CN112543899B - Control method, control device and computer-readable storage medium for movable carrier - Google Patents
Control method, control device and computer-readable storage medium for movable carrier Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B11/00—Automatic controllers
- G05B11/01—Automatic controllers electric
- G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
- G05B11/42—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P. I., P. I. D.
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/048—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators using a predictor
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
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Abstract
提供了一种可移动载体的控制方法、控制装置、计算机可读存储介质。可移动载体的控制方法，包括：获取用于控制所述可移动载体的控制杆量(S201)；根据所述控制杆量确定所述可移动载体的预测轨迹(S202)；根据所述预测轨迹生成控制指令序列，以控制所述可移动载体按照所述预测轨迹移动(S203)。
A control method, a control device, and a computer-readable storage medium for a movable carrier are provided. The control method for a movable carrier includes: obtaining a control rod amount for controlling the movable carrier (S201); determining a predicted trajectory of the movable carrier according to the control rod amount (S202); generating a control instruction sequence according to the predicted trajectory to control the movable carrier to move according to the predicted trajectory (S203).
Description
Technical Field
The present disclosure relates to the field of control, and in particular, to a method and apparatus for controlling a removable carrier, and a computer readable storage medium.
Background
For mobile carriers such as unmanned aerial vehicles, a user can control the unmanned aerial vehicle through remote control equipment. In many scenarios, when a user wishes for a drone to fly along a desired trajectory, the drone may be caused to fly out of the trajectory corresponding to the amount of control stick by pushing and pulling a rocker of the remote control device.
In the prior art, remote control equipment sends control rod quantity to an unmanned aerial vehicle, and closed-loop control of speed is realized by mapping the rod quantity into a speed instruction. However, since closed-loop control of the position is not currently achieved, it is often caused that the actual flight trajectory of the unmanned aerial vehicle cannot be kept consistent with the desired trajectory of the user. For example, when a user controls the drone to fly straight by pushing and pulling a joystick of the remote control device, the drone flies out a straight line that is not desired by the user. The above-mentioned circumstances can influence unmanned aerial vehicle and carry out its flight mission, for example, when unmanned aerial vehicle carried out the shooting mission, can reduce the shooting quality of video, influence user experience.
Disclosure of Invention
The present disclosure provides a control method of a movable carrier, including:
acquiring a control lever amount for controlling the movable carrier;
determining a predicted trajectory of the movable carrier according to the control lever quantity;
And generating a control instruction sequence according to the predicted track so as to control the movable carrier to move according to the predicted track.
The present disclosure also provides a control device for a movable carrier, including:
a memory for storing executable instructions;
a processor for executing the executable instructions stored in the memory to perform the following operations:
acquiring a control lever amount for controlling the movable carrier;
determining a predicted trajectory of the movable carrier according to the control lever quantity;
And generating a control instruction sequence according to the predicted track so as to control the movable carrier to move according to the predicted track.
The present disclosure also provides a computer-readable storage medium storing executable instructions that, when executed by one or more processors, cause the one or more processors to perform the above-described control method.
The present disclosure also provides a movable carrier comprising:
The control device and
And the controller is used for receiving the control instruction sequence generated by the control device and controlling the movable carrier by utilizing the control instruction sequence.
The present disclosure also provides a remote control device of a movable carrier, comprising:
The control device and
And the communication unit is used for sending the control instruction sequence generated by the control device to the movable carrier so that the controller of the movable carrier can control the movable carrier by using the control instruction sequence.
The method and the device predict the track according to the control rod quantity, and control the unmanned aerial vehicle by reusing the predicted track. Through the measures, the actual flight track of the unmanned aerial vehicle is kept to be highly consistent with the track expected by the user in the process of controlling the unmanned aerial vehicle to fly by the driving rod, and the user experience is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person of ordinary skill in the art.
Fig. 1 is a schematic structural view of a unmanned aerial vehicle.
Fig. 2 is a flowchart of a method for controlling a movable carrier according to an embodiment of the present disclosure.
Fig. 3 is a schematic diagram of a control method executed by a drone according to an embodiment of the disclosure.
Fig. 4 is a schematic diagram of a control method performed by a remote control device according to an embodiment of the disclosure.
Fig. 5 is a schematic diagram of a control method performed by a drone according to another embodiment of the disclosure.
Fig. 6 is a schematic diagram of a control method performed by a remote control device according to another embodiment of the present disclosure.
Fig. 7 is a schematic structural view of a control device for a movable carrier according to an embodiment of the present disclosure.
Fig. 8 is a schematic structural view of a movable carrier according to an embodiment of the present disclosure.
Fig. 9 is a schematic structural diagram of a remote control device according to an embodiment of the present disclosure.
