64 results about "Motion computation" patented technology

The invention discloses a feeding motion calculation method for a double-output-shaft five-axis numerical control tool grinding machine, and the method specifically comprises the steps: building a unified coordinate system according to the mechanism characteristics and solving demands of the grinding machine, and the unified coordinate system comprises a machine tool coordinate system, a machining coordinate system, a workpiece coordinate system and a grinding wheel coordinate system; grinding machine structure parameters are set and comprise the offset of the original point of a machining coordinate system relative to the C axis, grinding machine structure offset examples of the offset of the original point of the machining coordinate system relative to the B axis, the grinding wheel installation distance and the grinding wheel installation direction; a universal grinding machine feeding kinematics equation is established by considering the inward and outward mounting conditions of main shafts at the left end and the right end of the grinding wheel; and solving based on grinding wheel installation transformation and grinding machine stroke constraint. According to the method for solving the partitioned selective solution based on the actual travel limit of the machine tool, the solution is more universal and practical, the actual travel limit of the machine tool is met, and the method has good adaptability.

The invention discloses a visual positioning method for satellite on-orbit fuel filling docking service, which comprises two stages of off-line training and on-line positioning, and comprises the following steps: firstly, acquiring image and pose information by using a camera, establishing a pre-matching database, carrying out feature matching, calculating the pose of the camera through structural motion, and generating sparse point cloud; carrying out dense reconstruction on the scene by adopting three-dimensional Gaussian sputtering, and generating a three-dimensional Gaussian sputtering model through training; after a camera at the tail end of the refueling satellite mechanical arm captures an original image in real time, a reference image most similar to the current image is recognized based on the pre-matching database, a corresponding initial pose is obtained, and the image is rendered to serve as a starting point of subsequent iterative optimization; and meanwhile, color migration correction is performed on the captured image by taking the rendered image as a reference, and inter-domain differences are eliminated to generate a target image in an optimization stage. According to the invention, a picture captured at an unknown view angle can be well positioned. And the calculation efficiency is improved while the accuracy is ensured as much as possible.

The invention discloses an automatic video editing method and device based on text and shot similarity and a terminal, and belongs to the technical field of artificial intelligence. The method comprises the following steps: determining the end time of a mixed video based on a music interval identification result of specified music; selecting a lens of which the main body label is scenery as a lens head lens; performing similarity analysis with other lenses based on a subject recognition result, a behavior recognition result and a motion calculation result, calculating visual similarity between the lenses based on a deep learning model, recognizing repeated or redundant pictures, and selecting a high-energy lens as an in-chip high-combustion lens; retrieving and intercepting a corresponding lens as a tail lens based on a corresponding segment of the selected end word; and carrying out audio and video mixed cutting and assembling on the specified music, the head lens, the in-chip high-combustion lens and the tail lens. According to the invention, by fusing multi-modal feature analysis and intelligent editing logic generation, efficient and high-quality video automatic production is realized.

To solve the problem in which human sensing detection using a radio wave method of an IQ signal does not produce results consistent with a radio wave propagation theory in enclosed spaces, such as unit bathrooms, where metal is embedded in walls.SOLUTION: A human sensing detection method using radio waves utilizing radio wave absorption characteristics of a human body includes measuring the total amount of radio waves when no one is present in an enclosed space in which there is provided a single or multiple radio wave sensors including at least a reference radio wave oscillation unit, a radio wave transmitting unit, a transmitting antenna unit, a receiving antenna unit, a radio wave receiving unit, an IQ signal processing unit, a distance calculation unit, a movement calculation unit, a memory unit for each reflected wave component, and a power supply unit, storing a value for each reflected wave component, extracting a component whose value, which is stored when no one is present, decreases each time someone enters the space and moves around, and thereby detecting a position and movement of a person. The human sensing detection method makes it easy to detect the location and movement of the person.SELECTED DRAWING: Figure 1

