1173 results about "Quaternion" patented technology

An inertial sensor based surgical navigation system for knee replacement surgery is disclosed. Inertial sensors composed of six-degree-of-freedom inertial chips, whose measurements are processed through a series of integration, quaternion, and kalman filter algorithms, are used to track the position and orientation of bones and surgical instruments. The system registers anatomically significant geometry, calculates joint centers and the mechanical axis of the knee, develops a visualization of the lower extremity that moves in real time, assists in the intra-operative planning of surgical cuts, determines the optimal cutting planes for cut guides and the optimal prosthesis position and orientation, and finally navigates the cut guides and the prosthesis to their optimal positions and orientations using a graphical user interface.

The invention provides an unscented Kalman filter-based method for tracking an inertial pose according to acceleration compensation, which is used for an inertial measurement unit integrating a three-axis micro-gyroscope, a three-axis micro-accelerometer and a three-axis magnetoresistive sensor, and realizes pose tracking estimation on a device carrier by using rotary angular velocity vectors, acceleration vectors and magnetic field sensor vectors which are detected by the device by means of filter technology. The method comprises the following steps: 1) treating the acceleration vectors as combination of the acceleration vectors and gravity acceleration vectors of the device carrier self, and constructing observation equations respectively for amplitude and normalized direction vectors of the acceleration vectors and the gravity acceleration vectors; 2) describing quaternion, accumulated error vectors of the gyroscope and the acceleration vectors of the device carrier self by using the pose to construct a system state vector; and 3) realizing a filter estimating process of the system by using the unscented Kalman filter technology because of nonlinearity of the observation equations. Compared with the conventional method ignoring the acceleration of the carrier self, the method not only can provide a more accurate estimation result, but also widens the application range of the system.

The invention relates to a systematic calibration method of a welding robot guided by a line structured light vision sensor, which comprises the following steps: firstly, controlling a mechanical arm to change pose, obtaining a round target image through a camera, accomplishing the matching of the round target image and a world coordinate, and then obtaining an internal parameter matrix and an external parameter matrix RT of the camera; secondly, solving a line equation of a line laser bar by Hough transformation, and using the external parameter matrix RT obtained in the first step to obtain a plane equation of the plane of the line laser bar under a coordinate system of the camera; thirdly, calculating to obtain a transformation matrix of a tail end coordinate system of the mechanical arm and a base coordinate system of the mechanical arm by utilizing a quaternion method; and fourthly, calculating a coordinate value of a tail end point of a welding workpiece under the coordinate of the mechanical arm, and then calculating an offset value of the workpiece in the pose combined with the pose of the mechanical arm. The systematic calibration method of the welding robot guided by the line structured light vision sensor is flexible, simple and fast, and is high in precision and generality, good in stability and timeliness and small in calculation amount.

The invention discloses a human body attitude calculation method based on quaternion and Kalman filtering. The method comprises determining a vector coordinate system and a navigation coordinate system, determining an attitude matrix, respectively acquiring accelerated speed, angular velocity and magnetic induction intensity signals through an accelerometer, a gyroscope and a magnetometer, carrying out initial alignment on a human body attitude detection system, calculating initial attitude angles such as a pitching angle, a rolling angle and a heading angle, transforming the initial attitude angles into initial quaternion, carrying out system modeling according to a quaternion differential equation, inputting the initial quaternion as a measured value, carrying out data fusion on the attitude data through a Kalman filtering algorithm, outputting an estimated value which is updated quaternion, carrying out normalization processing on the updated quaternion to obtain final posture information, updating the attitude matrix and acquiring updated attitude angles. The human body attitude estimation method effectively improves the accuracy of human posture detection, has a fast response speed, has good stability and instantaneity and has a broad application prospect.

Higher Order Sliding Mode (HOSM) control techniques are applied to the Guidance Control (G&C) of interceptor missile in which velocity may be steered by combination of main thrust, aerodynamic lift and lateral on-off divert thrusters, and attitude may be steered by continuous or on-off actuators. Methods include the pointing of the seeker, its associated estimation processes, a guidance law that uses concurrent divert mechanisms, and an attitude autopilot. The insensitivity of the controller to matched disturbances allows the concurrent usage of the divert mechanisms without adverse effect on the accuracy. The controller also allows the de-coupling of the control of roll, pitch and yaw channels, and usage quaternions to represent body attitude and it provides control perfect robustness. While it conceivable to design separately the components of the G&C method, it is widely accepted that designing them in an integrated fashion usually produces a better result.

