289 results about "Movement tracking" patented technology

The invention belongs to the technical field of collaborative robots, and particularly discloses and provides an anti-explosion mechanical arm positive pressure control system and method.The system comprises a mechanical arm motion tracking module, an environment data monitoring module, a configuration adjustment analysis module, a pressure adjustment analysis module, a database and a pressure adjustment execution terminal. The mechanical arm motion tracking module is designed to track the motion state of the mechanical arm and record motion data, a key part pressure sensor is started to monitor pressure data, and the correlation change of motion and pressure can be captured. The environment data monitoring module monitors environment parameters of a working area in real time, and environment changes are comprehensively mastered. The all-dimensional monitoring capability of the system is improved, factors influencing positive pressure control can be obtained more comprehensively, meanwhile, configuration adjustment judgment is carried out in combination with environment, movement and pressure data, adjustment values are dynamically determined, and intelligent decision making and self-adaptive adjustment of mechanical arm positive pressure control are achieved.

The invention is suitable for the technical field of reliability test of numerical control machine tools, and provides a ball screw pair comprehensive performance test device and method for simulating real working conditions. The device comprises a ball screw pair, a test device base, a rolling guide rail pair, a grating ruler integrated installation unit, two sets of support driving units, a loading workbench, an axial force simulation loading unit, a tested workbench and a comprehensive performance detection unit. The two sets of supporting and driving units are distributed on the test device base in a staggered alignment manner and are respectively connected with the loading workbench and the tested workbench, and synchronous driving of the loading workbench and the tested workbench is realized through synchronous control; and the axial force simulation loading unit realizes static and dynamic simulation loading of the axial force through electro-hydraulic servo control. According to the invention, a test device and technical support are provided for carrying out the reliable comprehensive performance bench test of the ball screw pair, and the problems of the ball screw pair in the aspects of high-frequency dynamic load simulation loading, comprehensive performance test and motion tracking loading are solved.

Systems and methods for motion tracking on a hardware device without a camera and / or without a sufficiently powerful hardware processor, by offloading pose processing fully or partially to a mobile device, are disclosed. Methods executable on the hardware device include receiving pose data associated with a user from the mobile device, and performing a touchless control of an application on the hardware device, based on the received pose data. Methods executable on the mobile device include capturing at least one image associated with a user, performing a pose recognition algorithm on the mobile device, based on the captured image, to generate pose data for performing a touchless control of an application on the hardware device, and transmitting the pose data to the hardware device, using the network connection. The methods and systems include embodiments where the pose recognition algorithm uses machine learning.

Provided in the present invention are an exoskeleton shared control method, system and device based on AI co-driving, and a storage medium. The exoskeleton shared control method based on AI co-driving comprises: acquiring real-time pose data of an exoskeleton wearer; on the basis of the pose data, performing switching between a local trajectory correction mode and a hybrid long-short-term motion optimization mode in real time, wherein the local trajectory correction mode is completed on the basis of an AI co-driving policy network model; and performing multi-task tracking on the direction of a three-dimensional motion of an exoskeleton and a walking trajectory thereof, so as to achieve motion tracking control over the exoskeleton. By using the method provided in the present application, when encountering a sudden obstacle, an initial path can be corrected to an optimal path in combination with pose data and target point image feature data, thereby helping an exoskeleton to realize omnidirectional walking in a three-dimensional complex environment.

The invention discloses an endoscope monocular dynamic scene reconstruction method based on dynamic Gaussian splashing and motion tracking, and the method comprises the steps: firstly obtaining a dynamic scene image, obtaining an initial three-dimensional track through introducing auxiliary prior information, and then obtaining three-dimensional Gaussian; based on the auxiliary prior information, generating a group of compact Sim3 motion bases, and obtaining each three-dimensional Gaussian transformation function in the dynamic scene image by using the weighted combination of the Sim3 motion bases, the parameters of the three-dimensional Gaussian transformation function including the transformation of the position and the shape along with the time; and performing three-dimensional Gaussian transformation to each frame of image of the dynamic scene according to the three-dimensional Gaussian transformation function, and performing image rendering on each frame to obtain a rendered image. According to the method, monocular depth and dense displacement field prior are combined, and the problem of monocular scale drift is solved by utilizing depth relative sequence stability. According to the method, real-time rendering is ensured, and meanwhile, the dynamic scene reconstruction precision is remarkably improved.

