CN110785722A - Parameter optimization method and device for mobile platform, control equipment and aircraft - Google Patents

Parameter optimization method and device for mobile platform, control equipment and aircraft Download PDF

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CN110785722A
CN110785722A CN201880038852.6A CN201880038852A CN110785722A CN 110785722 A CN110785722 A CN 110785722A CN 201880038852 A CN201880038852 A CN 201880038852A CN 110785722 A CN110785722 A CN 110785722A
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parameter
state
mobile platform
preset
speed
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叶长春
周游
苏坤岳
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Shenzhen Dajiang Innovations Technology Co Ltd
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Shenzhen Dajiang Innovations Technology Co Ltd
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64C—AEROPLANES; HELICOPTERS
    • B64C27/00—Rotorcraft; Rotors peculiar thereto
    • B64C27/04—Helicopters
    • B64C27/08—Helicopters with two or more rotors
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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

Abstract

The embodiment of the invention provides a method and a device for optimizing parameters of a mobile platform, control equipment and an aircraft, wherein the method comprises the following steps: determining a current power-on state of the mobile platform (S201); acquiring sensing data acquired by a mobile platform in a power-on state (S202); if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters (S203); the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states. By adopting the embodiment of the invention, the accuracy and timeliness of observation parameter optimization can be better ensured, and the mobile platform can be conveniently and safely controlled subsequently.

Description

Parameter optimization method and device for mobile platform, control equipment and aircraft
Technical Field
The embodiment of the invention relates to the technical field of electronics, in particular to a method and a device for optimizing parameters of a mobile platform and an aircraft.
Background
With the continuous development and improvement of electronic technology and automation technology, various mobile platforms capable of automatically sensing the surrounding environment and performing intelligent motion control, such as aircrafts, intelligent robots, auto-pilot cars, etc., are developed.
In order to realize intelligent motion control, some sensors are disposed on the mobile platforms, and the sensors sense the environment around the mobile platforms and the data of the mobile platforms themselves, and the motion control of the mobile platforms is completed based on the data. For example, a visual sensor based on a camera or the like, a position sensor capable of performing Positioning, such as an Inertial Measurement Unit (IMU) including an accelerometer and a gyroscope, a Global Positioning System (GPS) module, or the like, may be provided, and control of the mobile platform may be realized based on an environmental image, a posture, a speed, and other parameters of the mobile platform, a position of the mobile platform, and the like sensed by these sensors.
At present, mobile platforms such as unmanned aerial vehicles and automatic driving automobiles mainly rely on a GPS positioning mode to position the mobile platforms, and safety control is realized on the basis of accurate positioning. In order to further ensure the safety, a visual perception system depending on a computer visual algorithm can be introduced in the implementation, and the visual perception system can provide observation of information such as speed and position, so that control processing such as stable hovering and motion planning is realized. And how to process the relevant parameters calculated based on the visual perception system so as to better carry out automation and intelligent control on various mobile platforms to be a hotspot problem of research.
Disclosure of Invention
The embodiment of the invention provides a method and a device for optimizing parameters of a mobile platform and an aircraft, which can be used for optimizing different observation parameters in a targeted manner.
In one aspect, an embodiment of the present invention provides a method for optimizing parameters of a mobile platform, where a visual perception system is disposed on the mobile platform, the visual perception system includes an attitude sensor and a visual sensor, and the method includes: determining the current power-on state of the mobile platform; acquiring sensing data acquired by the mobile platform in the power-on state;
if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters;
the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
On the other hand, an embodiment of the present invention provides a device for optimizing parameters of a mobile platform, where a visual perception system is disposed on the mobile platform, the visual perception system includes an attitude sensor and a visual sensor, and the device includes: the determining module is used for determining the current power-on state of the mobile platform; the acquisition module is used for acquiring the sensing data acquired by the mobile platform in the power-on state; the optimization module is used for optimizing observation parameters of the mobile platform corresponding to the power-on state to correct the observation parameters if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data; the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
In another aspect, an embodiment of the present invention provides a control device, where the control device is configured to perform parameter optimization on a mobile platform, the control device is connected to a visual perception system of the mobile platform, the visual perception system includes an attitude sensor and a visual sensor, and the control device includes: a communication interface and a processor; the communication interface is used for being connected with a visual perception system; the processor is used for acquiring the sensing data acquired by the mobile platform in the power-on state; if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters; the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
In another aspect, an embodiment of the present invention provides an aircraft, including: the vision perception system comprises an attitude sensor and a vision sensor;
the controller is used for calculating observation parameters according to the sensing data of the attitude sensor and/or the vision sensor and determining the current power-on state of the mobile platform; acquiring sensing data acquired by the mobile platform in the power-on state; if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters; the observation parameters are obtained through calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, different observation parameters are correspondingly arranged in different power-on states, and the mobile platform is used for controlling the power assembly based on the corrected observation parameters so as to control the aircraft to move.
The embodiment of the invention can define different power-on states for the mobile platform, and pointedly optimize observation data obtained by different sensing data based on the visual perception system under different power-on states, thereby better ensuring the accuracy and timeliness of observation parameter optimization and facilitating the subsequent safer control of the mobile platform.
Drawings
FIG. 1 is a schematic structural diagram of an aircraft in accordance with an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for optimizing parameters of a mobile platform according to an embodiment of the present invention;
FIG. 3a is a schematic diagram of calculating relevant sensed data based on a visual location algorithm according to an embodiment of the present invention;
FIG. 3b is a schematic diagram of calculating relevant sensed data based on a visual location algorithm according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a parameter optimization apparatus for a mobile platform according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a control device according to an embodiment of the present invention.
Detailed Description
In the embodiment of the invention, the motion of the mobile platform is mainly combined with the positioning data of the position sensor and the observation data of the visual perception system to automatically control the mobile platform. The location sensor may be, for example, a conventional GPS location sensor, or may be another sensor capable of locating latitude and longitude coordinates, such as a compass location sensor, a galileo location sensor, or the like. The visual perception system of the embodiment of the invention mainly comprises an attitude sensor and a visual sensor, wherein the attitude sensor comprises an accelerometer and a gyroscope, for example, the attitude sensor can be an IMU module, and the visual sensor is mainly constructed based on a binocular camera.
Fig. 1 is a schematic structural diagram illustrating a mobile platform according to an embodiment of the present invention, which includes an IMU101 and a binocular vision sensor 102, where sensing data of the IMU101 and the binocular vision sensor 102 may be sent to a flight controller 103 of the aircraft, and the flight controller 103 performs calculation to obtain data that can be used to control the flight of the aircraft, for example, calculating the sensing data of the IMU101 and the binocular vision sensor 102 based on a visual positioning algorithm to obtain an observation parameter, such as data for positioning. In other embodiments, different structures and installation modes can be built on mobile platforms such as aircrafts, intelligent robots and automatic driving automobiles according to the requirements of users and different environments, so that the aim of controlling the mobile platforms more stably and safely is fulfilled.
In the embodiment of the present invention, please refer to fig. 2, which is a flowchart illustrating a parameter optimization method for a mobile platform according to the embodiment of the present invention, where the optimization method may be implemented by a single control device, and the control device may be connected to a visual perception system, on one hand, to facilitate calculation and optimization of related data of the visual perception system, and on the other hand, may output data obtained by final optimization, so as to facilitate better security control of the mobile platform. Of course, the optimization method may also be implemented by a function module in the mobile platform, through which the relevant data of the visual perception system is obtained, and then the safety control is directly performed on the mobile platform, for example, for an aircraft, it may be performed by a flight controller of the aircraft, and for an auto-pilot automobile, it may be performed by a central controller of the auto-pilot automobile.
The current power-on state of the mobile platform may be determined in S201 according to the sensing data of the mobile platform and/or the sensing data of some or all of the functional components on the mobile platform, and of course, the power-on state of the mobile platform may also be determined in other manners. In one embodiment, the power-on state of the mobile platform may also be determined according to a set control mode for the mobile platform, for example, a flight mode in which the aircraft may be set by a user to automatically fly according to a preset route through a remote controller, a hover mode for stopping flight, a standby mode after landing, and the like, which may be implemented in one embodiment based on one or more user operations of the user on the remote controller. In the embodiment of the invention, at least two power-on states can be defined for the mobile platform, so that observation parameters corresponding to the visual perception system can be optimized in a targeted manner based on safety control requirements in different power-on states. In the embodiment of the present invention, the power-on state may include, but is not limited to: motion state, hover state, resting state. When the mobile platform is an aircraft, the motion state can be a flight state, and the hovering state can be a special state of the aircraft hovering in the air; the stationary state may be described as a state in which the mobile platform is powered on but the motor is not started, and the mobile platform is placed on a ground such as a level ground, for example, when the aircraft is powered on and is on the ground to receive flight instructions.
The sensing data collected by the mobile platform in the power-on state may be acquired in S202 at the same time as or after the current power-on state of the mobile platform is determined. The sensing data is determined mainly by data output from sensors on the mobile platform, which may include, for example, position sensors, attitude sensors such as IMUs, vision sensors, and the like. In different power-on states, the required sensing data is different. In one embodiment, the required sensing data includes, in the powered state being the motion state: the state parameters of the position sensor can be any one or more of speed state parameters, altitude state parameters, signal strength parameters and speed precision estimation indexes. When the power-on state is the hovering state, the sensing data includes: data calculated based on sensing data collected by an attitude sensor, the attitude sensor including an accelerometer and a gyroscope, specifically, the sensing data may include: any one or more of an acceleration calculated based on sensing data of the accelerometer, an angle calculated based on sensing data of the gyroscope, and a velocity calculated based on sensing data of the accelerometer. When the power-on state comprises a standing state, the sensing data comprises: the measurement values of the gyroscope in the attitude sensor, specifically, the sensor data may include: zero axis deviation of the gyroscope.
After the sensing data in the powered-on state is acquired, in S203, if it is determined that the mobile platform is in the stable state in the powered-on state according to the sensing data, the observation parameters of the mobile platform corresponding to the powered-on state are optimized to correct the observation parameters.