Novel techniques for estimating compass and gyroscope biases for handheld devices are disclosed. The handheld devices can include wireless phones, navigational devices and video gaming systems. The compass bias can be determined by causing a small movement of the handheld device and comparing the data obtained from the compass with the data obtained from the gyroscope. The gyroscope bias can be determined by obtaining a quaternion based angular velocity term of the handheld device when the accelerometer and compass data are reliable, and then comparing the angular velocity term to with the gyro data estimate the gyro bias. When the compass and / or the accelerometer data are unreliable, a previously determined quaternion angular velocity term is used, which was determined when the compass and the accelerometer were providing reliable data. The gyroscope bias can also be determined by measuring gyroscope biases at various temperatures in a non-factory setting, and storing that data in a memory, and using the data to estimate gyro biases when the accelerometer and / or the compass data are unreliable.

The invention discloses a human body movement reconstruction and analysis system and method based on inertial sensing units. The system comprises a pose information acquisition system, a WIFI wireless router and a central computer. The pose information acquisition system is composed of the inertial sensing units. The inertial sensing units are installed on multiple parts of a human body respectively to collect accelerated velocities, angular velocities and magnetic information of all the parts in real time and fuse the accelerated velocities, the angular velocities and the magnetic information to obtain pose information such as pose angles, quaternions and Euler angles; next, the collected information and the fused information are sent to the central computer through the WIFI wireless router in a WIFI mode; the central computer fuses pose information data of all the inertial sensing units to complete human body movement reconstruction and extracts movement parameters such as positions, velocities, angles, the accelerated velocities and angular accelerated velocities, and the movement parameters are used for biomechanical analysis and kinematic analysis of human body movement. By means of the human body movement reconstruction and analysis system and method, influences on the movement of a subject are reduced to the maximum extent, the requirements for capturing the movement of the whole body of the subject and the special movement of a specific part of the subject are both met, and the system and method are suitable for various application occasions.

The invention discloses a high-precision three-dimensional posture inertia measurement system and method based on MEMS (Micro Electro Mechanical Systems), which relate to a high-precision three-dimensional posture inertia measurement method. The system and the method disclosed by the invention aim for solving the problems that the existing three-dimensional posture inertia measurement equipment is low in cost and low in precision due to adoption of a sensor. A three-axis gyroscope sensor is used for sending measured angular speed data to an ARM (Advanced RISC Machines) processor; a three-axis accelerometer sensor is used for sending measured acceleration data to the ARM processor; a three-axis magnetometer sensor is used for sending measured magnetic strength data to the ARM processor; a temperature sensor is used for measuring and sending obtained temperature excursion data of the three-axis gyroscope sensor to the ARM processor; the ARM processor is used for processing the received data by means of front low-pass digital filtration, front-end data processing and expansion Kalman filtration respectively so as to obtain Euler angle three-dimensional posture inertia data or quaternion three-dimensional posture inertia data. The system and the method disclosed by the invention can be applied to the field of navigation control.

The invention relates to a system capable of realizing immersive virtual reality across mobile platforms. A DirectX3D rendering technology is adopted to perform distortion correction and distortion scale on images rendered by virtual three-dimensional scenes via a Pixel Shader, the images are segmented and drawn on left-eye and right-eye screens of HMD equipment, and a refresh frequency of more than 60 frames per second is kept; position information and facing information of the HMD equipment are acquired from a sensor and used for head tracking, and coordinate and rotating quaternion information are fed back to an application program via a message interface; and interaction between a client end and a server end is realized by adopting a wireless communication technology. The system provided by the invention has the advantages that one product only needs to be developed for once, reality is enhanced, virtual objects not existing in the real environment are generated via a computer graphic technology and a visualization technology, the virtual objects are accurately 'placed' in the real environment via the sensing technology and are integrally mixed with the real environment by the aid of displaying equipment.