The invention relates to an automatic pet shooting device and a pet behavior recognition method, and belongs to the technical field of behavior recognition. The device comprises a motion module, a video data acquisition module, a target tracking module, a behavior recognition module and an uploading judgment module. The device monitors and shoots behavior images or video data of a pet in real time through the video data acquisition module, tracks the position of the pet in real time through the target tracking module, and guides the device to move to realize autonomous movement tracking. Meanwhile, behavior recognition is carried out on the behavior image of the pet through a corresponding behavior recognition algorithm, remote monitoring of the pet is achieved, and meanwhile the functionality and practicability of the device are improved. Meanwhile, the uploading judgment module is used for carrying out pet state judgment on the pet behavior recognition result according to the photo shooting logic and the pet abnormity judgment logic, shot video data are uploaded to the remote monitoring terminal according to the pet state judgment result, and a user can conveniently check the pet state.

The invention relates to the technical field of teleoperation, in particular to a teleoperation robot auxiliary control method based on a safety margin theory. The method comprises the following steps: establishing a three-dimensional digital twinborn model according to an image acquisition device, and obtaining a target object distance, a communication time delay size and a motion tracking error; based on the three factors, a fuzzy control theory is adopted to calculate a teleoperation safety margin value, and the safety of the current teleoperation is quantitatively evaluated. And calculating a master-slave motion mapping ratio and an end view display ratio according to the safety margin value. And constructing virtual force guidance according to the safety margin value, feeding back the virtual force guidance to an operator through force feedback equipment, and guiding the operator to complete a teleoperation task in combination with visual interaction equipment. Compared with a traditional teleoperation method, the method can effectively improve teleoperation efficiency and safety, and can better adapt to a complex long-distance working environment.

The invention relates to the field of computer vision and artificial intelligence, in particular to a real-time multi-person motion analysis system based on motion perception and semantic understanding, which comprises a motion perception module, a motion tracking module, a motion semantic understanding module and a motion performance analysis module. The motion area segmentation unit adopts a background modeling or inter-frame difference method to identify a motion area and generate a motion mask; the target detection unit is connected with the central processing unit through a data bus and used for processing video frame data and detecting the position and the bounding box of a moving target. The motion area segmentation unit is connected with the target detection unit and is used for generating a motion mask. By integrating a plurality of modules, the motion data can be comprehensively captured and analyzed, and the accuracy and real-time performance of motion analysis are improved. Through combination of the target detection unit and the motion area segmentation unit, the system can accurately identify a motion target and a motion area, and a solid foundation is laid for subsequent tracking and analysis.

The invention relates to the technical field of dynamic visual target motion tracking control, in particular to a dynamic visual target motion tracking control method and system based on deep learning, and the method comprises the steps: synchronously collecting continuous multi-frame target scene image data through a visual multi-frame collection module; and performing time sequence association and memory fusion on target features in continuous multi-frame target scene image data through a cross-frame feature memory fusion module, and constructing a target feature model. According to the invention, the current and historical stable features are dynamically fused through the cross-frame feature memory fusion module, time sequence association is realized in combination with the long and short-term memory network, and the problem of slow feature model updating under target deformation and shielding is solved; the deformation-shielding bimodal recognition module accurately recognizes a scene state, provides a basis for the multi-branch Kalman filtering prediction module, enables the multi-branch Kalman filtering prediction module to call a corresponding branch, corrects a prediction equation through a compensation factor, and improves the position prediction accuracy.

The invention discloses a target tracking method and system based on visual identification and an underwater robot, and relates to the technical field of underwater robots. According to the invention, automatic tracking and monitoring of an underwater target are realized by using a visual identification technology, operations such as an image identification technology of YOLOv5, a motion tracking technology of an optical flow and a Kalman filter, a target re-identification algorithm of deep learning, image enhancement and the like are specifically combined, and the intelligent level and the working efficiency of underwater operation are comprehensively improved. According to the method, the diver can be efficiently tracked in a complex underwater environment, and high recognition and tracking precision is ensured under the condition that the diver disappears or the motion trail is complex.

The invention relates to the technical field of image processing, and discloses a three-dimensional reconstruction method, device and equipment of a moving object and a readable storage medium, and the three-dimensional reconstruction method of the moving object comprises the steps: obtaining a plurality of fringe images of a measured moving object at continuous moments, selecting one frame as a reference frame, and obtaining a plurality of fringe images of the measured moving object at continuous moments; constructing an image set together with adjacent image frames; inputting the image set into a deep learning network for pixel-level motion tracking to obtain motion position information; based on the motion information and the intensity information, constructing a phase calculation equation set to obtain a relative phase value; performing phase unwrapping processing on the relative phase value to obtain absolute phase information; and performing phase height mapping by combining system calibration parameters to obtain dynamic three-dimensional shape data. According to the method, phase distortion caused by motion interference is remarkably eliminated, the three-dimensional reconstruction precision and real-time performance in a dynamic scene are improved, and a reliable guarantee is provided for industrial detection and high-speed target measurement.