The embodiment of the invention provides a method and device for judging upper limb compensatory movement, computer equipment and a medium, and relates to the technical field of artificial intelligence, and the method comprises the following steps: collecting image data of a target object in a movement process; converting the image data into joint point space coordinate data; generating an upper limb skeleton coordinate sequence according to the node space coordinate data; calculating to obtain a shoulder inclination angle theta and the relative displacement of the horizontal axes of the shoulders, judging whether shoulder lifting type compensation movement exists or not, calculating to obtain a spine inclination angle alpha, and judging whether trunk bending type compensation movement exists or not; if the shoulder raising type compensation exercise and / or the trunk bending type compensation exercise exist, the upper limb compensation exercise exists, and prompt information for prompting the target object to change the exercise mode is output. According to the scheme, video shooting is carried out on the training process of the target object, whether the target object has upper limb compensatory motion or not is judged, the target object is reminded, and therefore the upper limb compensatory motion is effectively restrained.

A continuum robot control device, configured to control operations of a continuum robot having a bendable portion that is bent by driving at least part of a plurality of wires, includes a kinematics computing unit that computes a driving amount lk1b of the at least part of the plurality of wires, based on a target bending angle that is a target value for a bending angle of the bendable portion, a compensation amount computing unit that computes a compensation amount for compensation of the driving amount lk1b, based on the target bending angle, and a displacement of one of the plurality of wires at the target bending angle, and an adding unit and position control unit that set a driving control amount of performing driving control of the at least part of the plurality of wires, based on the driving amount and the compensation amount obtained by computation.

The application discloses a kind of experimental measurement methods of non-spherical particle energy recovery coefficient, it is characterized in that, including the following steps: 1) establish the flat plate model of particle-wall collision working condition;2) establish non-spherical particle model and carry out DEM simulation;3) according to the motion parameter of non-spherical particle after collision, combined with free fall motion, the landing point of particle is calculated, and the random landing point distribution of non-spherical particle after collision with wall is quantified using probability density function;4) design several non-spherical particle models to carry out the above simulation and calculation, obtain the energy recovery coefficient and random landing point distribution of several different non-spherical particles;5) build artificial neural network training model, use Python tool to establish the nonlinear fitting relationship between random landing point distribution and energy recovery coefficient by artificial neural network, construct non-spherical particle energy recovery coefficient prediction model;The application has important significance to the research of particle-wall collision field.

Provided are a finger motion excessiveness evaluation method that can be used to quantitatively evaluate the excessiveness of finger motions by means of a simple measurement, and easily make a determination regarding adaptation to splint therapy, and a computer program and a device associated with the method.　A finger motion excessiveness evaluation method according to the present invention comprises: a measurement step S1 for measuring a finger tapping motion, which is an opening / closing motion of two fingers, for both left and right fingers on a healthy side and an affected side of a subject; a calculation step S3 for calculating an opening width left / right difference ratio, obtained by dividing the value of the maximum opening width between the two fingers on the affected side by the value of the maximum opening width on the healthy side, and calculating an opening speed left / right difference ratio, obtained by dividing the value of the maximum opening speed between the two fingers on the affected side by the value of the maximum opening speed on the healthy side, on the basis of the measurement data; and determination steps S5, S7, S8 for determining that the subject belongs to an excessive motion group when both the opening width left / right difference ratio and the opening speed left / right difference ratio are equal to or greater than a predetermined threshold, determining that the subject belongs to a motion restricted group when both the opening width left / right difference ratio and the opening speed left / right difference ratio are less than the predetermined threshold, and determining that the subject belongs to a control group when one of the opening width left / right difference ratio or the opening speed left / right difference ratio is less than the predetermined threshold and the other is equal to or greater than the predetermined threshold.

1. Name of the product in this design: Graphical User Interface for Calculating Motion of Electronic Device and its Data Input Area. 2. Purpose of this design: An electronic device. 3. The key design features of this product are the graphical user interface portion for which protection is sought. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: Design 1: The main view displays the interface for calculating the motion of the moving part. The left side of the main view of Design 1 displays an input box for user interaction, where users can fill in or select data related to the motion calculation of the mover. The right side of the main view of Design 1 displays the corresponding motion curve of the mover based on the input data. In the main view of Design 1, the single green block represents the content screen, and the X represents a variable character. In the main view of Design 2, the data input area of ​​the motion calculation interface of the part that needs to be protected is displayed. The data input area specifically displays the information involved in the motion calculation of the motion, such as "basic information", "setting parameters", "power configuration" and "actual calculation results" shown. The input boxes shown in the data input area are for user interaction. Users can enter data in the input boxes by filling in or selecting. In the main view of Design 2, the X represents a variable character. 7. Other situations requiring explanation: Design 1 requests protection for the overall appearance design of the product. Design 2 requests protection for a portion of the product's appearance design, wherein the portion covered by the blue semi-transparent layer is the part for which protection is not required.

