cross-combined to flexibly construct a new embodiment as long as such combination does not depart from the inventive spirit of the present application and can satisfy the needs in the art or solve the deficiencies in the prior art. This variant will be known to the person skilled in the art.
Referring to fig. 1, 2 and 3, in one embodiment, the method for controlling haptic teleoperation of an unmanned aerial vehicle according to the present application includes:
Step S10, detecting that a target unmanned aerial vehicle enters a non-safety area and responding to an unmanned aerial vehicle touch teleoperation control instruction, wherein a model prediction controller in a touch control device adopts a preset second derivative to determine a feedback force for driving a control lever in the touch control device to generate displacement change according to a position kinematic model, a gesture kinematic model, a function model and an obstacle function corresponding to the model prediction controller corresponding to the target unmanned aerial vehicle, and determining a control lever displacement increment of the control lever according to the feedback force;
The unmanned aerial vehicle touch teleoperation control system can detect that a target unmanned aerial vehicle enters a non-safety area and responds to an unmanned aerial vehicle touch teleoperation control instruction, a model prediction controller in touch control equipment adopts a preset second derivative to determine feedback force for driving a control lever in the touch control equipment to generate displacement change according to a position kinematic model, a gesture kinematic model, a function model and an obstacle function corresponding to the model prediction controller corresponding to the target unmanned aerial vehicle, and determines the control lever displacement increment of the control lever according to the feedback force;
Specifically, the unmanned aerial vehicle touch teleoperation control system comprises a system master end and a system slave end, wherein the system master end is a touch control device, the touch control device comprises three-degree-of-freedom falcon (novant) touch devices and the like, the force feedback frequency of the three-degree-of-freedom falcon (novant) touch devices is 1kHz, the system slave end is a target unmanned aerial vehicle, the target unmanned aerial vehicle can be a four-rotor unmanned aerial vehicle, and the sensor sampling frequency is 1kHz. The master and slave terminals communicate by adopting an ROS system under a Linux system, and write control algorithms by using C++ and Python languages.
First, a system master end coordinate system and a system slave end coordinate system are established, the master end coordinate system is [ x j,yj,zj ] under the world coordinate system [ x W,yW,zW ], the slave end coordinate system is [ x B,yB,zB ], and the rotation matrix from the world coordinate system to the slave end coordinate system is R (q), wherein q is a quaternion [ q x,qy,qz,qw ].
In some embodiments, the tri-axial displacement increment of the joystick center point is mapped to a drone position increment. When a control button in the touch control equipment is pressed, the control rod does not change the position of the unmanned aerial vehicle any more, the unmanned aerial vehicle cannot be controlled any more at the moment, the control rod can be moved to any proper position at the moment, new position increment information can be continuously transmitted to the unmanned aerial vehicle after the control button in the touch control equipment is released, position superposition is achieved, and therefore the unmanned aerial vehicle can move in an unbounded mode.
In some embodiments, the step of determining the feedback force driving the joystick in the haptic control device to change in displacement by using a model predictive controller in the haptic control device according to a position kinematic model, an attitude kinematic model, a function model corresponding to the model predictive controller and an obstacle function corresponding to the target unmanned aerial vehicle by using a preset second derivative includes:
The unmanned aerial vehicle touch teleoperation control system can respond to the safety obstacle avoidance warning instruction, and output the feedback force to a force feedback controller in the driving touch control equipment so that an operator senses the feedback force to warn the operator to drive the target unmanned aerial vehicle away from a non-safety area.
The application adopts a differential flat controller as an intermediate converter to realize direct control of a control lever to the position of the unmanned aerial vehicle, and in addition, the constraint condition of the model predictive controller is introduced to control barrier constraint, when the unmanned aerial vehicle is driven to fly to an unsafe area by an operator, the controller can generate a repulsive force far away from the obstacle to warn the operator to react, and when the unmanned aerial vehicle is extremely close to the unsafe area, the autonomous obstacle avoidance reaction can be generated.