The invention discloses an automatic tracking method for an intelligent video monitoring terminal based on target detection, particularly relates to the field of automatic tracking of video monitoring, and comprises an image intelligent analysis and processing module and a monitoring terminal. According to the method, firstly, the relative distance of a target is measured and calculated through a target distance measurement and calculation module, a moving track prediction module and a target behavior detection module, the moving track of the target is recorded and predicted, the moving behavior of the target is detected, and a key target is analyzed in combination with an image intelligent analysis and processing module; automatic switching of key targets is achieved through the target movement tracking module according to changes of the targets, the shooting orientation angle and the focal length of the camera are sequentially controlled through the execution module, the key targets are located in the optimal state of a video picture, key target tracking, recording and shooting are achieved, and it is guaranteed that key monitoring objects on a working site are clearly visible; and abnormal conditions caused by human negligence are avoided.

The invention relates to the technical field of metallurgical continuous casting production, in particular to a continuous casting blank movement tracking method, which comprises the following steps of: calculating the thermal deformation of each section of a casting blank according to the section temperature of the casting blank along the length direction in combination with the material thermal expansion coefficient and the section length at the corresponding section temperature, and generating the real-time correction position of the casting blank after a physical correction track is generated; on the basis of the real-time correction position, a preset casting blank benchmark reference position, the real-time pulling speed, the real-time cooling water amount, respective preset benchmarks and motion inertia deviations calculated on the basis of material physical properties and the real-time pulling speed, track prediction adjustment factors are generated; generating a compensation amount for the reference disturbance compensation amount by combining the matching degree of the visual solidification front edge and the model prediction, obtaining a position compensation value, superposing the position compensation value to the original trajectory, obtaining a final tracking trajectory, converting the final tracking trajectory into a servo control instruction, and dynamically correcting the casting blank tracking position. According to the invention, the precision, the dynamic performance and the intelligent performance of the continuous casting blank movement tracking are realized.

Methods and systems for performing computer-assisted image-guided surgery, including robotically-assisted surgery. A method of displaying image data includes displaying image data of a patient on a handheld display device, tracking the handheld display device using a motion tracking system, and modifying the image data displayed in response to changes in the position and orientation of the handheld display device. Further embodiments include a sterile case for a handheld display device, display devices on a robotic arm, and methods and systems for performing image-guided surgery using multiple reference marker devices fixed to a patient.

Automated systems and methods are presented for determining the physiological response of human or suitable animal subjects to physical exertion. The methods and systems can include monitoring sensors that capture the motion of the subject along with corresponding physiological data, and can track such motion for the duration of a period of physical exertion. The system is able to acquire an initial stream of physiological data from the subject during a range of physical exertion activities that are representative of the events intended to be monitored with the proposed method and system, enabling a corresponding dynamic physiological response model to be created. The motion tracking system and physiological response model can then be used to predict the physiological response to physical exertion events under a prescribed framework, including applications during real-time event monitoring.

Known jaw movement tracking systems generally allow for a limited tracking of the jaw movement. e.g. they are only able to track the jaw movement in two dimensions or track muscle activations without specifying direction of movements, and are thus unable to fully track the complex jaw movements. The reduced tracking ability of known devices reduces the ability to discriminate between different jaw movements based on the tracked movement. A need exists for a jaw movement tracking system that allows jaw movement tracking for discriminating between different jaw movements. The invention relates to a jaw movement tracking system. invention further relates to a method for use of the jaw movement tracking system.

Example methods, apparatuses, and computer-readable media are provided. Example methods include generating a virtual environment including a first shape and a second shape in a virtual viewpoint, the first shape in front of the second shape. The second shape adjusts as the virtual viewpoint adjusts, and is offset from the first shape along a test axis. The first shape is affixed to the virtual viewpoint. The virtual viewpoint is configured to adjust in response to movement of a HMD. The method includes moving a position of the virtual viewpoint with respect to the second shape in response to the movement. The method includes recording reference data associated with moving of the position of the virtual viewpoint. The method includes generating a positional displacement vector by comparing reference data of the second shape with reference data of the first shape, and determining a HMD movement tracking error based on the vector.