Control circuitry for a crane, comprises an input interface (102) configured to receive readings of sensors (174, 520) sensing operating parameters of the crane and an output interface (104) to output control data to cause actuators of the crane to perform a movement. A compute circuit (106) is configured to control the movement of the actuators in a first operation mode and in a second operation mode, wherein at least one kinematic parameter of the actuators is limited in the second mode as compared to the first mode.

The invention discloses a flatness control system for diffusion plate production. According to the system, laser and visual data are collected in real time through the PLC, and a multi-sensor fusion algorithm of the motion calculation card is combined, so that the system can dynamically capture the micro deformation trend of the surface of the plate and quickly generate a compensation instruction. The cooperative action of the electric push rod and the air bag adjuster directly acts on the conveying roller and the traction device, so that the problems of wave deformation and local concave-convex are effectively inhibited, the surface uniformity of the finished diffusion plate reaches a higher standard, meanwhile, the cost of manual inspection and offline repair is reduced, and the production efficiency is improved. The flatness control precision and the response speed in diffusion plate production are remarkably improved, and the stability under complex working conditions is enhanced through a hierarchical control strategy. The linkage algorithm of the PLC and the motion calculation card automatically adjusts compensation parameters according to different materials and production speeds, continuous operation of a high-speed production line is guaranteed, and edge abrasion caused by traditional mechanical adjustment is avoided.

It is difficult to accurately recognize movements from motion information related to localized body parts. [Solution] The information processing device of the present disclosure includes: a first motion calculation unit that calculates a first motion feature representing the characteristics of a person's movements based on whole-body motion data, which is motion data of the whole body of a person based on training data representing the movements of a person; a second motion calculation unit that calculates a second motion feature representing the characteristics of a person's movements based on local motion data, which is motion data of a local part of a person; and an update unit that updates parameters used by the second motion calculation unit to calculate the second motion feature based on training motion features, which are pre-specified motion characteristics of a person corresponding to training data, the first motion feature, and the second motion feature.

Embodiments of the present application relate to the field of optical tomography technology, and in particular to a computer vision-driven optical tomography reconstruction method and system. The method includes the following steps: obtaining microscopic projection images of cells in multiple directions; identifying the cells in the microscopic projection images and cropping the microscopic projection images into images with consistent sizes; separating the cells from the background area; determining the exact positions of the cells in each frame based on the high contrast of the images after cell segmentation and precisely aligning the positions of the segmented cells; using a Harris corner detector to implement dynamic feature extraction on the cell rotation video; using an optical flow method to track the feature motion in the image sequence and calculating the rotation angle of the cells; generating a sinogram based on the microscopic projection images and the rotation angles of the corresponding cells, and reconstructing the three-dimensional intensity distribution of the cells. The present application utilizes computer vision technology to improve the speed, robustness, and accuracy of optical tomography image reconstruction.

An autonomous robot is provided. In one example embodiment, an autonomous robot can include a main body including one or more compartments. The one or more compartments can be configured to provide support for transporting an item. The autonomous robot can include a mobility assembly affixed to the main body and a sensor configured to obtain sensor data associated with a surrounding environment of the autonomous robot. The autonomous robot can include a computing system configured to plan a motion of the autonomous robot based at least in part on the sensor data. The computing system can be operably connected to the mobility assembly for controlling a motion of the autonomous robot. The autonomous robot can include a coupling assembly configured to temporarily secure the autonomous robot to an autonomous vehicle. The autonomous robot can include a power system and a ventilation system that can interface with the autonomous vehicle.