The invention discloses a human body posture recognition method based on self-adaptive extension Kalman filtering, belonging to the field of body-area networks. The method comprises a model design step and a parameter design step. In the model design step, the angular speed and accelerated speed of the motion of a human body and the peripheral magnetic field intensity are collected by virtue of an inertial sensor through the characteristic that the motion angle of limbs of the human body can be reflected by a quaternion, and posture resolving is carried out based on a self-adaptive extension Kalman filtering method so as to obtain a posture quaternion. In the parameter design step, by utilizing a theoretical analysis and experiment method, a process noise covariance matrix is determined, and the value of a noise covariance matrix, a state initial value and an initial value of a state covariance matrix are measured, so that the continuous iteration of the self-adaptive extension Kalman filtering method can be realized, and the motion posture of the human body is continuously recognized in real time. The human body posture recognition method can be used as a human body posture recognition method in the fields of physical training, medical care, game design and the like.

The invention relates to a system capable of realizing immersive virtual reality over mobile platforms. A DirectX3D rendering technique is adopted to perform distortion correction and distortion zooming on images rendered by virtual three-dimensional scenes via a Pixel Shader , the images are segmented and drawn on a left and right binoculus screen of HMD (helmet-mounted display) equipment, and an updating frequency of more than 60 frames per second is kept; position information and facing information of the HMD equipment are acquired from a sensor and used for head tracking, and coordinate and rotating quaternion information are fed back to an application program via a message port; interaction between a client end and a server end is realized via a wireless communication technology. The system has the advantages that one product only needs to be developed for once, reality is enhanced, virtual objects not existing in the real environment are generated via a computer graphic technology and a visualization technology, the virtual objects are accurately 'placed' in the real environment via the sensing technology and are integrally mixed with the real environment by the aid of displaying equipment.

A method and system senses the attitude of an accelerating object by measuring acceleration with accelerometers in three orthogonal axes and measuring angular rate with angular rate sensors disposed about each such axis to compute attitude of the object accurately relative to a vertical axis. A processor updates a quaternion representation of attitude based upon the angular rate of the object, and a corrective rate signal is determined from level frame acceleration as a reference for a Kalman filter in calculating the attitude of the object. When velocity or airspeed is available from an external source, an aiding algorithm is employed to provide accurate attitude representations throughout all flight regimes.

This invention provides a system and method for determining position of a viewed object in three dimensions by employing 2D machine vision processes on each of a plurality of planar faces of the object, and thereby refining the location of the object. First a rough pose estimate of the object is derived. This rough pose estimate can be based upon predetermined pose data, or can be derived by acquiring a plurality of planar face poses of the object (using, for example multiple cameras) and correlating the corners of the trained image pattern, which have known coordinates relative to the origin, to the acquired patterns. Once the rough pose is achieved, this is refined by defining the pose as a quaternion (a, b, c and d) for rotation and a three variables (x, y, z) for translation and employing an iterative weighted, least squares error calculation to minimize the error between the edgelets of trained model image and the acquired runtime edgelets. The overall, refined / optimized pose estimate incorporates data from each of the cameras' acquired images. Thereby, the estimate minimizes the total error between the edgelets of each camera's / view's trained model image and the associated camera's / view's acquired runtime edgelets. A final transformation of trained features relative to the runtime features is derived from the iterative error computation.

The invention discloses flywheel based attitude maneuvering control device and method for successive approaching of a satellite rounding an instantaneous Euler shaft and relates to control device and method for satellite attitude adjustment. The invention is provided for solving the problems of great fuel consumption, short service life of a satellite, complex configuration of an air injecting control system and difficult reduction of size and weight of the satellite existing in the realization of satellite wide-angle attitude maneuvering by adopting air injecting control. The method comprises the following steps of: setting a parameter of the control device according to the system requirement of the control device and obtaining attitude deviation angular velocity according to a motion equation; and expressing a relationship of the instantaneous Euler shaft and a deviation angle of the current attitude and a target attitude of the satellite by an attitude error quaternion to obtain a control signal, calculating to obtain a flywheel control input moment vector calculated by a satellite controller, to be used as a data control command as a basis for generating moment by a back action flywheel. The invention does not consume other resources on the satellite or consume fuel, prolongs the service life of the satellite and can be widely suitable for various satellites needing attitude maneuvering.