Detailed Description
The technical solutions of the present disclosure will be clearly and completely described below with reference to the embodiments and the drawings in the embodiments. It will be apparent that the described embodiments are merely some, but not all embodiments of the present disclosure. Based on the embodiments in this disclosure, all other embodiments that a person of ordinary skill in the art would obtain without making any inventive effort are within the scope of protection of this disclosure.
An embodiment of the present disclosure provides a method for controlling a movable carrier. The control method of the embodiments of the present disclosure is adapted to control various movable carriers. For convenience of description, the unmanned aerial vehicle is exemplified in the embodiment of the present disclosure, but the movable carrier is not limited to the unmanned aerial vehicle, but is applicable to various other movable carriers such as an unmanned vehicle, an unmanned ship, a robot, and the like.
First, unmanned aerial vehicle to which the control method of the embodiment is applied will be described. As shown in fig. 1, an example of a drone is given. The unmanned aerial vehicle is provided with a flight controller. The flight controller may include one or more processors that may individually or collectively generate control instructions to control the flight of the drone.
The unmanned aerial vehicle is further provided with a drive, for example a motor. The motor may be coupled to one or more power units of the drone. The power unit may include a rotor. The flight controller can control the action of the driver to enable the driver to drive the rotor to rotate, so that power is generated for the unmanned aerial vehicle.
The unmanned aerial vehicle is also provided with a sensor. The sensors may include, but are not limited to, various types of sensors such as GPS receivers, inertial measurement units (IMUs, inertial Measurement Unit), and the like. The unmanned aerial vehicle can obtain the position and the gesture parameters of the unmanned aerial vehicle through the sensor. The position parameters may include the position, linear velocity, linear acceleration of the drone. The attitude parameters can comprise an attitude angle, an attitude angular speed and an attitude angular acceleration of the unmanned aerial vehicle, and the attitude angle can comprise a course angle, a pitch angle and a roll angle of the unmanned aerial vehicle.
The unmanned aerial vehicle is also provided with shooting device, and shooting device can be hung on the unmanned aerial vehicle fuselage through increasing steady cloud platform, catches the image or record the video in unmanned aerial vehicle motion process.
The unmanned aerial vehicle can be controlled to fly through the remote control equipment, and the remote control equipment is in wireless communication with a flight controller of the unmanned aerial vehicle. The remote control device is provided with an operating element, such as a joystick, for operation by a user. The user generates control rod quantity through operating the rocker, the control rod quantity is sent to the flight controller through wireless communication, and the flight controller generates control instructions according to the control rod quantity so as to control the action of the driver, and therefore the flight of the unmanned aerial vehicle is controlled.
The control method of the movable carrier of this embodiment, as shown in fig. 2, includes:
step S201, obtaining the control rod quantity for controlling the movable carrier;
step S202, determining a predicted track of the movable carrier according to the control rod quantity;
and step S203, a control instruction sequence is generated according to the predicted track so as to control the movable carrier to move according to the predicted track.
The control method of the present embodiment may be executed by a flight controller of an unmanned aerial vehicle, or may be executed by a remote control device, and will be described below with reference to fig. 3 by way of example.
In step S201, a control lever amount of the control unmanned aerial vehicle is generated at the remote control device. The user can manually control the unmanned aerial vehicle to fly, and the rocker of the remote control device is pushed and pulled to generate a control rod amount, and the control rod amount corresponds to the expected track of the user. For example, when a user wants to control the unmanned aerial vehicle to fly straight, the joystick of the remote control device can be pushed and pulled, so that the control lever quantity corresponding to the expected straight track is generated.
In step S202, after receiving the control rod amount sent by the remote control device, the flight controller generates a control command according to the control rod amount, but does not directly control the unmanned aerial vehicle according to the generated control command, but performs trajectory prediction according to the control rod amount. And taking the generated control instruction as an initial control instruction, predicting the track of the unmanned aerial vehicle according to the initial control instruction, tracking the predicted track to obtain an optimized control instruction, and controlling the unmanned aerial vehicle according to the optimized control instruction. Specifically:
First, an initial command sequence is generated based on the control lever amount.
Assuming that the control lever amount generated by the remote control device is received at the current moment, the embodiment can obtain an instruction sequence according to the control lever amount, and takes the instruction sequence as an initial instruction sequence.
The initial command sequence of the present embodiment may include an initial linear velocity command sequence and an initial linear acceleration command sequence. In one example, the lever amount may be mapped to a linear velocity command. And filtering the linear velocity command at the current moment according to the linear velocity command filtered at the last moment, obtaining an initial linear velocity command sequence v_cmd k, k=1..N according to a uniform acceleration model, and searching linear acceleration corresponding to the linear velocity in the initial linear velocity command sequence according to an air resistance model, thereby obtaining an initial linear acceleration command sequence a_cmd k, k=1..N, wherein k represents each command moment after the current moment. The present embodiment does not limit the number of instructions (i.e., the number of N) in the initial linear velocity instruction sequence and the initial linear acceleration instruction sequence, and the time interval between adjacent instructions, and can be set according to the actual situation and the control effect.
