Intuitive Surgical Operations, Inc.

The Charles Stark Draper Laboratory, Inc.

Luna Innovations Inc.

Dogwood Logic, Inc.

Sandra M Klute

Evan M Lally

Mark Earl Froggatt

Matthew T Reaves

Juha-Pekka J Laine

Dawn K Gifford

Justin W Klein

Gregory P Blasche

Stephen Tod Kreger

Paul A Bohn

Marc W McConley

Matthew S Bottkol

James Donna

Matthew M White

Matthew A Castellucci

Bruce Dow

Michael Ricard

Emily H Templeton

Emily E Horrell

Matthew White

Matthew Castellucci

Decentralized database technology is applied to decentralized artificial intelligence (AI) information enabling collaborative AI techniques to enhance the performance of AI models and gain new insights with larger and/or better curated data sets. AI information from multiple independent sources is linked together and synthesized to render the AI information searchable, discoverable, accessible, and traceable, while also ensuring that information remains under its source's control over its lifetime, e.g., controlling the conditions under which other entities may access which pieces of AI information at a particular time.

Secure decentralized control of network access to AI models and data

Systems and methods for determining the shape and/or position of an object are described. A fiber optic shape sensor (FOSS) may be used in combination with one or more inertial measurement units (IMUs) to mutually cross-correct for errors in the sensors' measurements of position and/or orientation. The IMU(s) may be attached to the FOSS's optical fiber, such that each IMU measures the orientation of a corresponding portion of the optical fiber. The position and shape of the optical fiber can then be determined based on the measurements obtained from the IMU(s) and the measurements obtained from the FOSS. For example, the FOSS measurements and the IMU measurements can be provided to a state estimation unit (e.g., a Kalman filter), which can estimate the position and/or shape of the optical fiber based on those measurements. In some embodiments, the estimates of position are used for navigation of tethered mobile devices.

Navigation systems and methods using fiber optic shape sensors and localized position sensors

Optical frequency domain reflectometry (OFDR) circuitry to perform tasks on an optical fiber to generate calibration or correction data for calibrating or correcting a reference OFDR data set. A segmented technique is used which permits precise and accurate determination of the correction data for even initial and long fiber lengths. Correction information for each segment is stitched together to generate the correction data for the fiber.

Methods and apparatus segmented calibration of a sensing optical fiber

An interferometric measurement system includes a spun optical fiber including multiple optical waveguides configured in the fiber. Interferometric detection circuitry detects measurement interferometric pattern data associated with each of the multiple optical waveguides when the optical fiber is placed into a bend. Data processing circuitry determines compensation parameters that compensate for variations between an optimal configuration of the multiple optical waveguides in the fiber and an actual configuration of multiple optical waveguides in the fiber. The compensation parameters are stored in memory for compensating subsequently-obtained measurement interferometric pattern data for the fiber. The compensation parameters are applied to the subsequently-obtained measurement interferometric pattern data in order to distinguish between axial strain, bend strain, and twist strain on the fiber and to accurately determine one or more strain values for the fiber corresponding to one or more of the axial strain, bend strain, or twist strain on the fiber.

Compensating for non-ideal multi-core optical fiber structure

Growing community of inventors

Blacksburg, VA, United States of America

Sandra M Klute