A non-linear alignment method of a strapdown inertial navigation system comprises the following steps of: acquiring data of an accelerometer and a fiber gyroscope of the fiber strapdown inertial navigation system and carrying out denoise processing, realizing coarse alignment and fine alignment processes by the utilization of an analysis method and a compass method, establishing a quaternion-based strapdown inertial navigation system non-linear error model under the condition that attitude angle and azimuth angle are both large misalignment angles, establishing an observation model with speed as observed quantity, carrying out iterative and filter estimation by the use of an improved UKF algorithm on the basis of the model so as to obtain the misaligned angle of the platform, continuously carrying out closed-loop feedback and correcting attitude matrix of the strapdown inertia system in the previous period, so as to accurately complete the initial alignment process. The method can be used to guarantee safety and confidentiality of the initial alignment without the utilization of other sensor information. By the introduction of the quaternion error based non-linear system error model, linearization is not required to guarantee the precision of the model. Computational complexity is reduced, and filtering is carried out on the established non-linear system so as to complete fine alignment.

The invention relates to a spacecraft fault tolerance attitude cooperation tracking control method based on a normalized neural network, and belongs to the technical field of spacecraft formation flight. According to the method, an attitude motion model of a single spacecraft is built, errors are defined, a control law is designed for the model, a sliding mode function is designed, the derivative of the sliding mode function is solved, an error model is obtained, a control law based on an input normalized neural network is designed, and the states of the spacecrafts are cooperative and consistent; each spacecraft calculates the required control torque according to attitude information of itself and the adjacent spacecraft, the calculated control torque is acted on the corresponding spacecraft via an execution mechanism of each spacecraft, the angular velocity is solved via an obtained attitude dynamic equation, a unit quaternion attitude tracks an expected attitude via the attitude dynamic equation, and consistent attitude of the spacecraft formation is finally realized. According to the method, estimation errors of non-linear function approximation are reduced, the calculating time is reduced, and the convergence rate and the control precision of the system are increased.

The invention discloses a planning method for the smooth trajectory of a robot in Cartesian space. The planning method comprises the following process: planning the positions and postures of single-section trajectories, such as a spatial line and an arc; carrying out planning on the smooth transition of a path; controlling the size of the transition region of the path by adopting a transition grade; fitting the path in the transition region by adopting a parabola, and fitting the postures by adopting a quaternion algorithm; and adopting a cycloidal acceleration and deceleration planning method containing acceleration and an acceleration restraint to carry out planning on the spatial trajectory of the path so as to obtain the smooth spatial position and posture trajectory of a robot. The method can effectively solve robot trajectory problems, such as pause, non-smoothness, dithering, path deviation and speed excess and improve the running stability of the robot. The planning method for the smooth trajectory, related to the invention, has certain flexibility, and not only can plan the positions and the postures in the Cartesian space but also can adapt to various robot structures, containing common 6-degree-of-freedom vertical joint mechanical arms, low-degree-of-freedom robots and redundant robots.

This invention provides a system and method for determining position of a viewed object in three dimensions by employing 2D machine vision processes on each of a plurality of planar faces of the object, and thereby refining the location of the object. First a rough pose estimate of the object is derived. This rough pose estimate can be based upon predetermined pose data, or can be derived by acquiring a plurality of planar face poses of the object (using, for example multiple cameras) and correlating the corners of the trained image pattern, which have known coordinates relative to the origin, to the acquired patterns. Once the rough pose is achieved, this is refined by defining the pose as a quaternion (a, b, c and d) for rotation and a three variables (x, y, z) for translation and employing an iterative weighted, least squares error calculation to minimize the error between the edgelets of trained model image and the acquired runtime edgelets. The overall, refined / optimized pose estimate incorporates data from each of the cameras' acquired images. Thereby, the estimate minimizes the total error between the edgelets of each camera's / view's trained model image and the associated camera's / view's acquired runtime edgelets. A final transformation of trained features relative to the runtime features is derived from the iterative error computation.