In other examples, the control lever amount may be mapped to a linear acceleration command, and a linear velocity corresponding to a linear acceleration in the initial linear acceleration command sequence may be found to obtain the initial linear velocity command sequence, or the control lever amount may be mapped to both the linear velocity command sequence and the linear acceleration command sequence. By the method, the smooth continuous initial instruction sequence can be generated, so that the predicted track determined according to the initial instruction sequence is smooth and continuous, and the control effect on the flight track of the unmanned aerial vehicle can be ensured.
After the initial instruction sequence is generated, determining the predicted track of the unmanned aerial vehicle according to the initial instruction sequence. In the process of determining the predicted track, firstly, a kinematic model of the unmanned aerial vehicle is obtained, then the initial instruction sequence is subjected to track prediction by using the kinematic model, the predicted track is obtained, and predicted track points in the predicted track are characterized by predicted position parameters. The predicted position parameters include a predicted position, or a predicted position and a predicted linear velocity.
The following description will be given by taking a uniform acceleration model as an example, but the present embodiment is not limited thereto, and any other type of kinematic model may be used, such as, but not limited to, a uniform velocity model, a nonlinear model, and the like.
The ramp up model is as follows:
pk+1＝pk+vk·Δt+0.5·ak·Δt2 (1)
vk+1＝vk+ak·Δt (2)
Wherein Δt represents the time interval between adjacent times, p k represents the position at time k, v k represents the linear velocity at time k, a k represents the linear acceleration at time k, v k+1 represents the linear velocity at time k+1, and a k+1 represents the linear acceleration at time k+1.
In this embodiment, first, the position parameter of the unmanned aerial vehicle at the current moment is obtained, and then the position parameter, the initial linear velocity instruction sequence and the initial linear acceleration instruction sequence at the current moment are input into formulas (1) and (2), so as to obtain the predicted position parameter of the predicted track point of the predicted track. Specifically, the position p 0, the linear velocity v 0 and the linear acceleration a 0 of the unmanned aerial vehicle at the current moment can be obtained through the sensors of the unmanned aerial vehicle. And then taking the position P 0, the linear velocity v 0 and the linear acceleration a 0 as initial values of formulas (1) and (2), substituting each linear velocity instruction in the initial linear velocity instruction sequence v_cmd k and each linear acceleration instruction in the initial linear acceleration instruction sequence a_cmd k into formulas (1) and (2) for iterative operation, and obtaining each predicted track point P 1,P2,...,PN of the predicted track, wherein the predicted position parameters of the predicted track point comprise two parameters, namely the predicted position and the predicted linear velocity.
In the track prediction process, the initial linear acceleration command sequence needs to be corrected by considering the influence of the following factors.
In order to achieve the expected track, the unmanned aerial vehicle is required to be realized through a flight controller, the unmanned aerial vehicle can be subjected to air resistance in flight, the initial linear acceleration instruction sequence also needs to overcome the air resistance, the position and the gesture are decoupled in the track prediction process, and the coupling of the position and the gesture is considered, so that the influence of the centripetal acceleration of the unmanned aerial vehicle also needs to be considered.
In this embodiment, the initial linear acceleration command sequence is modified with at least one of a linear acceleration control amount acc_ctrl of the flight controller of the unmanned aerial vehicle, a centripetal acceleration acc_ cent of the unmanned aerial vehicle, and an air resistance acc_air experienced by the unmanned aerial vehicle. For example, when the initial linear acceleration command sequence is corrected in consideration of the above three factors, the corrected initial linear acceleration command sequence a_cmd' k＝a_cmdk +acc_ctrl-acc_ cent-acc_air.
After obtaining the predicted track of the unmanned aerial vehicle, performing instruction optimization by utilizing step S203, namely generating a control instruction sequence according to the predicted track so as to control the unmanned aerial vehicle to move according to the predicted track. The predicted trajectory point may be tracked by a trajectory tracking controller to generate a sequence of control instructions. The following describes step S203 using the model predictive controller as an example, but the trajectory tracking controller that can be used in the present embodiment is not limited to this, and may be any other trajectory tracking controller such as a proportional-integral-derivative controller, a pure tracking controller, and a linear quadratic regulator.
When the model predictive controller is used to track the predicted track points, the predicted track P 1,P2,...,PN obtained in step S202 may be first sampled at intervals to obtain the predicted track points after being sampled at intervals, and the predicted track points after being sampled at intervals are input into the model predictive controller to generate the control instruction sequence. The specific mode of interval sampling is that in the predicted track, one predicted track point is sampled every a plurality of predicted track points, and the sampled predicted track points form a new predicted track which is used as the predicted track after interval sampling. The predicted track P 1,P2,...,PN obtained in step S202 is sampled at intervals, and the whole predicted track can be represented by fewer track points, so that the operation amount is reduced, and the operation efficiency is improved.