Because the mobile platform is already in the corresponding power-on state, the observation parameters to be optimized at this time are the observation parameters of the mobile platform in the current power-on state, and the observation parameters are obtained by calculation according to the sensing data of the attitude sensor and/or the visual sensor. In one embodiment, the observation parameters corresponding to the visual perception system may be calculated based on a visual positioning algorithm on the sensing data of the attitude sensor (e.g., an inertial measurement unit) and/or the visual sensor. The Visual localization algorithm may be, for example, a VO (Visual odometer) algorithm or a VIO (Visual-inertial odometer) algorithm.
The vision perception system based on the combination of vision and inertial navigation can complete the positioning function of the mobile platform by only one camera (such as a camera) and one IMU at least, so that the mobile platform can perceive the position of the mobile platform relative to the environment indoors and the like under the conditions of no GPS or weak GPS, further upper-layer application such as navigation and the like is completed, and the application range of the mobile platform is expanded. The visual localization algorithm can be divided into loosely-coupled (loseley-coupled) and tightly-coupled (tiglyy-coupled) according to whether or not image features of an image sensed by the visual sensor are added to the state vector.
The loose coupling does not add image features to the state vector, but uses the image as a black box, independently calculates the pose (position and posture) of the camera (such as a vision sensor) based on the image, and then fuses with the IMU information, as shown in fig. 3 a. The loose coupling algorithm can be understood as a VO algorithm.
The tight coupling is to add image features to the state vector and use the raw data of the two sensors to jointly estimate a set of vectors, as shown in fig. 3b, which fully uses the sensing data of the attitude sensor (e.g. inertial measurement unit) and the vision sensor, and can achieve a relatively high positioning accuracy. The tight coupling algorithm may be understood as the VIO algorithm.
It is understood that data from other sensors, such as a position sensor such as a GPS, may be incorporated into the loose coupling or tight coupling algorithm, and may be set according to the needs.
In the embodiment of the invention, an IMU + vision sensor can be selected and used, and a VIO algorithm of 6-DoF (Degrees of freedom) is used for calculating and obtaining the observation parameters of the mobile platform. The six degrees of freedom refer to rotation of an x axis, a y axis and a z axis and translation in directions of the x axis, the y axis and the z axis. The calculated observation parameters may include: visual velocity data, first and second angle parameters, and gyroscope parameters in an attitude sensor. Wherein the first angle parameter comprises: the method comprises the following steps that a first included angle between the north direction estimated by a vision perception system and the true north direction is obtained by calculating sensing data collected by a position sensor and a vision sensor; the second angle parameter includes: and a second included angle between the horizontal plane and the real horizontal plane estimated by the vision perception system is obtained by calculating the sensing data acquired by the attitude sensor. The gyroscope parameters include: zero axis deviation of the gyroscope in the attitude sensor.
After the observation parameters are obtained, and it is determined that the mobile platform is in a stable state in the power-on state according to the sensing data, the observation parameters may be optimized in S203 to control the mobile platform. The current position, posture and the like of the mobile platform can be corrected based on the relevant parameters obtained after the observation parameters are optimized, so that more accurate relevant visual positioning parameters can be obtained, and finally, the mobile platform is subjected to safety control according to the more accurate visual positioning parameters. For example, a drone as described in fig. 1 may be controlled to fly more stably, hover more stably. In one embodiment, the optimization of the observation parameters may be based on a kalman filter to optimize the observation parameters of the mobile platform.
In addition, in the optimization process, for some power-on states, such as the motion states mentioned later, some reference parameters may be utilized to optimize the observation parameters. Specifically, the method of the embodiment of the present invention includes: acquiring reference parameters corresponding to observation parameters of the mobile platform in a power-on state; optimizing observation parameters, including: and optimizing the difference data between the reference parameters and the observation parameters to obtain observation compensation data of the observation parameters. The reference parameter may be, for example, a relatively accurate parameter sensed by a position sensor such as a GPS sensor, and the observation parameter calculated by an algorithm such as a VIO is optimized based on the relatively accurate parameter. The specific optimization method can refer to the following embodiments, and the optimization of the observation parameters such as the visual velocity data and the first angle parameter data can be performed.
In the embodiment of the invention, before the observation parameters are optimized, whether the mobile platform is in a stable state in a power-on state can be determined according to the sensing data. Therefore, some conditions can be defined, when the sensing data meet the conditions, the mobile platform is considered to be in a stable state in the current power-on state, and the observation parameters can be optimized. Triggering optimization based on these defined conditions may ensure, to some extent, that an otherwise superior observed parameter is not erroneously optimized, or that an observation parameter is not unnecessarily optimized. In one embodiment, prior to performing S203, the method may include: detecting whether the sensing data meet preset optimization conditions or not; and if the sensing data meet the preset optimization condition, determining that the mobile platform is in a stable state in the power-on state so as to execute the step of optimizing the observation parameters in the step S203 and control the step of the mobile platform.
The following describes in detail the optimization of the corresponding observation parameters of the mobile platform in the corresponding power-on state, based on different power-on states of the mobile platform, and taking the mobile platform as an example:
research shows that for a single-purpose VIO system, for example, in the case that some aircrafts are only provided with monocular vision sensors on the left and right sides of the aircraft, or images of binocular vision sensors in high altitude have no difference basically and are degraded into the monocular vision sensors, the accuracy of observation parameters calculated based on a VIO algorithm cannot be guaranteed. Moreover, when the aircraft moves at a constant speed, the accelerometer in the attitude sensor IMU basically does not observe (acceleration is measured by the accelerometer), the whole algorithm is degenerated to SfM (Structure from motion), and the accuracy of the observation parameters calculated based on the VIO algorithm cannot be guaranteed. For example, it has been found through testing that when the aircraft moves at a constant speed of 10m/s at a true speed, the observed parameter (i.e., the observed speed) calculated based on the VIO algorithm may be only 0.92 times the true speed, i.e., 9.2 m/s. That is, based on the above, optimization of the observation parameters in the motion state may be selected to obtain the best observation parameters as possible.
In one embodiment, a motion state is defined as one of the power-on states of the mobile platform, and the mobile platform is further provided with the above-mentioned position sensors such as GPS, beidou, galileo, and the like. In the motion state, the observation value based on the position sensor can be selected to correct the observation parameter of the visual perception system, that is, the adopted observation value can correspond to the reference parameter mentioned above, and optimization is performed based on the difference data between the reference parameter corresponding to the position sensor and the observation parameter, so as to obtain the observation compensation data of the observation parameter. Based on this, it is necessary to ensure that the observed value of the position sensor is a relatively accurate value, and under this condition, it is necessary to perform corresponding evaluation on the data of the position sensor to determine whether the observed value meets the preset optimization condition. Therefore, the sensing data includes the acquired state parameters of the position sensor, that is, whether the sensing signal (such as the positioning signal) of the position sensor is better or not is judged according to the state parameters of the position sensor, and it is determined that the sensing data meets the preset optimization condition under the condition that the sensing signal is better. Specifically, in the motion state, the state parameters of the position sensor include: one or more of attitude parameters, signal strength parameters and speed precision estimation indexes, and correspondingly, the sensing data meeting the preset optimization conditions comprises the following steps: the attitude parameter meets any one or more of a preset attitude condition, the signal intensity indicated by the signal intensity parameter is greater than a preset intensity threshold value, and the speed precision estimation index is less than a preset index threshold value. As long as the selected sensing data in the motion state satisfy the preset optimization condition, the mobile platform can be considered to be in a stable state in the motion state.
In one embodiment, the pose parameters include: a speed state parameter and/or an altitude state parameter; correspondingly, the gesture parameters meeting the gesture conditions include: the speed indicated by the speed status parameter is greater than a preset speed threshold and/or the altitude indicated by the altitude status parameter is greater than a preset altitude threshold. In one embodiment, it may be specifically determined whether the module length of the horizontal velocity calculated based on the sensing data of the position sensor is greater than 3m/s (or other velocity threshold), and whether the altitude is greater than 12 m (or other altitude threshold determined according to the parameters of the two cameras in the vision sensor, and specifically, whether the preset optimization condition is satisfied may be determined based on the resolution, the focal length, and the binocular distance of the two cameras). The higher the speed is, the higher the observation quality of the GPS and other position sensors is, the higher the reliability is, and meanwhile, the high-altitude high-speed operation is also a time period in which the VIO algorithm is easy to have problems, so that when the speed is greater than 3m/s and the height is greater than 12 meters, the dynamic performance of the position sensors can be considered to be better, and the observation parameters calculated by the VIO algorithm can be optimized finally based on the reference parameters determined by the position sensors. Meanwhile, based on attitude parameters of position sensors such as a GPS and the like, the state of the mobile platforms such as aircrafts and the like in motion can be determined.
In one embodiment, the signal strength of the position sensor such as the GPS may also be referred to, and if the signal strength is greater than a preset strength threshold value, for example, 3, the observation value obtained based on the position sensor such as the GPS may also be considered to be more accurate, and may be used to optimize the observation parameter calculated by the VIO algorithm. In addition, when the signal strength of the position sensor is referred to, the DOP (Dilution of precision) index of the GPS can be further referred to, so as to comprehensively evaluate whether the observed value of the position sensor is better.
In one embodiment, a speed accuracy estimation index of the position sensor such as the GPS may be further referred to, and if the speed accuracy estimation index is smaller than a preset index threshold value, for example, 20, the observation value obtained based on the position sensor such as the GPS may be considered to be more accurate, and may be used to optimize the observation parameter calculated by the VIO algorithm.
At one isIn an embodiment, the optimization of the observation parameters in the motion state may be an optimization of visual velocity data comprised by the observation parameters. That is, in the motion state, the observation parameters are optimized, including: optimizing visual speed data of a corresponding mobile platform in a motion state; the visual speed data is obtained by calculating the sensing data collected by the attitude sensor and the visual sensor. Visual velocity data V calculated based on VIO algorithm vioThe specific calculation method of (2) can refer to the existing method.