The invention discloses a decoupling control method for relative orbits and attitudes of formation satellites, relates to the technical field of the control of the orbits and attitudes of a spacecraft formation, and solves the problems of large satellite calculation amount and low orbit solving efficiency caused by high control dimension of the formation satellites due to serious coupling of the relative orbits and the attitudes of the formation satellites. The method gives two decoupling conditions at first, so that the control of the relative orbits and the attitudes can be designed independently; a thrust vector mobility decoupling constraint condition is introduced to the initialization control of the relative orbits according to satellite attitude mobility constraints indirectly; and during the optimal thrust vector attitude tracking, the possible orientation in space, which meets solar avoidance constraints, of a star sensor optical axis (1) is sought by using a geometric method, and the optimal attitude quaternion and attitude angular velocity are calculated finally by using a double-vector attitude determination algorithm. The method provides important reference value for the control of the orbits and the attitudes of the spacecraft formation.

The invention discloses a malicious encrypted flow feature analysis method, which belongs to the crossing field of network security and machine learning, and is used for analyzing the HTTPS flow and detecting the malicious threats in the HTTPS flow. The method comprises the following steps of modeling the flow data by taking a connection quaternion as a data structure, analyzing the encrypted flowfrom four levels by taking the connection quaternion as a unit, and extracting the flow-level features, TLS handshake features, X.509 certificate features and context features of the connection quaternion to obtain an initial feature set, adopting a recursive feature elimination method based on a decision tree to screen the initial feature set to obtain an optimal feature set used for the machinelearning model training to thereby obtain a malicious encrypted flow detection model.

A method and system senses the attitude of an accelerating object by measuring acceleration with accelerometers in three orthogonal axes and measuring angular rate with angular rate sensors disposed about each such axis to compute attitude of the object accurately relative to a vertical axis. A processor updates a quaternion representation of attitude based upon the angular rate of the object, and a corrective rate signal is determined from level frame acceleration as a reference for a Kalman filter in calculating the attitude of the object.

The invention provides a correction method for on-track aberration of a star sensor. The method comprises the following steps of: calculating the annual aberration constant of a satellite according to a formula; measuring the linear velocity of the satellite in an inertial coordinate system by using a satellite borne device; calculating the altitude of the satellite in the inertial coordinate system; calculating the optical axis direction of the star sensor in the inertial coordinate system; calculating the linear velocity vertical to the optical axis direction of the star sensor in the inertial coordinate system; calculating the diurnal aberration constant vertical to the optical axis direction of the star sensor; calculating the included angle between a fixed star direction and the optical axis direction in the view filed of the star sensor; calculating aberration synthesis caused by all factors; and calculating an altitude quaternion. In the invention, a mathematical model for eliminating the diurnal aberration and annual aberration of the star sensor and the peculiar motion aberration of the sun is induced; after the model is used to eliminate aberration, altitude information with high accuracy can be further provided for an aircraft, the angular speed of a non-gyro aircraft can be calculated by using altitude, and the accuracy of angular speed calculation can be further improved.

The invention relates to the technical field of unmanned aerial vehicles and discloses a pan-tilt attitude detection method and a pan-tilt attitude detection device. The method comprises the following steps: acquiring data of a pan-tilt inertia measurement unit, wherein the data of the inertia measurement unit includes angular velocity data of a gyro and accelerometer data; performing quaternion integral operation on the data of the inertia measurement unit; changing the data of the inertia measurement unit from quaternion expression into rotation matrix expression; and changing the data of the inertia measurement unit from the rotation matrix expression into eulerian angle expression, wherein the step of performing the quaternion integral operation on the data of the inertia measurement unit comprises the following sub-steps: by taking the rotation matrix expression as feedback, performing feedback correction on the quaternion expression, acquiring pan-tilt attitude data through an attitude heading system, performing pan-tilt attitude expression by adopting different algorithms and compensating and correcting the pan-tilt attitude. Therefore, the accuracy of the pan-tilt attitude detection is improved.

The invention discloses a real-time navigation system and a real-time navigation method for an underwater structure detection robot. The navigation system comprises a magnetic compass, a gyroscope, an accelerometer, a depth meter and a navigation microprocessor, wherein the magnetic compass, the gyroscope, the accelerometer and the depth meter are used for respectively collecting magnetic field intensity, an angular speed, a linear speed and submerged depth data and transmitting the magnetic field intensity, the angular speed, the linear speed and the submerged depth data to the navigation microprocessor; the navigation microprocessor is used for calculating attitude and position of the underwater robot according to the collected data. The navigation method comprises an attitude algorithm, a speed algorithm and a depth algorithm; according to the attitude algorithm, a complementary filtering method, a quaternion gradient descent method and a Kalman algorithm are combined for obtaining an attitude matrix and an attitude angle; the speed algorithm is used for calculating the speed and the position of the robot by using a three-order upwind scheme with rotary compensation; the depth algorithm is used for processing the data of the depth meter by using a moving average filter algorithm so as to obtain the submerged depth. By virtue of the real-time navigation system for the underwater structure detection robot and the method thereof, the navigation cost is reduced and a relatively good navigation precision is achieved.