In a specific embodiment, the global coordinate system of the system is first constructed to be F W:{xW,yW,zW, and the body reference system is constructed to be F B：{xB,yB,zB. Wherein B represents a variable in the body coordinate system, the other variables are represented in the world (inertial) coordinate system, and the rotation matrix from the world coordinate system F w to the body coordinate system F B is represented by quaternion q= [ q w,qx,qy,qz ] ∈so (3);
the expression of the position kinematic model is as follows:
wherein ζ w is the displacement of the unmanned aerial vehicle in the world coordinate system, and v w is the speed of the unmanned aerial vehicle in the world coordinate system;
The expression of the gesture kinematic model is as follows:
w=W·ΩB,
Wherein w represents three attitude angles (Euler angles) of the target unmanned aerial vehicle, and there are Omega B＝[p,q,r]T, W is expressed as angular velocity in world coordinate system, expressed as:
The expression of the function model corresponding to the model predictive controller comprises the following steps:
Xk＝xk-xk,r,
Uk＝uk-uk,r,
XN＝xn-xn,r,
s.t.u∈[umin,umax],
x0＝xinit,
xk+1＝f(xk,uk),
Wherein, the Expressed as a state space, k is a time step, T is a transpose, u is defined as a set of v w and Ω B, x k+1＝f(xk,uk) is a kinematic model of the drone, Q u is a weighting matrix of the input u, Q and Q n are diagonal matrices with the weighting matrix as diagonal elements, and the subscript r represents the desired value.
The expression of the barrier function is:
d(x)-psec≥0,
Where d (x) represents the physical region of the secure space, and p sec represents the secure region threshold;
Specifically, with reference to the control obstacle function, an obstacle constraint area is defined for the model predictive controller, and the expression is:
the function d (x) defines the physical area of the safety space, and the obstacle is equivalent to an ellipsoid;
For unmanned aerial vehicle systems, the general expression for obstacle surfaces is:
To accommodate the constraints of a differential flattening controller, which uses only position as a constraint, and designs a safe area threshold p sec, the expression of the final obstacle function is:
d(x)-psec≥0。
In order to meet the requirements of the differential flatness controller, the present application only considers the position constraints of the target drone, however, it may be more advantageous to include higher derivatives of the obstacle function when designing such safety constraints for dynamic systems. To this end, the application proposes a compensation measure to generate a force feedback based on the second derivative of the input, which has an advantage for the force feedback output, the expression of the second derivative being:
Where K f1、Kf2 and K f3 are constant parameters for adjusting the magnitude of the haptic feedback.
When an operator enters an unsafe area, the model prediction controller records the current entering position as a target point, performs reverse planning and generates force feedback to expel the unmanned aerial vehicle out of the unsafe area, the tactile feedback is determined by u MPC, smoother force feedback is generated, and the force feedback and the control rod are coupled to realize the function of autonomous obstacle avoidance.
As can be seen from the above embodiments, the model predictive controller in the haptic control device uses a preset second derivative to determine a feedback force for driving the joystick in the haptic control device to change in displacement according to the position kinematic model, the gesture kinematic model, the function model corresponding to the model predictive controller and the obstacle function corresponding to the target unmanned aerial vehicle, and determines the joystick displacement increment of the joystick according to the feedback force.
Step S20, a position increment type motion controller acquires current position information of the target unmanned aerial vehicle, the operating lever displacement increment and the maximum radius of an operating lever working space, and determines a displacement increment corresponding to the target unmanned aerial vehicle according to the operating lever displacement increment and the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment;
And after determining the joystick displacement increment of the joystick according to the feedback force, a position increment type motion controller acquires the current position information of the target unmanned aerial vehicle, the joystick displacement increment and the maximum radius of a joystick working space, and determines the corresponding displacement increment of the target unmanned aerial vehicle according to the joystick displacement increment and the ratio between the maximum radius of the joystick working space and the joystick displacement increment.