In the embodiment of the invention, the optimization of the visual velocity data can be performed by calling a preset Kalman filter, and the main idea is to optimize the scale residual error of the velocity to be corrected and utilize the scale residual error of the corrected velocity to observe the parameters (namely the visual velocity data V) vio) Compensation is performed. The residual equation used in this idea is as follows:
wherein, two Jacobian matrices are expressed by the following formula:
Figure BDA0002313356240000092
in the above equations 1 and 2, V GPSRepresenting the velocity calculated from GPS-based sensed data, which may be referred to as a positioning velocity parameter, V GPS,xAnd V GPS,yRespectively represent V GPSThe velocity resolved on the x-axis and y-axis in the coordinate system of the GPS sensor may also be understood as a positioning velocity parameter, which may be regarded as a reference parameter of the above-mentioned position sensor, and which is used to optimize the observation parameter (visual velocity data). In the same way, V vio,xAnd V vio,yRespectively represent V vioSpeed, δ s, resolved on the x-axis and y-axis in the coordinate system (VIO coordinate system) corresponding to the vision sensor xAnd δ s yIs a need for Kalman filter optimizationObtained data, δ s xAnd δ s yCan be respectively expressed as a pair V vioAnd a speed compensation amount for compensating for the speed on the x-axis and the y-axis in the coordinate system corresponding to the vision sensor. After obtaining the expression of the scale residual r of the speed and two Jacobian matrixes, optimizing and obtaining a speed compensation quantity based on a Kalman filter so as to obtain a V pair based on the speed compensation quantity vio,xAnd V vio,yRespectively carrying out compensation optimization to finally finish V vioAnd (4) optimizing.
In one embodiment, the velocity compensation amount may be optimized by using a non-linear Extended Kalman Filter (No-linear Kalman Filter) with an error state. Specifically, for the above-mentioned formula 1, J is specifically defined as xAnd J yAnd, and
Figure BDA0002313356240000093
as the input data of the No-linear error state EKF, the output data obtained by optimization is deltas xAnd δ s yObtaining the velocity compensation amount deltas xAnd δ s yThen, V is obtained based on VIO algorithm vio,xAnd V vio,yOn the basis, the corresponding speed compensation amount is added, and the optimization of the visual speed data is completed.
In one embodiment, the optimizing of the observation parameters in the motion state may mainly be optimizing a first angle parameter included in the observation parameters, that is, optimizing the observation parameters in the motion state includes: optimizing a first angle parameter of the corresponding mobile platform in a motion state; wherein the first angle parameter comprises: and calculating the sensing data acquired by the position sensor and the vision sensor to obtain a first included angle between the estimated north direction and the true north direction of the vision sensing system. For example, the first angle parameter may specifically include: the deviation (e.g., yaw angular deviation) between the north direction estimated by the vision perception system and the true north direction (e.g., the north direction determined from the sensing data of the GPS) is calculated based on the sensing data collected by the position sensor and the vision sensor. The first angle parameter calculated based on the sensing data acquired by the position sensor and the vision sensor may be calculated by using an existing calculation method.
In the embodiment of the present invention, the optimization of the first angle parameter may also be performed by calling a preset kalman filter, and the idea adopted in the optimization process may include: and correcting the deviation between the estimated north direction and the true north direction of the visual perception system, and then transferring the speed observation under the coordinate system where the GPS position sensor is located to the VIO coordinate system to obtain the residual error correction speed so as to finish the correction. Because the coordinate system of the IMU is aligned with the coordinate system of the GPS, the deviation between the VIO coordinate system and the coordinate system of the IMU is indirectly corrected. The residual formula under this idea is as follows:
wherein, two Jacobian matrices are expressed by the following formula:
Figure BDA0002313356240000102
wherein the content of the first and second substances, can be defined as: the two-dimensional GPS coordinate system rotates clockwise to the angle of the VIO coordinate system.
Figure BDA0002313356240000104
The value of the output needs to be optimized for the kalman filter, representing the amount of angular compensation of the first angular parameter. Similarly, after obtaining the residual error r and the expression of the jacobian matrix, a preset kalman filter may be specifically invoked to optimize and obtain a corresponding angle compensation amount, so as to perform compensation optimization on a first angle parameter, such as the yaw angle, corresponding to the visual perception system. δ V in equation 3 refers to a velocity compensation amount of velocity in the VIO coordinate system calculated based on VIO, and V in equation 4 xAnd v yThen expressed as velocity calculated based on VIO at VIO coordinatesDecomposition speed on the x-axis and y-axis of the system.
In one embodiment, the angle compensation amount of the first angle parameter may be optimized by using a non-linear extended kalman filter (No-linear error state EKF) with an error state. Specifically, for the above-mentioned formula 3, J is specifically defined as vAnd
Figure BDA0002313356240000105
and
Figure BDA0002313356240000111
as input data of the No-linear error state EKF, the optimized output data comprises
Figure BDA0002313356240000112
The angle compensation quantity of the first angle parameter is obtained
Figure BDA0002313356240000113
Later, already obtained based on the VIO algorithm
Figure BDA0002313356240000114
On the basis, the optimization of the first angle parameter is completed by adding the angle compensation quantity of the first angle parameter.
In an embodiment, the attitude sensor includes a gyroscope, and before the first angle parameter is optimized, it may further detect whether a difference between a current reading ω of the gyroscope and a current zero-axis deviation of the gyroscope satisfies a preset condition, for example, it may detect whether a modular length between the current reading ω of the gyroscope and the current zero-axis deviation of the gyroscope is smaller than a preset threshold, and if the modular length is smaller than the preset threshold, it indicates that a current attitude of the mobile platform is relatively stable, and it may be considered that the mobile platform does not rotate around the yaw axis, and then the first angle parameter, for example, the yaw angle, may be compensated and optimized.
It can be seen from the above embodiments that, on one hand, a motion state in which errors easily occur in the visual velocity parameter and the first angle parameter in the observation parameters is determined, and the visual velocity data and the first angle parameter in the observation parameters calculated based on the VIO algorithm are optimized in the motion state, so that the optimization of the observation parameters is more targeted; on the other hand, the reference parameters required by the optimization of the observation parameters are screened, and only when the conditions are met, the sensing data of the position sensor can be utilized to determine the reference parameters, so that the accuracy of the optimization of the observation parameters is better ensured.
In addition, in one embodiment, is for V vioWhether the optimization is performed or the first angle parameter is optimized can be selected as desired. Whether the difference between the positioning speed parameter and the visual speed data meets a preset difference condition can be judged; and if so, triggering to execute optimization of the visual speed data of the corresponding mobile platform in the motion state, and further taking the positioning speed parameter as a reference parameter to participate in the optimization of the visual speed data during optimization. If the first angle parameter is being optimized at this time, the optimization of the first angle parameter may be cancelled and instead the optimization of the visual velocity data may be performed. That is, the optimization of the visual velocity data is given a high priority, but is not always corrected, when a difference in scale greater than a certain threshold V is detected HSuch as: the difference value between the module length of the positioning speed parameter and the module length of the visual speed data is larger than a preset threshold value | | V GPS||-||V VIO||>V HV may be performed on the visual velocity data interrupting the optimization of the first angular parameter vioAnd (6) optimizing.
Additionally, in one embodiment, to ensure that an accurate V is used in the calculation GPSThe lever arm error caused by different installation positions of the position sensor such as the GPS and the attitude sensor IMU is avoided, the calculated speed of the position sensor such as the GPS can be transferred to the IMU end, and the converted speed is used as the observed value of the position sensor, namely V GPS. That is, the positioning speed parameter included in the sensing data is calculated from the initial positioning speed parameter, which is calculated from the positioning data sensed by the position sensor. It is composed ofIn the method, a positioning speed parameter is calculated according to the initial positioning speed parameter, and the method comprises the following steps: mapping calculation is carried out on the initial positioning speed parameter according to the mapping parameter to obtain a mapping speed parameter of the position sensor under a coordinate system where the attitude sensor is located; and taking the mapping speed parameter as a positioning speed parameter. In one embodiment, performing mapping calculation on the initial positioning speed parameter according to the mapping parameter to obtain a mapping speed parameter of the position sensor in a coordinate system where the attitude sensor is located includes: acquiring angular velocity parameters sensed by an attitude sensor, and acquiring a coordinate system rotation transformation matrix between the attitude sensor and a position sensor; and calculating to obtain a mapping speed parameter of the position sensor in the coordinate system of the attitude sensor according to the angular speed parameter, the coordinate system rotation transformation matrix and the initial positioning speed parameter. In one embodiment, the specific conversion formula is as follows:
V IMU＝V GPS-R wi[m gyro] ×T IGequation 5;
wherein, V IMURepresenting the speed of conversion to IMU terminal, corresponding to V as described above GPS，V GPSIs the original GPS-end velocity, i.e., the initial positioning velocity parameter, R wiIs a rotation transformation matrix from the coordinate system where the IMU is located to the world coordinate system, m gyroIs angular velocity measured by a gyro] ×Is a matrix representation of cross product, T IGRefers to the translation vector of the GPS pointing to the IMU in the IMU coordinate system.
Further, in the embodiment of the present invention, an error caused by time asynchronization between the position sensor such as the GPS and the IMU may be processed. Specifically, synchronization can be achieved through a timestamp, and the initial positioning speed parameter is obtained by calculating positioning data sensed by the position sensor after a preset time threshold of sensing data acquired by the attitude sensor is acquired. For example, the GPS observation is typically 500ms, so after the IMU value is obtained, it takes about 500ms (the preset duration threshold) to compare with the GPS speed.
In one embodiment, some feature points with poor observation or matching errors may be introduced during the VIO calculation process, but these feature points cannot be completely eliminated and may gradually make the pose calculated by the VIO wrong, causing the VIO coordinate system to deviate from the reference coordinate system of the IMU, and the corresponding observation parameters calculated thereby, such as the above-mentioned visual velocity data, to be inaccurate as feedback. In order to further ensure the stability of the VIO posture and reduce the posture deviation caused by adopting wrong characteristic points or characteristic points with poor quality for calculation, gravity updating, namely gravity optimization, can be added into the VIO, and the horizontal included angle deviation between the estimated horizontal plane in the VIO coordinate system and the real horizontal plane in the world coordinate system can be corrected in the stable hovering state.
Therefore, the embodiment of the present invention further defines a hovering state as one of the power-on states of the mobile platform, where the hovering state is mainly defined for the mobile platform such as the unmanned aerial vehicle shown in fig. 1, and the hovering state refers to that the mobile platform such as the unmanned aerial vehicle stops at a certain position in the air. In the hovering state, the used reference parameters mainly include the gravity acceleration, namely 9.8m/s 2. And optimizing the horizontal included angle deviation between the estimated horizontal plane under the VIO coordinate system and the real horizontal plane under the world coordinate system through the gravity acceleration.