Techniques are discussed herein for restoring autonomous vehicle operations after one or more onboard computer systems have failed. An autonomous vehicle may comprise a primary compute node (PCN), an active motion compute node (MCN) and a backup MCN. In the event of a fault or failure at the active MCN, the backup MCN can take control of the autonomous vehicle, in an operation referred to herein as a "'backup MCN takeover."Subsequent "active MCN takeback" techniques can be applied to restore active MCN control of the autonomous vehicle, and to relinquish backup MCN control of the autonomous vehicle. If an active MCN takeback is successfully completed, the autonomous vehicle can return to an autonomous mission that was in place prior to the fault or failure at the active MCN.

Method for projecting light distributions (10) for a vehicle (12, 12a) using a light distribution system (14), wherein the light distribution system (14) comprises at least one sensor unit (16) for determining position data (18) of the vehicle (12, 12a), a computing unit (20), and at least one light projector (22), wherein the computing unit (20) converts target light distributions (24) stored in the computing unit (20) into projection data (26) related to the light projector (22), and the light projector (22) uses the projection data (26) to project the light distributions (10) onto at least one projection surface (32) in the environment, wherein the position data (18) of the vehicle (12, 12a) determined by the at least one sensor unit (16) are12a) are transmitted to a correction calculation module (28) of the computing unit (20), and the correction calculation module (28) uses the position data (18) to calculate corrected projection data (30) from the projection data (26), and the corrected projection data (30) are forwarded to the light projector (22) for the projection of corrected light distributions (10), characterized in that several sensor units (16), comprising inertial sensors and a camera system, are combined with the vehicle data, such as speed and steering angle, to further increase the accuracy of the correction by skillfully predicting the possible vehicle movements determined as position data (18), wherein the inertial sensors are acceleration sensors and yaw rate sensors which determine the vehicle movements as position data (18), wherein the sensor units (16) transmit position data (18) of the vehicle (12,12a) provide for use in the correction calculation module (28), wherein the vehicle movements are calculated as position data (18) in the correction calculation module (28) using algorithms based on the data determined by the camera system, wherein the projection data (26) are calculated by the computing unit (20) in parallel with the determination of the projection data (30) corrected by the correction calculation module (28), based on the specified target light distribution (24) and the position of the projection surface (32) detected by the light distribution system (14), wherein the corrected projection data (30) are recalculated every 10 to 40 milliseconds, and the correction calculation module (28) always refers back to the most recently determined projection data (26), whereby irregularities of the projection surface (32) are taken into account and thus a pre-distortion is implemented in the projection data (26) and in the corrected projection data (30).

The embodiment of the invention provides a universal motion processor for controlling motion of a physical entity. The core structure of the processor comprises at least one programmable motion calculation core used for processing calculation tasks related to dynamics and motion optimization of the physical entity; the at least one model interface is used for receiving model data describing the mechanical structure of the physical entity; and the at least one instruction interface is used for receiving motion task instructions. Wherein the motion computing core is configured to process a motion task instruction received through the instruction interface based on model data received through the model interface to generate a control signal for driving the physical entity. Based on the scheme, the invention provides a special hardware core to ensure the calculation performance and real-time performance of motion control, and meanwhile, through a standardized interface design, the system can adapt to different physical entities, thereby fundamentally solving the contradiction between'special 'and'universal'.

To prevent the control device from exceeding its allowable computational load and to suppress a decrease in control accuracy. [Solution] The drive control device includes: an motion generation unit that generates a target motion of the front work device using parameters based on the detection result of the attitude sensor and work design information; an actuator control unit that calculates the target operating speed of the actuator based on the target motion generated by the motion generation unit and generates and outputs a control signal to control the operation of the actuator at the calculated target operating speed; a computation load estimation unit that estimates the computation load of the drive control device based on the calculation time of the target motion in the motion generation unit, the calculation time of the target operating speed in the actuator control unit, and the load of the overall control device; and a parameter adjustment unit that adjusts the parameters to reduce the computation load of the motion generation unit if it is determined that the computation load estimated by the computation load estimation unit is higher than a predetermined reference value.

A system and method for detecting, quantifying, and / or measuring motion of an object and correcting for exposure includes providing a processor and at least one video sensor; determining video recording parameters of the at least one video sensor; recording, by the at least one video sensor, video of the object; extracting a data set from the video wherein the data set describes the motion of the object; calculating a frequency transform of the data set for at least one frequency; and performing exposure correction at the at least one frequency based on the recording parameters.