In a specific embodiment, the expression of the displacement increment corresponding to the target unmanned aerial vehicle is:
Wherein a represents an input signal of a touch device button, K m is a scaling matrix with positive diagonal line, the scaling matrix is used for controlling displacement increment of the unmanned aerial vehicle in different directions, q j (t) represents a distance between the tail end of the operating lever and the origin of the operating lever working space, delta q s (t) represents a corresponding displacement increment of the unmanned aerial vehicle, r represents the maximum radius of the operating lever working space, when the operating lever displacement increment q j (t) is smaller than the maximum radius r of the operating lever working space, the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment is larger than 1, and the corresponding displacement increment of the unmanned aerial vehicle is the product of the scaling matrix with positive diagonal line and the operating lever displacement increment.
More specifically, when the input signal a of the control button of the haptic device is 0, that is, when the control button of the haptic control device is in a pressed state, the control lever does not change the position of the unmanned aerial vehicle any more, the unmanned aerial vehicle cannot be controlled any more, the control lever can be moved to any proper position at the moment, when the input signal a of the control button of the haptic device is 1, when the control button of the haptic control device is in a released state, new displacement increment is continuously transmitted to the unmanned aerial vehicle, and position superposition is realized, so that the unbounded movement of the unmanned aerial vehicle can be realized.
Step S30, a position increment type motion controller calculates and determines the obstacle avoidance pose of the target unmanned aerial vehicle according to the initial position of the operating lever and the displacement increment of the operating lever, and determines the target position and the yaw angle of the target unmanned aerial vehicle according to the current position information;
After the corresponding displacement increment of the target unmanned aerial vehicle is determined according to the joystick displacement increment and the ratio between the maximum radius of the joystick working space and the joystick displacement increment, a position increment type motion controller (DFBC controller) calculates and determines the obstacle avoidance pose of the target unmanned aerial vehicle according to the initial position of the joystick and the joystick displacement increment, and determines the target position and yaw angle of the target unmanned aerial vehicle according to the current position information, specifically, the target unmanned aerial vehicle transmits the corresponding current position information to the position increment type motion controller in the touch control equipment, and the position increment type motion controller determines the target position and yaw angle of the target unmanned aerial vehicle according to the current position information so as to avoid obstacles, and transmits the obstacle avoidance pose of the target unmanned aerial vehicle, the target position and yaw angle of the target unmanned aerial vehicle to a differential flat controller so as to generate a control command to control the movement of the unmanned aerial vehicle.
In a specific embodiment, the step of determining the obstacle avoidance pose of the target unmanned aerial vehicle by the position increment type motion controller according to the initial position of the operating lever and the operating lever displacement increment calculation includes:
the expression of the obstacle avoidance pose of the target unmanned aerial vehicle is as follows:
Wherein, ζ n represents the initial position of the control lever, N represents the control times of the control lever, and ζ (t) represents the obstacle avoidance pose of the target unmanned aerial vehicle. The obstacle avoidance pose of the target drone is expressed as the sum of each increment of displacement caused by the manipulation of the joystick and its initial position ζ n.
And S40, generating a flight control instruction corresponding to the target unmanned aerial vehicle by the differential flat controller according to the obstacle avoidance pose, the target position and the yaw angle so as to drive the target unmanned aerial vehicle to automatically avoid the obstacle and complete the control of the unmanned aerial vehicle touch teleoperation.
And after determining the target position and the yaw angle of the target unmanned aerial vehicle according to the current position information, generating a flight control instruction corresponding to the target unmanned aerial vehicle by a differential flat controller according to the obstacle avoidance pose, the target position and the yaw angle and sending the flight control instruction to the target unmanned aerial vehicle so as to drive the target unmanned aerial vehicle to automatically avoid obstacles, thereby completing the control of unmanned aerial vehicle touch teleoperation.
