1148 results about "Kinematical model" patented technology

A position-tracking system for tracking the position of an object is disclosed. According to various embodiments, the tracking system includes a tracking device that is connected to or otherwise affixed to the object to be tracked. The tracking device may include, among other things, an inertial sensor assembly, radio transceivers and a processor. The position tracking system may also include a host processing system that is in communication with the tracking device. The position tracking system may provide variable-resolution position information based on the environment in which the object is moving. In a “wide resolution” area, the system may compute a general position for the object based on a wireless telephone network Cell-ID / map correlation architecture. In a high-resolution area, greater position resolution may be realized from the combination of a wireless aiding system and inputs from the inertial sensors. In the high-resolution mode, the system may exploit distinct patterns of motion that can be identified as motion “signatures” that are characteristic of certain types of motion. Kinematic (or object movement) models may be constructed based on these motion signatures and the position tracking system may estimate the state of the object based on the kinematic model for the current mode of the object. Adaptive and cascaded Kalman filtering may be employed in the analysis to more accurately estimate the position and velocity of the object based on the motion pattern identified.

A position-tracking system for tracking the position of an object is disclosed. According to various embodiments, the tracking system includes a tracking device that is connected to or otherwise affixed to the object to be tracked. The tracking device may include, among other things, an inertial sensor assembly, radio transceivers and a processor. The position tracking system may also include a host processing system that is in communication with the tracking device. The position tracking system may provide variable-resolution position information based on the environment in which the object is moving. In a “wide resolution” area, the system may compute a general position for the object based on a wireless telephone network Cell-ID / map correlation architecture. In a high-resolution area, greater position resolution may be realized from the combination of a wireless aiding system and inputs from the inertial sensors. In the high-resolution mode, the system may exploit distinct patterns of motion that can be identified as motion “signatures” that are characteristic of certain types of motion. Kinematic (or object movement) models may be constructed based on these motion signatures and the position tracking system may estimate the state of the object based on the kinematic model for the current mode of the object. Adaptive and cascaded Kalman filtering may be employed in the analysis to more accurately estimate the position and velocity of the object based on the motion pattern identified.

A system for determination of kinematics of a moving object comprising: a sensor producing angular data for the object at a number of observation times, a state initialization unit, receiving angular data from the sensor and on basis thereof determining a first kinematic state of the object, and a tracking filter having a prediction unit, arranged to determine a predicted kinematics state of the object on bases of a kinematic model of the object, wherein the kinematic model comprises a guidance law locked on a known position, and at least one previously determined kinematic state of the object, and a state updating unit, receiving angular data from the sensor and the predicted kinematic state of the object, and on basis thereof determining an updated kinematic state of the object.

A markerless motion capture system is provided for measurements accurate enough for biomechanical, clinical, sport, entertainment, animation, game and movie, design, ergonomics, surveillance applications. The system has multiple cameras distributed around a viewing volume. The cameras allow for the creation of three-dimensional mesh representations of an object dynamically moving within the viewing volume. A model of the object that incorporates specific morphological and kinematic model information (including soft joint constraints) is then matched to the captured three-dimensional mesh representations. The matching routine aims to embed the model into each of the three-dimensional representations using (i) iterative closest point or simulated annealing algorithms and (ii) using soft joint constraints. This unique combination of routines offers a simple, time-efficient, accurate and thus more meaningful assessment of movements. The system further offers feasibility of accurately and precisely measuring three-dimensional kinematics of the dynamically moving object or human.

A method for estimating joint angles of a multi-segment limb from inertial sensor data accurately estimates and tracks the orientations of multiple segments of the limb as a function of time using data from a single inertial measurement unit worn at the distal end of the limb. Estimated joint angles are computed from measured inertial data as a function of time in a single step using a nonlinear state space estimator. The estimator preferably includes a tracking filter such as an unscented Kalman filter or particle filter. The nonlinear state space estimator incorporates state space evolution equations based on a kinematic model of the multi-segment limb.