The invention discloses a method for determining the attitude of a flight carrier, which belongs to the field of attitude measurement. The main steps include: establish the coordinate system and attitude matrix of the flight carrier; collect sensor signals; use the gyro measurements to carry out strapdown attitude calculations to obtain the attitude quaternions and attitude angles of the flight carrier; use the magnetometer measurements to calculate the flight Carrier heading angle; use speed information to compensate acceleration measurement value, solve pitch angle and roll angle; solve attitude quaternion determined by magnetometer and accelerometer information; design Kalman filter, estimate state vector; correct attitude four arity and extract attitude angle. This method combines gyroscopes, accelerometers, magnetometers, and speed sensors to meet the requirements of real-time attitude control of the flight carrier; introduces gyroscope drift into the system state vector, estimates and corrects it in real time, and uses the measured value of the magnetometer to directly Calculate the heading angle, avoid the calculation of the geomagnetic field vector in the geographic coordinate system, and improve the accuracy of attitude determination.

The invention belongs to the field of computer vision and particularly relates to a quaternion time-space convolutional neural network-based human body behavior identification method. The method comprises the following specific implementation steps of (1) inputting a to-be-identified action video set; (2) performing image preprocessing, and extracting a key region image of a human body motion; (3) constructing a quaternion time-space convolutional neural network; (4) training the network by adopting a BP algorithm, and outputting a training result; and (5) inputting a video test set, and outputting a test result. According to the method, the region image of the human body motion is extracted by utilizing a codebook model, so that the human body motion can be detected under the condition of a complex background; and the quaternion time-space convolutional neural network directly takes a color image as an input, so that the problem of image feature deficiency in a process of converting the color image into a grayscale image or performing processing by channels in a conventional convolutional neural network is solved, the performance of network feature extraction is improved, and the human body behavior identification is more accurate.

The invention provides a biquaternion communication-in-motion antenna control method based on MEMS inertial navigation. An antenna control quaternion is introduced on the basis of a navigation posture quaternion. In each interrupt cycle of a navigation computer, a rotation vector of a carrier relative to an ideal platform coordinate system is measured through a gyroscope to update the two quaternions. In each filtering cycle, errors of the navigation posture quaternion are modified through Kalman filtering. According to the relation between postures determined through the two posture quaternions, an antenna control instruction angular speed is determined. Finally, a servo system is controlled to rotate through an antenna servo control angle obtained through conversion by means of antenna control quaternion postures. According to a biquaternion communication-in-motion antenna control system based on MEMS inertial navigation, the control method serves as a control flow, and precise control of communication-in-motion antenna orientation can be achieved. By means of the method and the system, impact caused by unstable of the navigation posture quaternion to a communication-in-motion antenna servo system can be effectively avoided in the Kalman filtering transient process, and alignment time of a communication-in-motion system is effectively shortened.

A spacecraft attitude fixing method of DD2 (Divided Difierence 2) filter and a counting method based on Euler-q (Euler-quaternion) are provided, which relates to a state estimation and attitude determination method based on vector observation. The invention is characterized in that: according to the reference ephemeris and the reference vector and the observation vector observed by a star sensor, the spacecraft attitude quaternion can be gotten through Euler-q counting method; through DD2 filter, on one hand, feedback compensation the attitude matrix obtained through resolving by gyro; on the other hand, revise the palstance output of three-axle gyro and conduct compensation to the constant drift of gyroscope. As for that, the current spacecraft attitude information when getting high precision can be achieved, the constant drift of gyroscope can be scaled on line. The invention is an unattended attitude determining method, which is characterized in high precision and good timeliness, being convenient and feasible, and can be used in the attitude fixing system of various spacecrafts.