In one example, if the time interval between adjacent predicted track points in step S202 is 0.04 seconds, 8 predicted track points may be sampled from each predicted track point once every 5 predicted track points. For example, starting from the predicted track point P 1, sampling every 5 predicted track points, starting from the predicted track point P 2, sampling every 5 predicted track points, and so on, wherein the number m=8 of the predicted track points after interval sampling, the time interval between the predicted track points is 0.2 seconds, and the 8 predicted track points after interval sampling are sequentially input into the model prediction controller.
The model predictive controller is described as follows:
x1(k+1)＝x1(k)+ΔT·x2(k)+0.5·ΔT2·u(k) (4)
x2(k+1)＝x2(k)+ΔT·u(k) (5)
-vmax≤x2(k)≤vmax (6)
-amax≤u(k)≤amax (7)
Wherein, formula (3) represents a cost function, the cost function includes a penalty term J p_err for predicting a position parameter, a linear acceleration and a penalty term J acc、Jjerk.xi、xri for a linear acceleration change rate represent a predicted input and a reference input of the cost function, respectively, and u represents a linear acceleration instruction. Equations (4) - (7) represent constraints, and equations (4) and (5) represent prediction models for outputting predicted position x 1 and predicted linear velocity x 2, respectively. Similar to the kinematic model in step S202, the predictive model here also employs a uniform acceleration model. Equations (6) and (7) represent the values of the predicted linear velocity x 2 and the linear acceleration command u, respectively.
And tracking the predicted position parameters of the predicted track points after the interval sampling by using a model prediction controller to generate a position control instruction sequence. When a group of predicted track points after interval sampling is input, the predicted position and the predicted linear speed of the predicted track points after interval sampling are used as reference input of a cost function, the predicted position and the predicted linear speed output by a prediction model are used as prediction input of the cost function, model prediction control is carried out, a group of linear speed control instructions and linear acceleration control instructions are obtained, a first linear speed control instruction and a first linear acceleration instruction in the group of linear speed control instructions and the linear acceleration control instructions are used as control instructions corresponding to the predicted track points after interval sampling and are input into a flight controller, and the flight controller controls the unmanned aerial vehicle by using the control instructions.
In the motion process of the unmanned aerial vehicle, the steps can be repeatedly executed, the predicted track is updated according to the control rod quantity at different moments, a plurality of groups of predicted track points after interval sampling are sequentially input into a model prediction controller for rolling prediction, and a linear speed control instruction sequence and a linear acceleration control instruction sequence corresponding to the predicted track points after interval sampling can be obtained.
Therefore, the control command mapped by the control rod quantity is not directly used for controlling the unmanned aerial vehicle, the track prediction is carried out according to the control command mapped by the control rod quantity, the track tracking controller is used for tracking the predicted track, so that the optimized control command is obtained, and the unmanned aerial vehicle is controlled according to the optimized control command. Through the measures, the unmanned aerial vehicle flight control process through the rocker has the position planning capability, the position closed-loop control is realized, the actual flight track of the unmanned aerial vehicle is kept to be highly consistent with the track which is expected by a user and corresponds to the control rod amount under the control of the optimized control instruction, for example, when the user wants to control the unmanned aerial vehicle to fly straight line, the unmanned aerial vehicle can fly out of the straight line which is expected by the user through pushing and pulling the remote rod of the remote control equipment, so that the technical problem that the prior art that the unmanned aerial vehicle cannot fly out of the straight line under the control of the user is solved, on the basis, the shooting quality of the unmanned aerial vehicle is improved, for example, the stability of synthesized video and the aesthetic degree of video under the time-delay shooting mode are enhanced.
The control method of the present embodiment has been described above with reference to fig. 2 and 3, in which the predicted position parameters of the predicted trajectory point include the predicted position and the predicted linear velocity, and the position control instruction sequence includes the control instruction sequence of the linear velocity and the linear acceleration, but the above description is only one implementation of the present embodiment. In another implementation of the control method of the present embodiment, the predicted position parameter of the predicted track point may include a predicted position, and the position control instruction sequence includes a linear velocity control instruction sequence. In this implementation, in step S202, the position parameter at the current time and the initial instruction sequence are input into the kinematic model, so as to obtain the predicted position of each predicted track point in the predicted track. In step S203, the model predictive controller is used to track the predicted positions of the predicted track points after the interval sampling, and a linear velocity control command sequence is generated, and the flight control of the unmanned aerial vehicle is used to control the position of the unmanned aerial vehicle.