When no operator operates, the model predictive controller adopts a preset second derivative to determine a feedback force for driving the operating lever to change in displacement according to a position kinematic model, a gesture kinematic model and a function model corresponding to the model predictive controller, which correspond to the target unmanned aerial vehicle, so as to drive the operating lever to move to change in displacement, and determines an operating lever displacement increment of the operating lever according to the feedback force, the incremental type motion controller determines a target unmanned aerial vehicle according to the current position information, the operating lever displacement increment and the maximum radius of an operating lever working space, determines a displacement increment corresponding to the target unmanned aerial vehicle according to the operating lever displacement increment and the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment, and the position incremental type motion controller calculates and determines a target unmanned aerial vehicle obstacle avoidance position according to the initial position of the operating lever and the operating lever displacement increment, determines a target unmanned aerial vehicle obstacle avoidance angle according to the current position information, and the yaw control function, and the automatic unmanned aerial vehicle is driven by the unmanned aerial vehicle, and the automatic yaw control function is realized, and the target unmanned aerial vehicle is driven by the unmanned aerial vehicle.
As can be seen from the foregoing embodiments, compared with the prior art, the present application aims at the problems of poor adaptability of the haptic force feedback to the complex environment, especially in the changeable or dynamic environment, and the feedback effect is not ideal, and the present application includes, but is not limited to, the following beneficial effects:
firstly, the unmanned aerial vehicle touch teleoperation control method improves the control performance of the system in a complex environment, is suitable for tasks requiring high-precision and fine operation, such as accurate positioning, inspection, carrying and the like, remarkably improves the operation safety of the unmanned aerial vehicle in the complex environment, reduces risks caused by control errors or environmental uncertainty, and provides higher safety guarantee for operators, particularly in dangerous areas or highly uncertain environments.
Secondly, the unmanned aerial vehicle touch teleoperation control method reduces the cognitive load of an operator on control through position increment type motion control and smooth force feedback, so that the operator can concentrate on tasks without paying attention to complicated control details, and meanwhile, the system can easily finish operation when facing high-difficulty tasks through intelligent obstacle avoidance and dynamic feedback optimization.
Thirdly, according to the unmanned aerial vehicle touch teleoperation control method, the system can improve the control precision and the reliability of unmanned aerial vehicle execution tasks in complex task environments through accurate control and force feedback optimization. For example, in medical transportation, hazardous area reconnaissance, etc., fine control and reliable feedback can ensure successful completion of the task, minimizing the risk of accident.
Furthermore, the unmanned aerial vehicle touch teleoperation control method based on position increment and model predictive control optimization effectively improves the controllability, the perceptibility, the safety and the operation precision of the system through various innovations such as precise control, smooth force feedback, intelligent obstacle avoidance and the like, not only enhances the operation performance of the unmanned aerial vehicle in a complex environment, but also obviously lightens the burden of operators and improves the working efficiency, thereby providing a more superior solution for various teleoperation tasks with high precision and high risk.
Referring to fig. 4, an unmanned aerial vehicle haptic teleoperation control device according to one of the purposes of the present application includes a feedback force determining module 1100, a displacement increment determining module 1200, an obstacle avoidance pose determining module 1300 and a teleoperation control module 1400. The feedback force determining module 1100 is configured to detect that a target unmanned aerial vehicle enters a non-safety area and respond to a unmanned aerial vehicle touch teleoperation control instruction, and a model prediction controller in a touch control device adopts a preset second derivative to determine a feedback force for driving a joystick in the touch control device to generate displacement change according to a position kinematic model, a gesture kinematic model, a function model and an obstacle function corresponding to the model prediction controller corresponding to the target unmanned aerial vehicle, and determine a joystick displacement increment of the joystick according to the feedback force; the unmanned aerial vehicle comprises a displacement increment determining module 1200, a barrier avoidance pose determining module 1300, a teleoperation control module 1400 and a teleoperation control module 1400, wherein the displacement increment determining module is configured to obtain current position information of the target unmanned aerial vehicle, the joystick displacement increment and the maximum radius of a joystick working space by a position increment type motion controller, the displacement increment corresponding to the target unmanned aerial vehicle is determined according to the joystick displacement increment and the ratio between the maximum radius of the joystick working space and the joystick displacement increment, the barrier avoidance pose determining module 1300 is configured to determine the barrier avoidance pose of the target unmanned aerial vehicle by the position increment type motion controller according to the initial position of the joystick and the joystick displacement increment by calculation, and determine the target position and the yaw angle of the target unmanned aerial vehicle according to the current position information, and the teleoperation control module 1400 is configured to generate flight control instructions corresponding to the target unmanned aerial vehicle by a differential flat controller according to the barrier avoidance pose, the target position and the yaw angle so as to drive the target unmanned aerial vehicle to automatically avoid barriers, and control tactile operations of the target unmanned aerial vehicle.