In the hovering state, sensing data includes: sensed data collected by the attitude sensor. The attitude sensor may be, for example, the IMU described above, including an accelerometer and a gyroscope, and the sensing data may be considered to be in a hovering state and stable when the mobile platform is hovering after meeting the preset optimization condition.
Gravity correction, that is, optimization of the second angle parameter included in the observation parameter is performed when the vehicle is hovering stably, the acceleration is substantially 0, only the gravity acceleration towards the geocentric can be measured, and therefore, the correction by gravity is accurate. Whether the unmanned aerial vehicle aircraft is in the stable hovering state or not can be obtained by utilizing the existing state quantity, obtaining a corresponding hovering state signal from flight control, and even initiating a notification that the mobile platform is in the hovering state through a remote control signal after the unmanned aerial vehicle is observed and judged to be hovering stably by a user. And when the acceleration module length, the gyroscope module length and the speed module length are judged to be small enough, the aircraft can be proved to be stably hovered. In one embodiment, the sensing data satisfying the preset optimization condition may include any one or more of the following cases:
the acceleration mode length calculated based on the sensing data of the accelerometer is smaller than a preset acceleration mode length threshold, and a specific expression can be represented as: | | m a-b a|| 2<a thWherein m is aRefers to an acceleration calculated from the sensed data of the accelerometer, b aIs the zero axis deviation, a, of the accelerometer thIs an acceleration mode length threshold;
the angle mode length calculated based on the sensing data of the gyroscope is smaller than a preset angle mode length threshold, and a specific expression can be expressed as: | | m ω-b ω|| 2<ω thWherein m is ωRefers to an angle b calculated from the sensed data of the gyroscope ωIs the zero axis deviation, omega, of the gyroscope thRefers to the angle mode length threshold;
the velocity mode length calculated based on the sensing data of the accelerometer is smaller than a preset velocity mode length threshold, and a specific expression can be represented as: i V 2||<V thWherein V refers to a velocity calculated based on sensing data of the accelerometer, V thIs referred to as the velocity mode length threshold.
That is, as long as the sensing data in the hovering state satisfy the preset optimization condition, the mobile platform may be considered to be in a stable state in the hovering state, that is, stable hovering.
It should be further noted that the updating frequency of the IMU data is relatively high, for example, 200Hz can be reached, while the updating speed of the VIO algorithm is relatively low, for example, only 20Hz, and in order to ensure the accuracy of the data, a preset low-pass filter may be invoked to filter the sensing data collected by the attitude sensor; and processing the data obtained after filtering to obtain the sensing data of the mobile platform in the power-on state. Namely, the IMU data is subjected to low-pass filtering, such as second-order Butterworth filtering, the cut-off frequency is set to be 20Hz, high-frequency noise can be filtered, and the sensing data, namely the sensing data acquired by the attitude sensor, is more accurate.
The gravity correction performed in the hovering state is optimization of a second angle parameter included in the observation parameter, and the optimization of the observation parameter includes: optimizing a second angle parameter of the corresponding mobile platform in the hovering state; wherein the second angle parameter includes: and a second included angle between the horizontal plane estimated by the visual perception system and the real horizontal plane under the world coordinate system is calculated by the second included angle according to the sensing data acquired by the attitude sensor.
The residual error formula used when the second angle parameter is optimized is as follows:
wherein, the expression of the Jacobian matrix is as follows:
Figure BDA0002313356240000142
wherein θ is: horizontal plane included angle m between horizontal plane determined by two-dimensional GPS position sensor (in world coordinate system) and horizontal plane estimated in VIO coordinate system aAs measured by an accelerometer, b aIs the zero axis offset of the accelerometer. g is the acceleration of gravity, typically 9.8m/s 2. And delta theta is a compensation quantity of the second angle parameter and is obtained by optimizing the second angle parameter by using a Kalman filter. After the residual error r and the Jacobian matrix are obtained, a preset Kalman filter can be called to obtain a second angle parameter compensation quantity, and the second angle parameter compensation quantity is added on the basis of a second angle parameter calculated based on a visual perception system and a VIO algorithm to complete optimization of the observation parameter. R in equation 6 wiIs a rotation transformation matrix from the coordinate system in which the IMU is located to the world coordinate system, and [ 2 ] in equation 7] ×Is a matrix representation of cross product.
In one embodiment, the second angle parameter compensation amount may be obtained by using a non-linear extended kalman filter (No-linear error state EKF) optimization of the error state.Specifically, for the above-mentioned formula 6, J is specifically defined as θAnd J bAnd, and
Figure BDA0002313356240000143
and as the input data of the No-linear error state EKF, optimizing to obtain output data comprising delta theta, and after obtaining the compensation quantity delta theta of the second angle parameter, adding the compensation quantity of the second angle parameter on the basis of the theta already obtained based on the VIO algorithm to complete the optimization of the second angle parameter.
Based on the description of the above embodiment, on one hand, for the case that the second angle parameter in the observation parameters is easily estimated incorrectly, it is determined that the second angle parameter is optimized based on the measurement value of the accelerometer, the zero axis deviation of the accelerometer, the gravitational acceleration and other reference parameters in the hovering state, so that the second angle parameter can be optimized more accurately, and on the other hand, a determination condition for determining that the second angle parameter is in the stable hovering state is defined, so that the accurate relevant reference parameter can be obtained without being interfered by other data, and the accuracy of optimizing the second angle parameter is better ensured.
Further, research shows that a user of the mobile platform does not immediately control the mobile platform to move after the mobile platform is powered on, for example, for an aircraft, the user may lift the aircraft to walk around to find a flying point, the process generates large shaking, the aircraft is in an inverted state, and if the user immediately controls the aircraft to take off after finding a suitable flying point, the attitude estimation of the aircraft is not converged or is slowly converged, and an incorrect attitude is calculated based on a VIO algorithm, so that the suspension stop after taking off is unstable.
Therefore, in one embodiment, the static state is defined as one of the power-on states of the mobile platform, in the static state, the reference parameter for optimizing the zero-axis deviation of the gyroscope may be the current reading of the gyroscope, and since the mobile platform is static, the current reading of the gyroscope is theoretically 0. The sensing data in the static state comprises: in order to accelerate the calculation convergence rate, the measurement value of the gyroscope in the attitude sensor may be optimized, specifically, the parameter of the gyroscope in the attitude sensor, that is, the zero axis deviation bias of the gyroscope described above may be optimized. The correction of the zero axis deviation bias of the gyroscope needs to be performed when the mobile platform is in a static state (specifically, when the mobile platform is in a ground state and the motor is not started), as in the above-mentioned stable hovering, the correction may be obtained from flight control by using the existing state observation quantity, or may be notified by a remote controller or other device after the mobile platform is in a static state through observation and determination by a user.
In the embodiment of the present invention, a determination process may also be performed, that is, determining that the sensing data satisfies the preset optimization condition includes: the modular length of the mean value of the zero axis deviation of the gyroscope is smaller than a preset first modular length threshold value, and/or the modular length of the variance of the zero axis deviation of the gyroscope is smaller than a preset second modular length threshold value. Specifically, first, the observed value of the gyroscope within the latest N seconds (for example, 1 second), that is, the bias of the calculated gyroscope is taken, the mean value μ and the standard deviation σ are obtained, and the condition | | | | μ | | magnetism needs to be satisfied 2<μ T，||σ 2||<σ T，μ TThe threshold may take 0.05 (or other value), σ, for the mean value TThe standard deviation threshold can be 0.005 (or other values) to determine, the mobile platform is considered to be in a static state if the standard deviation threshold meets the condition, and the mobile platform is considered to be in a stable state in the static state, namely stable static state, and the bias of the optimized gyroscope can be updated, otherwise, the bias is not optimized.
In one embodiment, in the process of optimizing the gyroscope parameters of the attitude sensor in the corresponding mobile platform in the static state, the calculation expression of the residual error is as follows:
Figure BDA0002313356240000161
wherein, the expression of the Jacobian matrix is as follows:
Figure BDA0002313356240000162
wherein m is ωRefers to an angle determined based on sensed data of a gyroscope, b ωThe zero-axis deviation of the current gyroscope is referred to, and I is an Identity matrix Identity unit matrix. δ b ωIs a value obtained by optimization based on a Kalman filter, is expressed as a compensation quantity of zero axis deviation of the gyroscope, and the bias of the gyroscope obtained by current calculation is added with the delta b ωThe optimization of the gyroscope parameters in the attitude sensor can be completed.
In one embodiment, a compensation amount of the zero axis deviation of the gyroscope can be obtained by adopting a nonlinear extended Kalman filter (No-linear error state EKF) optimization of an error state. Specifically, for the above mentioned formula 8, it will be specifically
Figure BDA0002313356240000163
And m ω-b ωThe output data obtained by optimization is delta b as the input data of the No-linear error state EKF ωObtaining the compensation delta b of the zero-axis deviation of the gyroscope ωThen, in b which is already obtained based on VIO algorithm ωOn the basis, add delta b ωAnd the optimization of the zero axis deviation of the gyroscope is completed.
Based on the description of the above embodiment, on one hand, a scene in which errors are likely to occur in the zero axis deviation of the gyroscope in the observation parameters is determined, and a static state is determined, so that the optimization of the zero axis deviation of the gyroscope is rapidly completed in the static state, and on the other hand, a condition for determining whether the mobile platform is in the static state is defined, so that whether the mobile platform is in the static state can be accurately determined, and the accuracy for optimizing the zero axis deviation of the gyroscope is further well ensured.
The embodiment of the invention can define different power-on states for the mobile platform, and pointedly optimize observation data obtained by different sensing data based on the visual perception system under different power-on states, thereby better ensuring the accuracy and timeliness of observation parameter optimization and facilitating the subsequent safer control of the mobile platform. And from the perspective of better optimizing the observation data calculated by the VIO, the observation parameters are optimized by selecting the power-on states under different judgment conditions, so that the accuracy of optimization of the corresponding observation parameters can be ensured, and the mobile platform can be controlled more accurately.
Fig. 4 is a schematic structural diagram of a device for optimizing parameters of a mobile platform according to an embodiment of the present invention; the device may be provided in a separate control device or in a corresponding control module of the mobile platform, for example in the case of an aircraft, in the flight controller of the aircraft. In the embodiment of the invention, a visual perception system is arranged on the mobile platform, the visual perception system comprises an attitude sensor and a visual sensor, and the device comprises the following modules.