The control method of the present embodiment is described above by taking the control method performed by the flight controller of the unmanned aerial vehicle as an example. The above description is also only one implementation of the present embodiment. In another implementation manner of the control method of the present embodiment, the control method of the present embodiment may be executed in a remote control device of an unmanned aerial vehicle. As shown in fig. 4, at the remote control device, a predicted position parameter is obtained through track prediction in step S202, and then a position control instruction sequence is obtained through instruction optimization in step S203, and the position control instruction sequence is sent to the unmanned aerial vehicle instead of the control lever amount. A position controller in the flight controller controls the flight of the unmanned aerial vehicle using a position control command sequence.
According to the embodiment, the unmanned aerial vehicle flight control process through the rocker is enabled to have position planning capability, position closed-loop control is achieved, the actual flight track of the unmanned aerial vehicle is kept highly consistent with the track which is expected by a user and corresponds to the control rod amount, and the technical problem that the unmanned aerial vehicle cannot fly out of a straight line under the control of the rod of the user in the prior art is solved.
For the purpose of simplifying the description, any description of the technical features of the above embodiments that can be applied to the same application is incorporated herein, and the description is not repeated.
In some application scenarios, the user wants to control the drone to fly along a curve, rather than along a straight line. For example, a control stick quantity may be generated by pushing and pulling a joystick of a remote control device, the control stick quantity corresponding to a desired curved track. According to the control method of the movable carrier, the unmanned aerial vehicle can fly along the curve track corresponding to the control rod quantity, and the expected track of the user is kept to be highly consistent with the actual flight track of the unmanned aerial vehicle.
Referring to fig. 2 and 5, in step S201, a control lever amount for controlling the unmanned aerial vehicle is generated at the remote control device. Since the user's desired flight trajectory is a curve, the control stick quantity generated by the remote control device includes two parts, a stick quantity corresponding to the linear motion and a stick quantity corresponding to the rotational motion.
In step S202, after receiving the control rod amount sent by the remote control device, the flight controller generates an initial control instruction according to the control rod amount, predicts the trajectory of the unmanned aerial vehicle according to the initial control instruction, tracks the predicted trajectory to obtain an optimized control instruction, and controls the unmanned aerial vehicle according to the optimized control instruction. Specifically:
First, an initial command sequence is generated based on the control lever amount.
The initial instruction sequence of the present embodiment includes an initial position instruction sequence and an initial posture instruction sequence. The initial position command sequence is similar to the previous embodiment and includes an initial linear velocity command sequence v_cmd k, k=1..n and an initial linear acceleration command sequence a_cmd k, k=1..n. The initial gesture command sequence may include an initial heading angular velocity command sequenceSimilar to the previous embodiment, the present embodiment may obtain the initial command sequence by filtering, so as to obtain the initial position command sequence and the initial gesture command sequence, and the number of commands (i.e., the value of N) of the two command sequences and the time interval between the adjacent commands are defined, which may be set according to the actual situation and the control effect.
By the method, a smooth and continuous initial position instruction sequence and an initial gesture instruction sequence can be generated, so that a predicted track determined according to the initial position instruction sequence and the initial gesture instruction sequence is smooth and continuous, and the control effect on the flight track of the unmanned aerial vehicle can be ensured.
After the initial instruction sequence is generated, determining the predicted track of the unmanned aerial vehicle according to the initial instruction sequence. Similar to the previous embodiment, in the process of determining the predicted track, firstly, a kinematic model of the unmanned aerial vehicle is obtained, then the initial instruction sequence is subjected to track prediction by using the kinematic model to obtain the predicted track, and the predicted track points in the predicted track are characterized by the predicted position parameters and the predicted posture parameters. The predicted attitude parameters comprise a predicted course angle and a predicted course angular speed.
For the ramp up model, the ramp up model is as follows:
pk+1＝pk+vk·Δt+0.5·ak·Δt2 (8)
vk+1＝vk+ak·Δt (9)
wherein, the formulas (8) and (9) are the same as the formulas (1) and (2) of the previous embodiment, and are used for predicting the position parameters of the predicted track. Equations (10) and (11) are used for predicting the attitude parameters of the predicted trajectory; The heading angular velocity at the time k is indicated, Represents the linear angular velocity at time k +1, phi k represents the heading angle at time k, phi k+1 represents the heading angle at time k +1,And represents the heading angular acceleration at time k.
In this embodiment, the position parameter and the posture parameter of the predicted track may be decoupled, and the position parameter and the posture parameter may be predicted respectively.
The prediction process of the position parameter is similar to that of the previous embodiment, and specifically can be referred to the description of the previous embodiment, in brief, the position parameter, the initial linear velocity instruction sequence and the initial linear acceleration instruction sequence at the current moment are substituted into formulas (8) and (9) for iterative operation, so that the predicted position and the predicted linear velocity of the predicted track point can be obtained, and the initial linear acceleration instruction sequence is modified based on at least one factor selected from the group consisting of the linear acceleration control quantity of the unmanned aerial vehicle flight controller, the centripetal acceleration of the unmanned aerial vehicle and the air resistance suffered by the unmanned aerial vehicle.