On the basis of any embodiment of the present application, referring to fig. 5, another embodiment of the present application further provides an electronic device, where the electronic device may be implemented by a computer device, and as shown in fig. 5, the internal structure of the computer device is schematically shown. The computer device includes a processor, a computer readable storage medium, a memory, and a network interface connected by a system bus. The computer readable storage medium of the computer device stores an operating system, a database and computer readable instructions, the database can store a control information sequence, and when the computer readable instructions are executed by a processor, the processor can realize an unmanned aerial vehicle touch teleoperation control method. The processor of the computer device is used to provide computing and control capabilities, supporting the operation of the entire computer device. The memory of the computer device may store computer readable instructions that, when executed by the processor, cause the processor to perform the unmanned aerial vehicle haptic teleoperation control method of the present application. The network interface of the computer device is for communicating with a terminal connection. It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
The processor in this embodiment is configured to perform specific functions of each module in fig. 4, and the memory stores program codes and various types of data required for executing the above modules. The network interface is used for data transmission between the user terminal or the server. The memory in this embodiment stores program codes and data required for executing all modules/sub-modules in the unmanned aerial vehicle haptic teleoperation control device of the present application, and the server can call the program codes and data of the server to execute the functions of all sub-modules.
The present application also provides a storage medium storing computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the unmanned aerial vehicle haptic teleoperation control method of any one of the embodiments of the present application.
The application also provides a computer program product comprising computer programs/instructions which when executed by one or more processors implement the steps of the unmanned aerial vehicle haptic teleoperation control method of any one of the embodiments of the application.
Those skilled in the art will appreciate that all or part of the processes implementing the methods of the above embodiments of the present application may be implemented by a computer program for instructing relevant hardware, where the computer program may be stored on a computer readable storage medium, where the program, when executed, may include processes implementing the embodiments of the methods described above. The storage medium may be a computer readable storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).
The foregoing is only a partial embodiment of the present application, and it should be noted that it will be apparent to those skilled in the art that modifications and adaptations can be made without departing from the principles of the present application, and such modifications and adaptations are intended to be comprehended within the scope of the present application.
In summary, the unmanned aerial vehicle haptic teleoperation control method based on position increment and model predictive control optimization effectively improves the controllability, the perceptibility, the safety and the operation precision of the system through various innovations such as precise control, smooth force feedback, intelligent obstacle avoidance and the like, not only enhances the operation performance of the unmanned aerial vehicle in a complex environment, but also obviously lightens the burden of operators and improves the working efficiency, thereby providing a more superior solution for various teleoperation tasks with high precision and high risk.