A determining module 401, configured to determine a current power-on state of the mobile platform; an obtaining module 402, configured to obtain sensing data acquired by the mobile platform in the power-on state; an optimization module 403, configured to optimize an observation parameter of the mobile platform corresponding to the powered-on state to correct the observation parameter if it is determined that the mobile platform is in a stable state in the powered-on state according to the sensing data; the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
In an embodiment, before the acquiring the observation parameter of the mobile platform in the power-on state, the acquiring module 402 is further configured to detect whether the sensing data meets a preset optimization condition; if the sensing data meets the preset optimization condition, it is determined that the mobile platform is in a stable state in the power-on state, and the optimization module 403 may be triggered to optimize the existing observation parameters.
In one embodiment, the powered-up state comprises a motion state, the mobile platform further comprises a position sensor, and the sensing data comprises: and acquiring the state parameters of the position sensor.
In one embodiment, the state parameters include attitude parameters, signal strength parameters, and velocity accuracy estimation indicators; the sensing data meeting the preset optimization condition comprises the following steps: the attitude parameter meets any one or more of a preset attitude condition, the signal intensity indicated by the signal intensity parameter is greater than a preset intensity threshold value, and the speed precision estimation index is less than a preset index threshold value.
In one embodiment, the pose parameters include: a speed state parameter and a height state parameter; the attitude parameter satisfying the attitude condition includes: the speed indicated by the speed state parameter is greater than a preset speed threshold value, and/or the height indicated by the height state parameter is greater than a preset height threshold value.
In one embodiment, the observed parameters include: visual speed data; the optimization module 403 is configured to optimize the visual velocity data of the corresponding mobile platform in the motion state when the optimization module is configured to optimize the observation parameters; and the visual speed data is obtained by calculating the sensing data collected by the attitude sensor and the visual sensor.
In one embodiment, the observed parameters include: a first angle parameter; the optimization module 403 is configured to optimize a first angle parameter of the mobile platform corresponding to the motion state when the optimization module is configured to optimize the observation parameter; wherein the first angle parameter comprises: the first included angle between the north direction estimated by the vision perception system and the true north direction is obtained by calculating sensing data collected by the position sensor and the vision sensor.
In one embodiment, the sensed data includes: the device further includes a determining module 404, where the determining module 404 is configured to determine whether a difference between the positioning speed parameter and the visual speed data meets a preset difference condition before optimizing the visual speed data of the corresponding mobile platform in the motion state; if yes, triggering the optimization module 403 to optimize the visual speed data of the corresponding mobile platform in the motion state.
In one embodiment, the difference between the positioning speed parameter and the visual speed data satisfying the preset difference condition comprises: the difference between the module length of the positioning speed parameter and the module length of the visual speed data is larger than a preset threshold value.
In one embodiment, the positioning speed parameter included in the sensing data is calculated according to an initial positioning speed parameter, and the initial positioning speed parameter is calculated according to the positioning data sensed by the position sensor; the device further comprises a calculating module 405, wherein the calculating module 405 is configured to calculate the positioning speed parameter according to the initial positioning speed parameter. In an embodiment, the calculating module 405 performs mapping calculation on the initial positioning speed parameter according to a mapping parameter, to obtain a mapping speed parameter of the position sensor in a coordinate system where the attitude sensor is located; and taking the mapping speed parameter as a positioning speed parameter.
In one embodiment, the calculating module 405, when configured to perform mapping calculation on the initial positioning speed parameter according to a mapping parameter to obtain a mapping speed parameter of the position sensor in a coordinate system of the attitude sensor, is configured to obtain an angular speed parameter sensed by the attitude sensor, and obtain a coordinate system rotation transformation matrix between the attitude sensor and the position sensor; and calculating to obtain a mapping speed parameter of the position sensor in the coordinate system of the attitude sensor according to the angular speed parameter, the coordinate system rotation transformation matrix and the initial positioning speed parameter.
In one embodiment, the initial positioning speed parameter is obtained by calculating positioning data sensed by the position sensor after acquiring a preset time threshold of sensing data acquired by the attitude sensor.
In one embodiment, the power-up state comprises a hover state, and the sensory data comprises: the attitude sensor collects sensed data.
In one embodiment, the attitude sensor includes an accelerometer and a gyroscope; the sensing data meeting the preset optimization condition comprises the following steps: and the acceleration mode length calculated based on the sensing data of the accelerometer is less than a preset acceleration mode length threshold value, the angle mode length calculated based on the sensing data of the gyroscope is less than a preset angle mode length threshold value, and the speed mode length calculated based on the sensing data of the accelerometer is less than a preset speed mode length threshold value.
In an embodiment, the obtaining module 402, when configured to obtain the sensing data of the mobile platform in the power-on state, is configured to invoke a preset low-pass filter to filter the sensing data collected by the attitude sensor; and processing the data obtained after filtering to obtain the sensing data of the mobile platform in the power-on state.
In one embodiment, the observed parameters include: a second angle parameter; the optimizing module 403, when configured to optimize the observation parameter, is configured to optimize a second angle parameter of the mobile platform corresponding to the hovering state; wherein the second angle parameter comprises: and a second included angle between the horizontal plane and the real horizontal plane estimated by the vision perception system is calculated according to the sensing data collected by the attitude sensor.
In one embodiment, the power-up state comprises a rest state, and the sensing data comprises: a measurement of a gyroscope in the attitude sensor.
In one embodiment, the sensing data satisfying the preset optimization condition includes: the modular length of the mean value of the zero axis deviation of the gyroscope is smaller than a preset first modular length threshold value, and/or the modular length of the variance of the zero axis deviation of the gyroscope is smaller than a preset second modular length threshold value.
In one embodiment, the observed parameters include: gyroscope parameters in the attitude sensor; the optimization module 403 is configured to optimize, when the optimization module is configured to optimize the observation parameters, the gyroscope parameters of the attitude sensor in the mobile platform corresponding to the static state; wherein the gyroscope parameters include: and zero axis deviation of a gyroscope in the attitude sensor.
In an embodiment, the obtaining module 402 is further configured to obtain a reference parameter corresponding to the observation parameter of the mobile platform in the power-on state; the optimizing module 403 is configured to optimize difference data between the reference parameter and the observation parameter when the optimizing module is configured to optimize the observation parameter, so as to obtain observation compensation data of the observation parameter.
In the embodiments of the present invention, the specific implementation of each module of the apparatus may refer to the description of related content in each of the foregoing embodiments, which is not repeated herein.
The embodiment of the invention can define different power-on states for the mobile platform, and pointedly optimize observation data obtained by different sensing data based on the visual perception system under different power-on states, thereby better ensuring the accuracy and timeliness of observation parameter optimization and facilitating the subsequent safer control of the mobile platform. And from the perspective of better optimizing the observation data calculated by the VIO, the observation parameters are optimized by selecting the power-on states under different judgment conditions, so that the accuracy of optimization of the corresponding observation parameters can be ensured, and the mobile platform can be controlled more accurately.
Referring to fig. 5, it is a schematic structural diagram of a control device according to an embodiment of the present invention, and the control device according to the embodiment of the present invention may be arranged in a mobile platform as needed to optimize data of the mobile platform. The control device can also be used as an external device connected with the mobile platform and used for receiving the relevant data of the mobile platform and optimizing the data of the mobile platform. And the mobile platform can be an aircraft, an automatic driving automobile and the like, and the control equipment is connected with a visual perception system of the mobile platform, wherein the visual perception system comprises an attitude sensor and a visual sensor. In the embodiment of the present invention, the control device includes a communication interface 501 and a processor 502, and the control device may further include a power module, a user interface for human-computer interaction with a user, and other functional components.
The processor 502 may be a Central Processing Unit (CPU). The processor 502 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a Programmable Logic Device (PLD), or the like. The PLD may be a field-programmable gate array (FPGA), a General Array Logic (GAL), or the like.
In an embodiment, the control device may further set a storage device 503 to cooperate with the processor 502, where the storage device 503 may include a volatile memory (volatile memory), such as a random-access memory (RAM); the storage device 503 may also include a non-volatile memory (non-volatile memory), such as a flash memory (flash memory), a solid-state drive (SSD), etc.; the storage means 503 may also comprise a combination of memories of the kind described above. The processor 502 may call program instructions stored in the storage device 503 for implementing the relevant contents of the parameter optimization method for the mobile platform in the foregoing embodiments.
In one embodiment, the communication interface 501 is used for connecting with a visual perception system, and the communication interface 501 may be connected with a mobile platform in a wired or wireless manner; the processor 502 is configured to determine a current power-on state of the mobile platform; acquiring sensing data acquired by the mobile platform in the power-on state; if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters; the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
In one embodiment, the processor 502 is further configured to detect whether the sensing data meets a preset optimization condition; and if the sensing data meet the preset optimization condition, determining that the mobile platform is in a stable state in the power-on state, and optimizing observation parameters.
In one embodiment, the powered-up state comprises a motion state, the mobile platform further comprises a position sensor, and the sensing data comprises: and acquiring the state parameters of the position sensor.
In one embodiment, the state parameters include one or more of attitude parameters, signal strength parameters, and velocity accuracy estimation indicators; the sensing data meeting the preset optimization condition comprises the following steps: the attitude parameter meets any one or more of a preset attitude condition, the signal intensity indicated by the signal intensity parameter is greater than a preset intensity threshold value, and the speed precision estimation index is less than a preset index threshold value.
In one embodiment, the pose parameters include: a speed state parameter and/or an altitude state parameter; the attitude parameter satisfying the attitude condition includes: the speed indicated by the speed state parameter is greater than a preset speed threshold value, and/or the height indicated by the height state parameter is greater than a preset height threshold value.
In one embodiment, the observed parameters include: visual speed data; the processor 502 is configured to optimize the visual speed data of the mobile platform corresponding to the motion state; and the visual speed data is obtained by calculating the sensing data collected by the attitude sensor and the visual sensor.
In one embodiment, the observed parameters include: a first angle parameter; the processor 502 is configured to optimize a first angle parameter of the mobile platform corresponding to the motion state; wherein the first angle parameter comprises: the first included angle between the north direction estimated by the vision perception system and the true north direction is obtained by calculating sensing data collected by the position sensor and the vision sensor.