Method for operating a human-machine interface (10) comprising the steps: - Applying a large number of accelerometers (12) to the skin (16) of a user by means of a holding device (14) - Calculating a user-requested input command from the user's muscle movements detected by the accelerometers (12), by the following procedure steps: ◯ Determining a common movement of the accelerometers (12) caused by a movement of the entire body part (18) of the user to which the accelerometers (12) are attached, ◯ Removing the accelerations of the accelerometers (12) caused by this movement of the accelerometers (12), so that only their relative accelerations to each other remain and are taken into account for further processing.

Control circuitry (110) for a crane (120), comprising es an input interface (102) configured to receive readings of sensors sensing operating parameters of the crane (120) and an output interface (104) to output control data to cause actuators of the crane (120) to cause a motion of at least one of a boom (130) of a boom system or a column (160) of the crane (120). A compute circuit (106) is configured to control the operation of a winch arrangement (140, 400) mounted to a boom (130) of the boom system, wherein a position of an attachment reference (150) of a cable (420) of the winch arrangement (140, 400) moves along a definable path during movement of the crane (120).

The invention belongs to the technical field of ship yawing motion calculation, and particularly relates to a ship yawing motion numerical calculation method with a direction angle, which comprises the following steps: carrying out a propeller open water test to obtain a propeller open water performance table; importing the obtained open water performance table into starccm + software, and performing numerical simulation on pure yawing motion with a direction angle under ship ballast draft by combining a volume force method and a reference system coordinate method to obtain a longitudinal force and yawing moment curve; meanwhile, pure yawing motion with a direction angle under ship ballast draft is conducted through a real test, and a longitudinal force and yawing moment curve is obtained; respectively calculating hydrodynamic derivatives corresponding to the numerical simulation and the real test based on the longitudinal force and the rocking head torque curve obtained by the numerical simulation and the real test; and comparing a numerical simulation result with a real test result through a least square method, and determining whether the numerical simulation is accurate or not. The numerical simulation calculation method provided by the invention is reliable and accurate in calculation result, and the calculation efficiency of numerical simulation is remarkably improved.

A system and method of calibrating moving cameras capturing a sporting event is disclosed herein. A computing system retrieves a broadcast video feed for a sporting event. The broadcast video feed includes a plurality of video frames. The computing system labels, via a neural network, components of a playing surface captured in each video frame. The computing system matches a subset of labeled video frames to a set of templates with various camera perspectives. The computing system fits a playing surface model to the set of labeled video frames that were matched to the set of templates. The computing system identifies camera motion in each video frame using an optical flow model. The computing system generates a homography matrix for each video frame based on the fitted playing surface model and camera motion. The computing system calibrates each camera based on the homography matrix generated for each video frame.

The present invention discloses a parameterized modeling method for the in-bore motion of rifled guns. First, within the Python language framework, the idea of ​​fragmentation and splicing is employed, combined with the structural parameters of the rifled gun barrel, to calculate the three-dimensional spatial coordinates of each node. The nodes are then connected in numerical order to generate a finite element model file for the rifled gun barrel. Then, based on the body-of-revolution characteristics of the projectile belt, a three-dimensional geometric model of the projectile and belt is established and meshed in ABAQUS software. The generated finite element model file for the rifled gun barrel is imported, and materials are assigned to each component involved in the calculation of the in-bore motion of the gun. Assembly, analysis step creation, contact definition, load and constraint setting are sequentially performed to create a job. The execution log file is retrieved, the key operation step codes are retained, and parameters related to the projectile belt structure are replaced with variables. Finally, the RSG dialog box builder is used to create a GUI plug-in for generating the rifled gun barrel and projectile belt, respectively, and performing pre-processing. The present invention greatly improves the efficiency of modeling and pre-processing by enabling one-click generation of a rifled artillery barrel finite element model, one-click completion of parametric modeling of projectile belts, and one-click completion of finite element analysis pre-processing of the motion within the rifled artillery firing chamber, thus providing a fast and efficient method for finite element simulation analysis of the artillery firing process.