The method comprises the steps of firstly obtaining the gesture parameters of the unmanned aerial vehicle at the current moment, inputting the gesture parameters, an initial course angular velocity instruction sequence and an initial course angular acceleration instruction sequence at the current moment into formulas (10) and (11) of a uniform acceleration model to obtain the predicted gesture parameters of each predicted track point in a predicted track, wherein the predicted gesture parameters comprise the predicted course angle and the predicted course angular velocity of the predicted track point.
In the above process, the initial course angular acceleration command may be determined according to the initial course angular velocity command sequence and the predicted course angular velocity of the predicted track point. In particular the number of the elements,
Wherein, A heading angular velocity command at time k in the initial heading angular velocity command sequence is represented,The predicted heading angular velocity of the predicted trajectory point at time k-1 is represented, and ρ represents a control coefficient.
Specifically, the heading angle psi 0 and the heading angular speed of the unmanned aerial vehicle at the current moment can be obtained through the IMU of the unmanned aerial vehicleAnd course angular accelerationHeading angle psi 0 and heading angular speedAnd course angular accelerationAs the initial values of formulas (10) and (11), and the initial values and the initial course angular velocity instruction sequenceAnd substituting the initial course angle acceleration instruction sequence into formulas (10) and (11) for iterative operation, and obtaining the predicted course angle and the predicted course angle speed of each predicted track point of the predicted track.
And obtaining a predicted track P 1,P2,...,PN predicted according to the initial position instruction sequence and the initial gesture instruction sequence through the prediction of the position parameters and the gesture parameters, and predicting four parameters of a predicted position, a predicted linear speed, a predicted course angle and a predicted course angular speed of a predicted track point.
After obtaining the predicted track of the unmanned aerial vehicle, performing instruction optimization by utilizing step S203, namely generating a control instruction sequence according to the predicted track so as to control the unmanned aerial vehicle to move according to the predicted track. The control instruction sequence comprises a position control instruction sequence and a gesture control instruction sequence.
In this embodiment, the position parameter and the gesture parameter of the predicted track may be decoupled, and the position control instruction sequence and the gesture control instruction sequence may be generated respectively.
The generation of the sequence of position control instructions is similar to the previous embodiment. As one example, a model predictive controller may be employed to generate the sequence of position control instructions separately. Similar to the previous embodiment, the position control command sequence may include a linear velocity control command sequence and/or a linear acceleration control command sequence.
Various trajectory tracking controllers may track the attitude parameters of the predicted trajectory to generate a sequence of attitude control instructions, in one example, a proportional-integral-derivative controller (PID) may be employed. The generated gesture control instruction sequence may be a course angular velocity control instruction sequence or a course angular acceleration control instruction sequence, and the gesture control instruction sequence may also include the two instruction sequences.
After the position control instruction sequence and the gesture control instruction sequence are obtained, the two instruction sequences can be sent to the flight control of the unmanned aerial vehicle, and the flight control of the unmanned aerial vehicle controls the position and the gesture of the unmanned aerial vehicle by using the position control instruction sequence and the gesture control instruction sequence. The position control command sequence is input into the position controller, the gesture control command sequence is input into the gesture controller, and the position controller and the gesture controller respectively output control amounts to control each driver, so that the unmanned aerial vehicle flies along a curve corresponding to the control rod amount.
Therefore, the control command mapped by the control rod quantity is not directly used for controlling the unmanned aerial vehicle, the track prediction is carried out according to the control command mapped by the control rod quantity, the track tracking controller is used for tracking the predicted track, so that the optimized control command is obtained, and the unmanned aerial vehicle is controlled according to the optimized control command. Through the measures, the unmanned aerial vehicle flight control process through the rocker has the position planning capability, the position closed-loop control is realized, the actual flight track of the unmanned aerial vehicle is kept to be highly consistent with the track which is expected by a user and corresponds to the control rod quantity under the control of the optimized control instruction, for example, when the user wants to control the unmanned aerial vehicle flight curve or detour track, the unmanned aerial vehicle can fly out of the track expected by the user through pushing and pulling the remote rod of the remote control device, and therefore the technical problem that the actual flight track of the unmanned aerial vehicle is inconsistent with the track expected by the user under the control of the user's rod beating is solved.