In one embodiment, the sensed data includes: the positioning speed parameter of the mobile platform, the processor 502 is further configured to determine whether a difference between the positioning speed parameter and the visual speed data satisfies a preset difference condition; and optimizing the visual speed data of the mobile platform corresponding to the motion state when the preset difference condition is met.
In one embodiment, the difference between the positioning speed parameter and the visual speed data satisfying the preset difference condition comprises: the difference between the module length of the positioning speed parameter and the module length of the visual speed data is larger than a preset threshold value.
In one embodiment, the positioning speed parameter included in the sensing data is calculated according to an initial positioning speed parameter, and the initial positioning speed parameter is calculated according to the positioning data sensed by the position sensor; the processor 502 is configured to perform mapping calculation on the initial positioning speed parameter according to a mapping parameter, so as to obtain a mapping speed parameter of the position sensor in a coordinate system where the attitude sensor is located; and taking the mapping speed parameter as a positioning speed parameter.
In one embodiment, the processor 502 is configured to obtain an angular velocity parameter sensed by the attitude sensor, and obtain a coordinate system rotation transformation matrix between the attitude sensor and the position sensor; and calculating to obtain a mapping speed parameter of the position sensor in the coordinate system of the attitude sensor according to the angular speed parameter, the coordinate system rotation transformation matrix and the initial positioning speed parameter.
In one embodiment, the initial positioning speed parameter is obtained by calculating positioning data sensed by the position sensor after acquiring a preset time threshold of sensing data acquired by the attitude sensor.
In one embodiment, the power-up state comprises a hover state, and the sensory data comprises: the attitude sensor collects sensed data.
In one embodiment, the attitude sensor includes an accelerometer and a gyroscope; the sensing data meeting the preset optimization condition comprises the following steps: and the acceleration mode length calculated based on the sensing data of the accelerometer is less than a preset acceleration mode length threshold value, the angle mode length calculated based on the sensing data of the gyroscope is less than a preset angle mode length threshold value, and the speed mode length calculated based on the sensing data of the accelerometer is less than a preset speed mode length threshold value.
In one embodiment, the processor 502 is configured to invoke a preset low-pass filter to filter the sensing data collected by the attitude sensor; and processing the data obtained after filtering to obtain the sensing data of the mobile platform in the power-on state.
In one embodiment, the observed parameters include: a second angle parameter; the processor 502 is configured to optimize a second angle parameter of the mobile platform corresponding to the hovering state; wherein the second angle parameter comprises: and a second included angle between the horizontal plane and the real horizontal plane estimated by the vision perception system is calculated according to the sensing data collected by the attitude sensor.
In one embodiment, the power-up state comprises a rest state, and the sensing data comprises: a measurement of a gyroscope in the attitude sensor.
In one embodiment, the sensing data satisfying the preset optimization condition includes: the modular length of the mean value of the zero axis deviation of the gyroscope is smaller than a preset first modular length threshold value, and/or the modular length of the variance of the zero axis deviation of the gyroscope is smaller than a preset second modular length threshold value.
In one embodiment, the observed parameters include: gyroscope parameters in the attitude sensor; the optimizing the observation parameters includes: optimizing gyroscope parameters of the corresponding attitude sensor in the mobile platform in the standing state; wherein the gyroscope parameters include: and zero axis deviation of a gyroscope in the attitude sensor.
In an embodiment, the processor 502 is further configured to obtain a reference parameter corresponding to the observation parameter of the mobile platform in the power-on state; moreover, the optimization of the observation parameters by the processor 502 refers to: and optimizing difference data between the reference parameters and the observation parameters to obtain observation compensation data of the observation parameters.
In the embodiments of the present invention, reference may be made to the description of relevant contents in the foregoing embodiments for specific implementation of the processor of the control device, which is not described herein again.
The embodiment of the invention can define different power-on states for the mobile platform, and pointedly optimize observation data obtained by different sensing data based on the visual perception system under different power-on states, thereby better ensuring the accuracy and timeliness of observation parameter optimization and facilitating the subsequent safer control of the mobile platform. And from the perspective of better optimizing the observation data calculated by the VIO, the observation parameters are optimized by selecting the power-on states under different judgment conditions, so that the accuracy of optimization of the corresponding observation parameters can be ensured, and the mobile platform can be controlled more accurately.
In addition, the embodiment of the invention also provides an aircraft, and one component of the aircraft can be shown by referring to fig. 1. Fig. 1 shows a multi-rotor aircraft, which may be a four-rotor aircraft, a six-rotor aircraft, an eight-rotor aircraft, or the like, that can be flown with the aid of rotors. In other embodiments, the aircraft may also be a fixed wing aircraft or the like. The aircraft comprises: the vision sensing system 100, a controller 103 and a power assembly 104, wherein the vision sensing system 100 comprises an attitude sensor 101 and a vision sensor 102. In addition, in specific implementation, the aircraft further comprises a power supply module, and can comprise a sensor such as a compass, ultrasonic waves and the like, a deformation mechanism and the like according to needs.
The controller 103 may be a CPU. The controller 103 may further include a hardware chip. The hardware chip may be an ASIC, PLD, or the like. The PLD may be an FPGA, GAL, or the like. In one embodiment, the aircraft may further comprise a memory device cooperating with the controller 103, the memory device may comprise a volatile memory (RAM); the storage device may also include a non-volatile memory (non-volatile memory), such as a flash memory (SSD), etc.; the storage means may also comprise a combination of memories of the kind described above. The controller 103 may call program instructions stored in the storage device for implementing the relevant contents of the parameter optimization method for the mobile platform in the foregoing embodiments.
In one embodiment, the controller 103 is configured to calculate observation parameters according to the sensing data of the attitude sensor 101 and/or the vision sensor 102, and determine the current power-on state of the mobile platform; acquiring sensing data acquired by the mobile platform in the power-on state; if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters; the observation parameters are calculated according to the sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, different observation parameters are correspondingly arranged in different power-on states, and the mobile platform is used for controlling the power assembly 104 based on the corrected observation parameters so as to control the aircraft to move.
In one embodiment, the controller 103 is further configured to detect whether the sensing data meets a preset optimization condition; and if the sensing data meet the preset optimization condition, determining that the mobile platform is in a stable state in the power-on state.
In one embodiment, the powered-up state comprises a motion state, the mobile platform further comprises a position sensor, and the sensing data comprises: and acquiring the state parameters of the position sensor.
In one embodiment, the state parameters include one or more of attitude parameters, signal strength parameters, and velocity accuracy estimation indicators; the sensing data meeting the preset optimization condition comprises the following steps: the attitude parameter meets any one or more of a preset attitude condition, the signal intensity indicated by the signal intensity parameter is greater than a preset intensity threshold value, and the speed precision estimation index is less than a preset index threshold value.
In one embodiment, the pose parameters include: a speed state parameter and/or an altitude state parameter; the attitude parameter satisfying the attitude condition includes: the speed indicated by the speed state parameter is greater than a preset speed threshold value, and/or the height indicated by the height state parameter is greater than a preset height threshold value.
In one embodiment, the observed parameters include: visual speed data; the controller 103 is configured to optimize the visual speed data of the corresponding mobile platform in the motion state; wherein the vision speed data is calculated from the sensing data collected by the position sensor and vision sensor 102.
In one embodiment, the observed parameters include: a first angle parameter; the controller 103 is configured to optimize a first angle parameter of the mobile platform corresponding to the motion state; wherein the first angle parameter comprises: the first angle between the estimated north direction and the true north direction of the visual perception system 100 is calculated from the sensing data collected by the position sensor and the visual sensor 102.
In one embodiment, the sensed data includes: the controller 103 is further configured to determine whether a difference between the positioning speed parameter and the visual speed data satisfies a preset difference condition; and optimizing the visual speed data of the mobile platform corresponding to the motion state when the preset difference condition is met.
In one embodiment, the difference between the positioning speed parameter and the visual speed data satisfying the preset difference condition comprises: the difference between the module length of the positioning speed parameter and the module length of the visual speed data is larger than a preset threshold value.
In one embodiment, the positioning speed parameter included in the sensing data is calculated according to an initial positioning speed parameter, and the initial positioning speed parameter is calculated according to the positioning data sensed by the position sensor; the controller 103 is configured to perform mapping calculation on the initial positioning speed parameter according to a mapping parameter, so as to obtain a mapping speed parameter of the position sensor in a coordinate system where the attitude sensor 101 is located; and taking the mapping speed parameter as a positioning speed parameter.
In one embodiment, the controller 103 is configured to acquire an angular velocity parameter sensed by the attitude sensor 101, and acquire a coordinate system rotation transformation matrix between the attitude sensor 101 and a position sensor; and calculating to obtain a mapping speed parameter of the position sensor in the coordinate system of the attitude sensor 101 according to the angular speed parameter, the coordinate system rotation transformation matrix and the initial positioning speed parameter.
In one embodiment, the initial positioning speed parameter is obtained by calculating positioning data sensed by the position sensor after acquiring a preset time threshold of the sensing data acquired by the attitude sensor 101.
In one embodiment, the power-up state comprises a hover state, and the sensory data comprises: the attitude sensor 101 collects sensed data.
In one embodiment, the attitude sensor 101 includes an accelerometer and a gyroscope; the sensing data meeting the preset optimization condition comprises the following steps: and the acceleration mode length calculated based on the sensing data of the accelerometer is less than a preset acceleration mode length threshold value, the angle mode length calculated based on the sensing data of the gyroscope is less than a preset angle mode length threshold value, and the speed mode length calculated based on the sensing data of the accelerometer is less than a preset speed mode length threshold value.
In one embodiment, the controller 103 is configured to invoke a preset low-pass filter to filter the sensing data collected by the attitude sensor 101; and processing the data obtained after filtering to obtain the sensing data of the mobile platform in the power-on state.
In one embodiment, the observed parameters include: a second angle parameter; the controller 103 is configured to optimize a second angle parameter of the mobile platform corresponding to the hovering state; wherein the second angle parameter comprises: and a second included angle between the horizontal plane estimated by the visual perception system 100 and the real horizontal plane is calculated from the sensing data collected by the attitude sensor 101.