This invention relates to a processing method for improving auxiliary clamping efficiency in a laser processing CNC system, comprising the following steps: raising the Z-axis; when the Z-axis moves to the position of the outer circle of the tube, the auxiliary clamping begins to release; the X-axis, Y-axis, Z-axis, and B-axis begin to move towards the starting point of the next cutting segment; calculating the maximum remaining angle of the B-axis; when the B-axis moves to a certain position from the endpoint, the auxiliary clamping begins to clamp; the Z-axis descends to the processing position, ready for the next processing. The processing method, device, processor, and computer-readable storage medium of this invention in a laser processing CNC system for improving auxiliary clamping efficiency reduce the waiting time of the auxiliary clamping and shorten the overall processing time. This invention provides a method for solving the maximum remaining angle of the B-axis in the method for improving auxiliary clamping efficiency, simplifying the process and improving the efficiency of the calculation.

The objective is to provide a method for calculating forward motion that can quickly determine the position and orientation of the mechanical interface of a 6-degree-of-freedom parallel link robot. [Solution] A method for calculating forward motion for calculating the position and orientation of a mechanical interface of a 6-degree-of-freedom parallel link robot, wherein the parallel link robot has first to sixth movable bodies that move on straight lines parallel to each other, first to sixth rods whose base ends are connected to each of the first to sixth movable bodies via ball joints and which have the same rod length, and the mechanical interface connected to the tip of each of the first to sixth rods via ball joints.

The present invention discloses a vehicle visual positioning method, system, device and readable storage medium. The rotation matrix in the vehicle motion process is parameterized as an angle variation, and the translation vector in the vehicle motion process is parameterized as a translation component to be represented by graph theory concepts. A feature detection algorithm based on robust feature point AKAZE and a feature point matching algorithm combining zero-mean normalized cross-correlation and multi-strategy are used to ensure the accuracy of feature point extraction and feature point association. An improved RANSAC algorithm's external point removal algorithm removes noise points and erroneous matching points, ensuring the accuracy of motion calculation. The vehicle motion information is solved by a nonlinear weighted least square method and a filtering processing technology based on Sigma points is used to further optimize the motion result. The positioning accuracy is high. The improved RANSAC algorithm based on initial value estimation reduces the complexity of external point removal, ensures the real-time performance of the algorithm, reduces the number of feature points, thereby reducing the complexity of the algorithm and ensuring the real-time performance of the entire algorithm.

The invention discloses a large model application platform construction method oriented to aircraft task intellectualization. The construction method of the platform comprises the following steps: deploying a large language model for local quantification of an aircraft orbital motion calculation vertical field task as a core processing engine; an aircraft orbital motion calculation type task planning workflow constructed based on an open source framework is established, and a complex orbital motion calculation type task is decomposed into fine grit; building an aircraft orbit task real-time correction workflow for monitoring a task execution state and dynamically adjusting a plan; a set of model context protocol tool set required by aircraft orbital motion calculation is assembled, calculation, model, perception and action tools are integrated, and the capability boundary of a special large model is greatly expanded. Besides, an aircraft orbit calculation type task execution specification manual knowledge base and a retrieval auxiliary workflow thereof are also constructed, and an accurate vertical field specification basis is provided for task execution through vectorization storage and semantic retrieval.

A first movement calculation unit 30 calculates a first movement direction v1 and a first movement amount q1 of an object X from a first frame f1 and a second frame f2 in a first video α1. A superimposition unit 40 generates a superimposed image p in which an image indicating the direction of the first movement direction v1 is superimposed on the image of the first frame f1. A second movement calculation unit 70 calculates a second movement direction v2 and a second movement amount q2 of a user's predetermined portion Y from a third frame f3 and a fourth frame f4 in a second video β obtained by imaging the predetermined portion Y moving along the superimposed image p. When the first movement direction v1 and the second movement direction v2 match and the first movement amount q1 and the second movement amount q2 satisfy a predetermined relationship, a control unit 80 updates a frame next to the first frame f1 to a new first frame f1, updates a frame next to the second frame f2 to a new second frame f2, and causes the superimposition unit 40 to generate the superimposed image p.