The control method of the present embodiment was described above as an example of the control method being executed by the unmanned aerial vehicle. The above description is also only one implementation of the present embodiment. In another implementation manner of the control method of the present embodiment, the control method of the present embodiment may be executed in a remote control device of an unmanned aerial vehicle. As shown in fig. 6, at the remote control device, a predicted position parameter and a predicted gesture parameter are obtained through track prediction, then a position control instruction sequence and a gesture control instruction sequence are obtained through instruction optimization, and the position control instruction sequence and the gesture control instruction sequence are sent to the unmanned aerial vehicle instead of the control lever quantity. The position controller and the gesture controller in the flight controller respectively control the flight of the unmanned aerial vehicle by using the position control command sequence and the gesture control command sequence.
A further embodiment of the present disclosure provides a control device for a movable carrier, as shown in fig. 7, where the control device may include a processor and a memory. The processor and the memory may be one or a plurality of processors, respectively.
The control device of the movable carrier of the embodiment stores executable instructions in a memory, and the processor can execute the executable instructions stored in the memory to execute the following operations:
acquiring a control lever amount for controlling the movable carrier;
determining a predicted trajectory of the movable carrier according to the control lever quantity;
And generating a control instruction sequence according to the predicted track so as to control the movable carrier to move according to the predicted track.
The operation of determining the predicted trajectory of the movable carrier from the control lever amount includes:
Generating an initial instruction sequence according to the control rod quantity;
and determining the predicted track of the movable carrier according to the initial instruction sequence.
The operation of determining the predicted trajectory of the movable carrier from the initial sequence of instructions comprises:
Acquiring a kinematic model of the movable carrier;
And carrying out track prediction on the initial instruction sequence by using the kinematic model to obtain the predicted track.
The predicted track points in the predicted track are characterized by a predicted position parameter. The predicted location parameters include:
Predicting the position or
Predicted position and predicted linear velocity.
The initial command sequence comprises an initial linear velocity command sequence and an initial linear acceleration command sequence.
The operation of performing track prediction on the initial instruction sequence by using the kinematic model to obtain the predicted track includes:
acquiring the position parameter of the movable carrier at the current moment;
And inputting the position parameter of the movable carrier at the current moment, the initial linear velocity instruction sequence and the initial linear acceleration instruction sequence into the kinematic model to obtain the predicted position parameter of the predicted track point of the predicted track. The position parameters of the movable carrier at the current moment comprise position, linear speed and linear acceleration.
The initial linear acceleration command sequence is modified according to at least one of the following factors:
The linear acceleration control amount of the controller of the movable carrier, the centripetal acceleration of the movable carrier and the air resistance of the movable carrier.
The predicted trajectory points in the predicted trajectory are also characterized by predicted gesture parameters. The predicted attitude parameters include a predicted heading angle and a predicted heading angular velocity.
The initial instruction sequence also comprises an initial course angular velocity instruction sequence.
The operation of predicting the track of the initial instruction sequence by using the kinematic model to obtain the predicted track further comprises:
Acquiring the attitude parameters of the movable carrier at the current moment;
Inputting the attitude parameters of the movable carrier at the current moment, the initial course angular velocity instruction sequence and the initial course angular acceleration instruction sequence into the kinematic model to obtain the predicted attitude parameters of the predicted track points of the predicted track sequence;
And determining the initial course angular acceleration instruction according to the initial course angular velocity instruction sequence and the predicted course angular velocity of the predicted track point of the predicted track. The attitude parameters of the movable carrier at the current moment comprise a course angle, a course angular velocity and a course angular acceleration.
The kinematic model comprises at least one of a uniform acceleration model, a uniform velocity model and a nonlinear model.
The operation of generating a control instruction sequence according to the predicted track comprises the following steps:
And tracking the predicted track points after the interval sampling by utilizing a track tracking controller to generate the control instruction sequence.
The trajectory tracking controller comprises at least one of a model predictive controller, a proportional-integral-derivative controller, a pure tracking controller and a linear quadratic regulator.
The control instruction sequence comprises a position control instruction sequence, the operation of tracking the predicted track points after interval sampling by using a track tracking controller to generate the control instruction sequence comprises the following steps:
and tracking the predicted position parameters of the predicted track points after the interval sampling by using the model prediction controller to generate the position control instruction sequence.
The position control command sequence comprises a linear acceleration control command sequence and/or a linear velocity control command sequence.
The linear acceleration control command sequence and/or the first command in the linear velocity control command sequence is used for controlling the movable carrier.
The control instruction sequence comprises an attitude control instruction sequence, the operation of tracking the predicted track points after interval sampling by using a track tracking controller to generate the control instruction sequence comprises the following steps:
And tracking the predicted gesture parameters of the predicted track points in the predicted track sequence by using the proportional-integral-derivative controller to generate the gesture control instruction sequence. The gesture control instruction sequence comprises a course angular speed control instruction sequence and/or a course angular acceleration control instruction sequence.
The gesture control instruction sequence is used for controlling the movable carrier.