In one embodiment, the power-up state comprises a rest state, and the sensing data comprises: the measurement values of the gyroscopes in the attitude sensor 101.
In one embodiment, the sensing data satisfying the preset optimization condition includes: the modular length of the mean value of the zero axis deviation of the gyroscope is smaller than a preset first modular length threshold value, and/or the modular length of the variance of the zero axis deviation of the gyroscope is smaller than a preset second modular length threshold value.
In one embodiment, the observed parameters include: gyroscope parameters in the attitude sensor 101; the optimizing the observation parameters includes: optimizing the gyroscope parameters of the attitude sensor 101 in the mobile platform corresponding to the static state; wherein the gyroscope parameters include: zero axis deviation of the gyroscope in the attitude sensor 101.
In an embodiment, the controller 103 is further configured to obtain a reference parameter corresponding to the observation parameter of the mobile platform in the power-on state; the optimization of the observation parameters by the controller 103 is performed by: and optimizing difference data between the reference parameters and the observation parameters to obtain observation compensation data of the observation parameters.
In the embodiment of the present invention, for specific implementation of the controller in the aircraft, reference may be made to the description of relevant contents in the foregoing embodiments, which is not repeated herein.
The embodiment of the invention can define different power-on states for the mobile platform, and pointedly optimize observation data obtained by different sensing data based on the visual perception system under different power-on states, thereby better ensuring the accuracy and timeliness of observation parameter optimization and facilitating the subsequent safer control of the mobile platform. And from the perspective of better optimizing the observation data calculated by the VIO, the observation parameters are optimized by selecting the power-on states under different judgment conditions, so that the accuracy of optimization of the corresponding observation parameters can be ensured, and the mobile platform can be controlled more accurately.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above disclosure is intended to be illustrative of only some embodiments of the invention, and is not intended to limit the scope of the invention.

Claims (61)

1. A parameter optimization method for a mobile platform is characterized in that a visual perception system is arranged on the mobile platform and comprises an attitude sensor and a visual sensor, and the method comprises the following steps:
determining the current power-on state of the mobile platform;
acquiring sensing data acquired by the mobile platform in the power-on state;
if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters;
the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
2. The method of claim 1, further comprising:
detecting whether the sensing data meet preset optimization conditions or not;
and if the sensing data meet the preset optimization condition, determining that the mobile platform is in a stable state in the power-on state.
3. The method of claim 2, wherein the powered-up state comprises a motion state, the mobile platform further comprises a position sensor, and the sensing data comprises: and acquiring the state parameters of the position sensor.
4. The method of claim 3, wherein the state parameters include one or more of attitude parameters, signal strength parameters, and velocity accuracy estimation indicators;
the sensing data meeting the preset optimization condition comprises the following steps: the attitude parameter meets any one or more of a preset attitude condition, the signal intensity indicated by the signal intensity parameter is greater than a preset intensity threshold value, and the speed precision estimation index is less than a preset index threshold value.
5. The method of claim 4, wherein the pose parameters comprise: a speed state parameter and/or an altitude state parameter;
the attitude parameter satisfying the attitude condition includes: the speed indicated by the speed state parameter is greater than a preset speed threshold value, and/or the height indicated by the height state parameter is greater than a preset height threshold value.
6. The method of claim 3, wherein the observed parameter comprises: visual speed data;
the optimizing the observation parameters of the mobile platform corresponding to the power-on state includes: optimizing the visual speed data of the corresponding mobile platform in the motion state;
and the visual speed data is obtained by calculating the sensing data collected by the attitude sensor and the visual sensor.
7. The method of claim 3, wherein the observed parameter comprises: a first angle parameter;
the optimizing the observation parameters of the mobile platform corresponding to the power-on state includes: optimizing a first angle parameter of the corresponding mobile platform in the motion state;
wherein the first angle parameter comprises: the first included angle between the north direction estimated by the vision perception system and the true north direction is obtained by calculating sensing data collected by the position sensor and the vision sensor.
8. The method of claim 7, wherein the sensing data comprises: before optimizing the visual speed data of the mobile platform corresponding to the motion state, the positioning speed parameter of the mobile platform further includes:
judging whether the difference between the positioning speed parameter and the visual speed data meets a preset difference condition or not;
and if so, triggering and executing the optimization of the visual speed data of the corresponding mobile platform in the motion state.
9. The method of claim 8, wherein the difference between the positioning speed parameter and the vision speed data satisfying the preset difference condition comprises: the difference between the module length of the positioning speed parameter and the module length of the visual speed data is larger than a preset threshold value.
10. The method according to any one of claims 2-9, wherein the positioning speed parameter included in the sensing data is calculated from an initial positioning speed parameter calculated from the positioning data sensed by the position sensor;
wherein, calculating according to the initial positioning speed parameter to obtain a positioning speed parameter, comprising:
carrying out mapping calculation on the initial positioning speed parameter according to a mapping parameter to obtain a mapping speed parameter of the position sensor in a coordinate system where the attitude sensor is located;
and taking the mapping speed parameter as a positioning speed parameter.
11. The method of claim 10, wherein the performing a mapping calculation on the initial positioning speed parameter according to the mapping parameter to obtain a mapping speed parameter of the position sensor in a coordinate system of the attitude sensor comprises:
acquiring angular velocity parameters sensed by the attitude sensor, and acquiring a coordinate system rotation transformation matrix between the attitude sensor and the position sensor;
and calculating to obtain a mapping speed parameter of the position sensor in the coordinate system of the attitude sensor according to the angular speed parameter, the coordinate system rotation transformation matrix and the initial positioning speed parameter.
12. The method of claim 10, wherein the initial positioning speed parameter is calculated from positioning data sensed by the position sensor after a preset time threshold of acquiring sensed data acquired by the attitude sensor.
13. The method of claim 2, wherein the power-up state comprises a hover state, the sensory data comprising: data calculated based on the sensed data collected by the attitude sensor.
14. The method of claim 13, wherein the attitude sensors comprise an accelerometer and a gyroscope;
the sensing data meeting the preset optimization condition comprises the following steps: and the acceleration mode length calculated based on the sensing data of the accelerometer is less than a preset acceleration mode length threshold value, the angle mode length calculated based on the sensing data of the gyroscope is less than a preset angle mode length threshold value, and the speed mode length calculated based on the sensing data of the accelerometer is less than a preset speed mode length threshold value.
15. The method of claim 13 or 14, wherein said obtaining sensory data of said mobile platform in said powered-on state comprises:
calling a preset low-pass filter to filter the sensing data acquired by the attitude sensor;
and processing the data obtained after filtering to obtain the sensing data of the mobile platform in the power-on state.
16. The method of claim 13, wherein the observed parameter comprises: a second angle parameter;
the optimizing the observation parameters of the mobile platform corresponding to the power-on state includes: optimizing a second angle parameter of the mobile platform corresponding to the hovering state;
wherein the second angle parameter comprises: and a second included angle between the horizontal plane and the real horizontal plane estimated by the vision perception system is calculated according to the sensing data collected by the attitude sensor.
17. The method of claim 2, wherein the powered-up state comprises a rest state, the sensory data comprising: a measurement of a gyroscope in the attitude sensor.
18. The method of claim 17, wherein the sensing data satisfying the preset optimization condition comprises: the modular length of the mean value of the zero axis deviation of the gyroscope is smaller than a preset first modular length threshold value, and/or the modular length of the variance of the zero axis deviation of the gyroscope is smaller than a preset second modular length threshold value.
19. The method of claim 17 or 18, wherein the observed parameter comprises: gyroscope parameters in the attitude sensor;
the optimizing the observation parameters of the mobile platform corresponding to the power-on state includes: optimizing gyroscope parameters of the corresponding attitude sensor in the mobile platform in the standing state;
wherein the gyroscope parameters include: and zero axis deviation of a gyroscope in the attitude sensor.
20. The method of claim 1, further comprising:
acquiring reference parameters corresponding to the observation parameters of the mobile platform in the power-on state;
the optimizing the observation parameters of the mobile platform corresponding to the power-on state includes:
and optimizing difference data between the reference parameters and the observation parameters to obtain observation compensation data of the observation parameters.
21. A parameter optimization device for a mobile platform is characterized in that a visual perception system is arranged on the mobile platform and comprises an attitude sensor and a visual sensor, and the device comprises:
the determining module is used for determining the current power-on state of the mobile platform;
the acquisition module is used for acquiring the sensing data acquired by the mobile platform in the power-on state;
the optimization module is used for optimizing observation parameters of the mobile platform corresponding to the power-on state to correct the observation parameters if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data;
the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
22. A control device for parameter optimization of a mobile platform, the control device being connected to a visual perception system of the mobile platform, the visual perception system comprising an attitude sensor and a visual sensor, the control device comprising: a communication interface and a processor;
the communication interface is used for being connected with a visual perception system;
the processor is used for determining the current power-on state of the mobile platform; acquiring sensing data acquired by the mobile platform in the power-on state; if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters; the observation parameters are obtained by calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, and different observation parameters are correspondingly arranged in different power-on states.
23. The control apparatus according to claim 22,
the processor is further used for detecting whether the sensing data meet preset optimization conditions; and if the sensing data meet the preset optimization condition, determining that the mobile platform is in a stable state in the power-on state.
24. The control device of claim 23, wherein the powered-up state comprises a motion state, the mobile platform further comprises a position sensor, and the sensory data comprises: and acquiring the state parameters of the position sensor.
25. The control apparatus of claim 24, wherein the state parameters include one or more of attitude parameters, signal strength parameters, and velocity accuracy estimation indicators;
the sensing data meeting the preset optimization condition comprises the following steps: the attitude parameter meets any one or more of a preset attitude condition, the signal intensity indicated by the signal intensity parameter is greater than a preset intensity threshold value, and the speed precision estimation index is less than a preset index threshold value.
26. The control device of claim 25, wherein the attitude parameters include: a speed state parameter and/or an altitude state parameter;
the attitude parameter satisfying the attitude condition includes: the speed indicated by the speed state parameter is greater than a preset speed threshold value, and/or the height indicated by the height state parameter is greater than a preset height threshold value.
27. The control device of claim 24, wherein the observed parameter comprises: visual speed data;
the processor is used for optimizing the visual speed data of the corresponding mobile platform in the motion state;
and the visual speed data is obtained by calculating the sensing data collected by the attitude sensor and the visual sensor.