Claims (10)
1. The unmanned aerial vehicle touch teleoperation control method is characterized by comprising the following steps of:
The method comprises the steps that a target unmanned aerial vehicle is detected to enter a non-safety area to respond to an unmanned aerial vehicle touch teleoperation control instruction, a model prediction controller in touch control equipment adopts a preset second derivative to determine feedback force for driving a control lever in the touch control equipment to generate displacement change according to a position kinematic model, a gesture kinematic model, a function model and an obstacle function corresponding to the model prediction controller corresponding to the target unmanned aerial vehicle, and the control lever displacement increment of the control lever is determined according to the feedback force;
The position increment type motion controller obtains the current position information of the target unmanned aerial vehicle, the operating lever displacement increment and the maximum radius of the operating lever working space, and determines the corresponding displacement increment of the target unmanned aerial vehicle according to the operating lever displacement increment and the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment;
The position increment type motion controller calculates and determines the obstacle avoidance pose of the target unmanned aerial vehicle according to the initial position of the control lever and the displacement increment of the control lever, and determines the target position and the yaw angle of the target unmanned aerial vehicle according to the current position information;
And the differential flat controller generates a flight control instruction corresponding to the target unmanned aerial vehicle according to the obstacle avoidance pose, the target position and the yaw angle so as to drive the target unmanned aerial vehicle to automatically avoid the obstacle, thereby completing the control of the unmanned aerial vehicle touch teleoperation.
2. The unmanned aerial vehicle haptic teleoperation control method according to claim 1, wherein the step of determining the feedback force driving the joystick in the haptic control device to undergo the displacement change by the model predictive controller using the preset second derivative according to the positional kinematic model, the gesture kinematic model, the function model corresponding to the model predictive controller, and the obstacle function corresponding to the target unmanned aerial vehicle comprises:
Firstly, constructing a global coordinate system of a system as F W:{xW,yW,zW, and a body reference system as F B：{xB,yB,zB, wherein B represents a variable in the body coordinate system, other variables are represented in a world (inertial) coordinate system, and a rotation matrix from the world coordinate system F w to the body coordinate system F B is represented by a quaternion q= [ q w,qx,qy,qz ] ∈SO (3);
the expression of the position kinematic model is as follows:
wherein ζ w is the displacement of the unmanned aerial vehicle in the world coordinate system, and v w is the speed of the unmanned aerial vehicle in the world coordinate system;
The expression of the gesture kinematic model is as follows:
w=W·ΩB,
wherein w represents three attitude angles of the target unmanned aerial vehicle, and comprises Omega B＝[p,q,r]T, W is expressed as angular velocity in world coordinate system.
3. The unmanned aerial vehicle haptic teleoperation control method according to claim 1, wherein the step of determining the feedback force driving the joystick in the haptic control device to undergo the displacement change by the model predictive controller using the preset second derivative according to the positional kinematic model, the gesture kinematic model, the function model corresponding to the model predictive controller, and the obstacle function corresponding to the target unmanned aerial vehicle comprises:
The expression of the function model corresponding to the model predictive controller comprises the following steps:
Xk＝xk-xk,r,
Uk＝uk-uk,r,
XN＝xn-xn,r,
s.t.u∈[umin,umax],
x0＝xinit,
xk+1＝f(xk,uk),
Wherein, the Expressed as a state space, k is a time step, T is a transpose, u is defined as a set of v w and Ω B, x k+1＝f(xk,uk) is a kinematic model of the drone, Q u is a weighting matrix of the input u, Q and Q n are diagonal matrices with the weighting matrix as diagonal elements, and the subscript r represents the desired value.
4. The unmanned aerial vehicle haptic teleoperation control method according to claim 1, wherein the step of determining the feedback force driving the joystick in the haptic control device to undergo the displacement change by the model predictive controller using the preset second derivative according to the positional kinematic model, the gesture kinematic model, the function model corresponding to the model predictive controller, and the obstacle function corresponding to the target unmanned aerial vehicle comprises:
the expression of the barrier function is:
d(x)-psec≥0,
Where d (x) represents the physical region of the secure space, and p sec represents the secure region threshold;
the expression of the second derivative is:
Where K f1、Kf2 and K f3 are constant parameters for adjusting the magnitude of the haptic feedback.