An onboard camera, motion detection, and early warning system for monitoring a parameterized safety zone around personal transportation systems for detecting motion, tracking changes, and monitoring the parameterized safety zone for providing early warning notifications.

The invention discloses an upper limb rehabilitation training system and method for a stroke patient. Relates to the technical field of medical rehabilitation. According to the stroke upper limb rehabilitation training system and method, the limbs are driven by a machine to do repeated movement, a nervous system for controlling limb movement is stimulated and reconstructed, and therefore the movement function of the limbs is recovered, and the rehabilitation training effect of the limbs is improved. On the basis of an existing motion tracking and feedback technology, the system and the method are improved, real-time data analysis is carried out based on a sensor, a brain-computer interface technology and a cloud platform, influences of operation environment information and motion performance are considered in individualized requirements of patients, individual differences and environment variables are comprehensively considered in the rehabilitation process, and the rehabilitation effect is improved. A patient can perform rehabilitation training at any place, a rehabilitation physician, the patient and family members can check the rehabilitation condition of the patient at any time, and the precise training system and method suitable for various environments and changeable rehabilitation requirements are provided.

A method and system for motion tracking that integrates pose estimation and segmentation. The method includes accessing a first set of keypoints generated by processing at least one image of a body area of a person. The first set of keypoints can be generated via pose estimation. The method further includes processing the at least one image to generate a body mask subsequently filtered to identify a second set of body contour keypoints, executing a predetermined function to identify a new keypoint based on the first set of keypoint and the second set of keypoints, generating a third set of keypoints based on the first set of keypoints and the new keypoint, and tracking the third set of keypoints to generate motion tracking data. The method generates feedback for the person based on the motion tracking data. The new keypoint and / or feedback can be generated based on a physical activity.

A user's accommodative spasm can be evaluated and mitigated via a virtual reality (VR) system, which can include a VR headset in electronic communication with a computing device. The computing device causes virtual environments, which can include objects, optotypes, various lighting conditions, and various weather conditions, to be displayed on the VR headset. Using varying combinations of eye-tracking sensors, eye-tracking cameras, motion-tracking sensors, handheld devices, and microphones, the VR headset collects data about the user as she focuses on various objects placed at different distances away from her in the virtual environments. Optionally, advanced algorithms in the computing device dynamically alter the virtual environments and the visual tasks and analyze the user's responses to evaluate the user's accommodative spasm.

A wearable device integrating a network of interactive sensors is disclosed, wherein said sensors are configured to detect, monitor, and transmit real-time spatial position data to a central control unit. The central control unit comprises a processing module that computes the relative positioning and orientation of each sensor within a predefined reference frame, enabling continuous user movement tracking. Upon reaching a predefined spatial condition, the system generates a feedback signal, triggering a responsive sensory output via a haptic, auditory, or visual feedback mechanism. The device employs multiple positioning technologies, including inertial measurement units (IMUs), accelerometers, gyroscopes, magnetometers, radio frequency identification (RFID), Bluetooth Low Energy (BLE), ultra-wideband (UWB), and infrared tracking to ensure high-precision spatial awareness. The system is designed for applications in sports performance optimization, medical rehabilitation, virtual and augmented reality (VR / AR), occupational safety, and industrial hazard detection.

The invention discloses a distributed electric vehicle motion planning method and system considering surrounding vehicle interactive perception, and relates to the technical field of electric vehicle motion planning. The method comprises the following steps: constructing a distributed electrically-driven automobile nonlinear dynamic model, and designing a motion tracking controller by adopting a feedback linearization method; based on the constructed vehicle closed-loop dynamics system, a regional polyhedron approximation method is adopted to carry out modeling and characterization on a safety forward reachable set of the vehicle; and in combination with a probability distribution model of interaction behaviors of surrounding vehicles, introducing a conditional value-at-risk constraint mechanism, converting an automobile motion planning problem into a trajectory optimization problem, and solving and outputting a final motion planning trajectory. According to the method, the advantage that four wheels of a distributed electric drive automobile are independent and controllable is fully utilized, the control freedom degree of the method is remarkably improved compared with centralized drive, a conditional value-at-risk constraint mechanism is introduced to be combined with a surrounding automobile interaction behavior probability distribution model, and safety and agility balance in an uncertain environment is guaranteed.