The processor of the present embodiment may include, for example, a general purpose microprocessor, an instruction set processor and/or an associated chipset and/or special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. The processor may also include on-board memory for caching purposes.
The memory of the present embodiment may be, for example, a nonvolatile computer-readable storage medium, specific examples of which include, but are not limited to, magnetic storage devices such as magnetic tape or hard disk (HDD), optical storage devices such as compact disk (CD-ROM), memories such as Random Access Memory (RAM) or flash memory, and the like.
Yet another embodiment of the present disclosure provides a computer-readable storage medium storing executable instructions that, when executed by one or more processors, cause the one or more processors to perform the control method of any one of the above embodiments.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but is not limited to, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A further embodiment of the disclosure provides a movable carrier, as shown in fig. 8, including the control device of the foregoing embodiment, and a controller configured to receive a control instruction sequence generated by the control device, and control the movable carrier using the control instruction sequence. In one example, the moveable carrier is a drone and the controller is a flight controller of the drone.
A further embodiment of the present disclosure provides a remote control device for a mobile carrier, as shown in fig. 9, including the control device of the foregoing embodiment, and a communication unit configured to send a control instruction sequence generated by the control device to the mobile carrier, so that a controller of the mobile carrier controls the mobile carrier using the control instruction sequence.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional modules is illustrated, and in practical application, the above-described functional allocation may be performed by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to perform all or part of the functions described above. The specific working process of the above-described device may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
Finally, it should be noted that the foregoing embodiments are merely for illustrating the technical solutions of the disclosure, and not for limiting the same, and although the disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that the technical solutions described in the foregoing embodiments may be modified or some or all of the technical features may be equivalently replaced, and that the features in the embodiments of the disclosure may be arbitrarily combined without conflict, and that these modifications or replacements do not depart from the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the disclosure.
Claims (48)
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| PCT/CN2019/128778 WO2021128184A1 (en) | 2019-12-26 | 2019-12-26 | Control method and control apparatus for movable carrier, and computer-readable storage medium |
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| CN114063496B (en) * | 2021-11-02 | 2024-07-02 | 广州昂宝电子有限公司 | Unmanned aerial vehicle control method and system and remote controller for remote control of unmanned aerial vehicle |
| US11999380B1 (en) * | 2021-12-17 | 2024-06-04 | Zoox, Inc. | Autonomous vehicle trajectory generation and optimization |
| CN114648574A (en) * | 2022-03-25 | 2022-06-21 | 云控智行科技有限公司 | Vehicle motion track prediction method, device and equipment |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108475074A (en) * | 2017-04-10 | 2018-08-31 | 深圳市大疆创新科技有限公司 | Holder follow-up control method and control device |
| CN110147098A (en) * | 2019-04-30 | 2019-08-20 | 杭州飞步科技有限公司 | Control method, device, device and readable storage medium of self-driving vehicle |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014187027A1 (en) * | 2013-05-22 | 2014-11-27 | 上海九鹰电子科技有限公司 | Transmission device and method, and reception device and method of remote control signal |
| WO2015126447A1 (en) * | 2013-08-15 | 2015-08-27 | Traxxas Lp | Controllable flight during automated tricks |
| CN105992980A (en) * | 2015-05-18 | 2016-10-05 | 深圳市大疆创新科技有限公司 | Unmanned aerial vehicle control method and device based on headless mode |
| CN105867407A (en) * | 2016-06-12 | 2016-08-17 | 零度智控（北京）智能科技有限公司 | Unmanned aerial vehicle as well as control device and control method thereof |
| CN106200673B (en) * | 2016-07-26 | 2019-10-18 | 中国航空工业集团公司西安飞行自动控制研究所 | Integrated automatic flight maneuver control method |
| CN110325939B (en) * | 2017-03-09 | 2023-08-01 | 深圳市大疆创新科技有限公司 | System and method for operating an unmanned aerial vehicle |
| CN106951871B (en) * | 2017-03-24 | 2020-07-28 | 北京地平线机器人技术研发有限公司 | Motion trajectory identification method and device of operation body and electronic equipment |
| CN109074088B (en) * | 2017-04-11 | 2021-12-03 | 深圳市大疆创新科技有限公司 | State detection method and device for unmanned aerial vehicle and unmanned aerial vehicle |
| CN109739264A (en) * | 2019-02-27 | 2019-05-10 | 重庆邮电大学 | A system and method for trajectory homing of small unmanned aerial vehicles based on flight instructions |
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|---|---|---|---|---|
| CN108475074A (en) * | 2017-04-10 | 2018-08-31 | 深圳市大疆创新科技有限公司 | Holder follow-up control method and control device |
| CN110147098A (en) * | 2019-04-30 | 2019-08-20 | 杭州飞步科技有限公司 | Control method, device, device and readable storage medium of self-driving vehicle |
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