5. The unmanned aerial vehicle haptic teleoperation control method of claim 1, wherein determining the corresponding displacement increment of the target unmanned aerial vehicle from the joystick displacement increment and a ratio between a maximum radius of the joystick workspace and the joystick displacement increment comprises:
the expression of the displacement increment corresponding to the target unmanned aerial vehicle is as follows:
Wherein a represents an input signal of a touch device button, K m is a scaling matrix with positive diagonal line, the scaling matrix is used for controlling displacement increment of the unmanned aerial vehicle in different directions, q j (t) represents a distance between the tail end of the operating lever and the origin of the operating lever working space, delta q s (t) represents a corresponding displacement increment of the unmanned aerial vehicle, r represents the maximum radius of the operating lever working space, when the operating lever displacement increment q j (t) is smaller than the maximum radius r of the operating lever working space, the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment is larger than 1, and the corresponding displacement increment of the unmanned aerial vehicle is the product of the scaling matrix with positive diagonal line and the operating lever displacement increment.
6. The unmanned aerial vehicle haptic teleoperation control method of claim 1, wherein the step of determining the obstacle avoidance pose of the target unmanned aerial vehicle by the position delta motion controller according to the initial position of the joystick and the joystick displacement delta calculation comprises:
the expression of the obstacle avoidance pose of the target unmanned aerial vehicle is as follows:
Wherein, ζ n represents the initial position of the control lever, N represents the control times of the control lever, and ζ (t) represents the obstacle avoidance pose of the target unmanned aerial vehicle.
7. The unmanned aerial vehicle haptic teleoperation control method according to any one of claims 1 to 6, wherein the step of determining the feedback force driving the joystick in the haptic control device to undergo a displacement change by using a preset second derivative according to the positional kinematic model, the posture kinematic model, the function model corresponding to the model predictive controller, and the obstacle function corresponding to the target unmanned aerial vehicle by the model predictive controller, comprises:
And responding to the safety obstacle avoidance warning command, outputting the feedback force to a force feedback controller in the driving touch control equipment so as to enable an operator to sense the feedback force, and warning the operator to drive the target unmanned aerial vehicle away from a non-safety area.
8. The utility model provides a unmanned aerial vehicle sense of touch teleoperation controlling means which characterized in that includes:
The feedback force determining module is used for detecting that the target unmanned aerial vehicle enters a non-safety area and responding to an unmanned aerial vehicle touch teleoperation control instruction, and a model prediction controller in the touch control equipment adopts a preset second derivative to determine feedback force for driving a control lever in the touch control equipment to generate displacement change according to a position kinematic model, a gesture kinematic model, a function model and an obstacle function corresponding to the model prediction controller corresponding to the target unmanned aerial vehicle, and determines the control lever displacement increment of the control lever according to the feedback force;
The displacement increment determining module is set to obtain the current position information of the target unmanned aerial vehicle, the displacement increment of the operating lever and the maximum radius of the operating lever working space by the position increment type motion controller, and the corresponding displacement increment of the target unmanned aerial vehicle is determined according to the operating lever displacement increment and the ratio between the maximum radius of the operating lever working space and the operating lever displacement increment;
The obstacle avoidance pose determining module is arranged as a position increment type motion controller for determining the obstacle avoidance pose of the target unmanned aerial vehicle according to the initial position of the operating lever and the displacement increment calculation of the operating lever, and determining the target position and the yaw angle of the target unmanned aerial vehicle according to the current position information;
and the teleoperation control module is arranged to generate a flight control instruction corresponding to the target unmanned aerial vehicle by the differential flat controller according to the obstacle avoidance pose, the target position and the yaw angle so as to drive the target unmanned aerial vehicle to automatically avoid the obstacle and complete the control of the unmanned aerial vehicle touch teleoperation.
9. An electronic device comprising a central processor and a memory, characterized in that the central processor is arranged to invoke a computer program stored in the memory for performing the steps of the method according to any of claims 1 to 7.
10. A computer-readable storage medium, characterized in that it stores in the form of computer-readable instructions a computer program implemented according to the method of any one of claims 1 to 7, which, when invoked by a computer, performs the steps comprised by the corresponding method.
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