Embodiments described herein relate to systems, devices, and methods for use in the implementation of a brain-computer interface that integrates real-time eye-movement tracking with brain activity tracking to present and update a user interface that is strategically designed for high speed and accuracy of human—machine interaction. Embodiments described herein also relate to the implementation of a hardware agnostic brain-computer interface with specific user interface adaptations to enable high-speed, intuitive, and accurate user manipulation of applications and / or machines.

A method of and an apparatus for motion tracking of a subject located in a scanner are presented. The method comprises generating a baseline 3D surface representation of a surface region of the subject at a first point of time (T(0)); generating a subsequent 3D surface representation of the surface region of the subject at a subsequent point of time (T(s)); determining a best-fit registration of the subsequent 3D surface representation with at least one constraint relative to the baseline 3D surface representation and determining at least one motion tracking parameter. The method may include selecting at least one virtual feature and associating the at least one virtual feature to the baseline 3D surface representation, wherein the constraint comprises a restriction of at least one parameter of the at least one virtual feature associated to the best-fit subsequent 3D surface representation relative to the at least one parameter of the at least one virtual feature associated to the baseline 3D surface representation.

Vision safety protocols in workplaces (e.g., a construction site, factory, or hospital) can be evaluated via a virtual reality (VR) system, which can include a VR headset in electronic communication with a computing device. The computing device causes virtual environments with virtual hazards to be displayed on the VR headset. The computing device can prompt the user to complete a task in the virtual environment while adhering to a set of vision safety protocols. Using varying combinations of eye-tracking sensors, eye-tracking cameras, motion-tracking sensors, handheld devices, and microphones, the VR headset collects data about the user as she completes the task. Optionally, algorithms in the computing device can assess the efficacy of the vision safety protocols based on the user's performance of the task and recommend changes to the vision safety protocols that increase workplace safety and efficiency. Optionally, the computing device can cause the virtual hazards to be changed.

The invention discloses a five-degree-of-freedom electromagnetic positioning system and method, and the system comprises a transmitting unit which comprises a plurality of single-axis transmitting coils and is used for generating a magnetic field in a three-dimensional space; the receiving unit is used for collecting field intensity information in a three-dimensional space; the control and data processing unit is used for inputting the field intensity information collected by the receiving unit into a pose initial value prediction network and outputting initial pose information of the receiving unit; inputting the initial attitude information into a coil magnetic field modeling network to obtain theoretical field intensity; and the iterative optimization module acquires a field intensity difference according to the theoretical field intensity and the acquired field intensity information, updates the attitude information according to the field intensity difference, and returns to execute the step of acquiring the theoretical field intensity until a preset iteration termination condition is reached, thereby acquiring the final attitude information. The method can reduce the complexity of a traditional electromagnetic positioning algorithm, improves the positioning precision and speed, can be widely applied to the fields of auxiliary medical treatment, man-machine interaction and motion tracking, and achieves a multi-degree-of-freedom electromagnetic positioning function.

A user's visual disorders can be treated via a virtual reality (VR) system, which can include a VR headset in electronic communication with a computing device. The computing device causes vision tests to be displayed on the VR headset. Using varying combinations of eye-tracking sensors, eye-tracking cameras, motion-tracking sensors, handheld devices, and microphones, the VR headset can collect data about the user as she completes the vision tests. Using the data collected by the VR headset, the computing device can evaluate the user for various visual disorders and develop a personalized vision therapy plan for the user. Optionally, advanced algorithms in the computing device dynamically alter the vision therapy plan based on the user's performance and the progression of her visual disorders.

Apparatus is provided to detect motion of a target reflecting one or more pure tone signals, comprising transmission of one or more pure tone acoustic signals, reception of the signal reflected by a target ensonified by the transmitted signal, and motion detection of the ensonified target from analysis of the Discrete Fourier Transform (DFT) of the received signal, in particular values of the time-variance of energy within adjacent frequency bins in the signal DFT, where the emitted tone has a frequency at the boundary between the two adjacent frequency bins.

The technology disclosed relates to coordinating motion-capture of a hand by a network of motion-capture sensors having overlapping fields of view. In particular, it relates to designating a first sensor among three or more motion-capture sensors as having a master frame of reference, observing motion of a hand as it passes through overlapping fields of view of the respective motion-capture sensors, synchronizing capture of images of the hand within the overlapping fields of view by pairs of the motion-capture devices, and using the pairs of the hand images captured by the synchronized motion-capture devices to automatically calibrate the motion-capture sensors to the master frame of reference frame.