28. The control device of claim 24, wherein the observed parameter comprises: a first angle parameter;
the processor is used for optimizing a first angle parameter of the corresponding mobile platform in the motion state;
wherein the first angle parameter comprises: the first included angle between the north direction estimated by the vision perception system and the true north direction is obtained by calculating sensing data collected by the position sensor and the vision sensor.
29. The control device of claim 28, wherein the sensory data comprises: the processor is further used for judging whether the difference between the positioning speed parameter and the visual speed data meets a preset difference condition; and optimizing the visual speed data of the mobile platform corresponding to the motion state when the preset difference condition is met.
30. The control device of claim 29, wherein the difference between the positioning speed parameter and the visual speed data satisfying the preset difference condition comprises: the difference between the module length of the positioning speed parameter and the module length of the visual speed data is larger than a preset threshold value.
31. The control apparatus according to any one of claims 23 to 30, wherein a positioning speed parameter included in the sensing data is calculated from an initial positioning speed parameter calculated from positioning data sensed by the position sensor;
the processor is used for carrying out mapping calculation on the initial positioning speed parameter according to a mapping parameter to obtain a mapping speed parameter of the position sensor in a coordinate system where the attitude sensor is located; and taking the mapping speed parameter as a positioning speed parameter.
32. The control device according to claim 31, wherein the processor is configured to acquire the angular velocity parameter sensed by the attitude sensor and acquire a coordinate system rotation transformation matrix between the attitude sensor and the position sensor; and calculating to obtain a mapping speed parameter of the position sensor in the coordinate system of the attitude sensor according to the angular speed parameter, the coordinate system rotation transformation matrix and the initial positioning speed parameter.
33. The control device of claim 31, wherein the initial positioning speed parameter is calculated from positioning data sensed by the position sensor after a preset time threshold of acquisition of sensed data collected by the attitude sensor.
34. The control device of claim 23, wherein the powered-up state comprises a hover state, the sensory data comprising: the attitude sensor collects sensed data.
35. The control device of claim 34, wherein the attitude sensor includes an accelerometer and a gyroscope;
the sensing data meeting the preset optimization condition comprises the following steps: and the acceleration mode length calculated based on the sensing data of the accelerometer is less than a preset acceleration mode length threshold value, the angle mode length calculated based on the sensing data of the gyroscope is less than a preset angle mode length threshold value, and the speed mode length calculated based on the sensing data of the accelerometer is less than a preset speed mode length threshold value.
36. The control device of claim 34 or 35, wherein the processor is configured to invoke a preset low pass filter to filter the sensed data collected by the attitude sensor; and processing the data obtained after filtering to obtain the sensing data of the mobile platform in the power-on state.
37. The control device of claim 34, wherein the observed parameter comprises: a second angle parameter;
the processor is configured to optimize a second angle parameter of the mobile platform corresponding to the hovering state;
wherein the second angle parameter comprises: and a second included angle between the horizontal plane and the real horizontal plane estimated by the vision perception system is calculated according to the sensing data collected by the attitude sensor.
38. The control device of claim 22, wherein the powered-up state comprises a rest state, the sensory data comprising: a measurement of a gyroscope in the attitude sensor.
39. The control device of claim 38, wherein the sensing data satisfying the preset optimization condition comprises: the modular length of the mean value of the zero axis deviation of the gyroscope is smaller than a preset first modular length threshold value, and/or the modular length of the variance of the zero axis deviation of the gyroscope is smaller than a preset second modular length threshold value.
40. The control device of claim 38 or 39, wherein the observed parameter comprises: gyroscope parameters in the attitude sensor;
the optimizing the observation parameters includes: optimizing gyroscope parameters of the corresponding attitude sensor in the mobile platform in the standing state;
wherein the gyroscope parameters include: and zero axis deviation of a gyroscope in the attitude sensor.
41. The control device according to claim 22, wherein the processor is further configured to obtain a reference parameter corresponding to the observation parameter of the mobile platform in the power-on state; and, the processor optimizing the observation parameters means: and optimizing difference data between the reference parameters and the observation parameters to obtain observation compensation data of the observation parameters.
42. An aircraft, characterized in that it comprises: the vision perception system comprises an attitude sensor and a vision sensor;
the controller is used for calculating observation parameters according to the sensing data of the attitude sensor and/or the vision sensor and determining the current power-on state of the mobile platform; acquiring sensing data acquired by the mobile platform in the power-on state; if the mobile platform is determined to be in a stable state in the power-on state according to the sensing data, optimizing observation parameters of the mobile platform corresponding to the power-on state so as to correct the observation parameters; the observation parameters are obtained through calculation according to sensing data of the attitude sensor and/or the vision sensor, the mobile platform comprises a plurality of power-on states, different observation parameters are correspondingly arranged in different power-on states, and the mobile platform is used for controlling the power assembly based on the corrected observation parameters so as to control the aircraft to move.
43. The aircraft of claim 42,
the controller is further used for detecting whether the sensing data meet preset optimization conditions; and if the sensing data meet the preset optimization condition, determining that the mobile platform is in a stable state in the power-on state.
44. The aircraft of claim 43, wherein said powered-on state comprises a motion state, said mobile platform further comprises a position sensor, and said sensory data comprises: and acquiring the state parameters of the position sensor.
45. The aircraft of claim 44, wherein the state parameters include one or more of attitude parameters, signal strength parameters, and velocity accuracy estimation indicators;
the sensing data meeting the preset optimization condition comprises the following steps: the attitude parameter meets any one or more of a preset attitude condition, the signal intensity indicated by the signal intensity parameter is greater than a preset intensity threshold value, and the speed precision estimation index is less than a preset index threshold value.
46. The aircraft of claim 45, wherein the attitude parameters comprise: a speed state parameter and/or an altitude state parameter;
the attitude parameter satisfying the attitude condition includes: the speed indicated by the speed state parameter is greater than a preset speed threshold value, and/or the height indicated by the height state parameter is greater than a preset height threshold value.
47. The aircraft of claim 44, wherein the observed parameter comprises: visual speed data;
the controller is used for optimizing the visual speed data of the corresponding mobile platform in the motion state;
and the visual speed data is obtained by calculating the sensing data collected by the attitude sensor and the visual sensor.
48. The aircraft of claim 44, wherein the observed parameter comprises: a first angle parameter;
the controller is used for optimizing a first angle parameter of the corresponding mobile platform in the motion state;
wherein the first angle parameter comprises: the first included angle between the north direction estimated by the vision perception system and the true north direction is obtained by calculating sensing data collected by the position sensor and the vision sensor.
49. The aircraft of claim 48, wherein said sensory data comprises: the controller is also used for judging whether the difference between the positioning speed parameter and the visual speed data meets a preset difference condition; and optimizing the visual speed data of the mobile platform corresponding to the motion state when the preset difference condition is met.
50. The aircraft of claim 49, wherein the difference between the positioning speed parameter and the vision speed data satisfying the preset difference condition comprises: the difference between the module length of the positioning speed parameter and the module length of the visual speed data is larger than a preset threshold value.
51. The aircraft of any of claims 43-50, wherein a positioning speed parameter included in said sensory data is calculated from an initial positioning speed parameter calculated from positioning data sensed by said position sensor;
the controller is used for carrying out mapping calculation on the initial positioning speed parameter according to a mapping parameter to obtain a mapping speed parameter of the position sensor in a coordinate system where the attitude sensor is located; and taking the mapping speed parameter as a positioning speed parameter.
52. The aircraft of claim 51, wherein the controller is configured to obtain angular velocity parameters sensed by the attitude sensor and obtain a coordinate system rotation transformation matrix between the attitude sensor and the position sensor; and calculating to obtain a mapping speed parameter of the position sensor in the coordinate system of the attitude sensor according to the angular speed parameter, the coordinate system rotation transformation matrix and the initial positioning speed parameter.
53. The aircraft of claim 51, wherein the initial positioning speed parameter is calculated from positioning data sensed by the position sensor after a preset time threshold of acquiring sensed data acquired by the attitude sensor.
54. The aircraft of claim 53, wherein the powered-up state comprises a hover state, the sensory data comprising: the attitude sensor collects sensed data.
55. The aircraft of claim 54, wherein the attitude sensor comprises an accelerometer and a gyroscope;
the sensing data meeting the preset optimization condition comprises the following steps: and the acceleration mode length calculated based on the sensing data of the accelerometer is less than a preset acceleration mode length threshold value, the angle mode length calculated based on the sensing data of the gyroscope is less than a preset angle mode length threshold value, and the speed mode length calculated based on the sensing data of the accelerometer is less than a preset speed mode length threshold value.
56. The aircraft of claim 54 or 55, wherein the controller is configured to invoke a preset low pass filter to filter the sensed data collected by the attitude sensor; and processing the data obtained after filtering to obtain the sensing data of the mobile platform in the power-on state.
57. The aircraft of claim 54, wherein said observed parameters comprise: a second angle parameter;
the controller is used for optimizing a second angle parameter of the mobile platform corresponding to the hovering state;
wherein the second angle parameter comprises: and a second included angle between the horizontal plane and the real horizontal plane estimated by the vision perception system is calculated according to the sensing data collected by the attitude sensor.
58. The aircraft of claim 42, wherein said powered-up state comprises a rest state, and said sensory data comprises: a measurement of a gyroscope in the attitude sensor.
59. The aircraft of claim 58, wherein said sensory data meeting said preset optimization condition comprises: the modular length of the mean value of the zero axis deviation of the gyroscope is smaller than a preset first modular length threshold value, and/or the modular length of the variance of the zero axis deviation of the gyroscope is smaller than a preset second modular length threshold value.
60. The aircraft of claim 58 or 59, wherein said observed parameters comprise: gyroscope parameters in the attitude sensor;
the optimizing the observation parameters includes: optimizing gyroscope parameters of the corresponding attitude sensor in the mobile platform in the standing state;
wherein the gyroscope parameters include: and zero axis deviation of a gyroscope in the attitude sensor.
61. The aircraft of claim 42, wherein the controller is further configured to obtain a reference parameter corresponding to the observed parameter of the mobile platform in the powered-up state; and, the controller optimizing the observation parameters means: and optimizing difference data between the reference parameters and the observation parameters to obtain observation compensation data of the observation parameters.
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