Sri International

Glenn Murray

Rakesh Kumar

Supun Samarasekera

Mikhail Sizintsev

Han-Pang Chiu

Girish Acharya

James R Carpenter

Michael John Wolverton

Zhiwei Zhu

Ryan Villamil

Vlad Branzoi

Massimiliano De Zambotti

Philip Miller

Fiona C Baker

Ian M Colrain

Alex Krasner

Abhinav Rajvanshi

Louise Yarnall

Supun Samarasekara

Xun Zhou

A method, apparatus and system for determining change in pose of a mobile device include determining from first ranging information received at a first and a second receiver on the mobile device from a stationary node during a first time instance, a distance from the stationary node to the first receiver and the second receiver, determining from second ranging information received at the first receiver and the second receiver from the stationary node during a second time instance, a distance from the stationary node to the first receiver and second receiver, and determining from the determined distances during the first time instance and the second time instance, how far and in which direction the first receiver and the second receiver moved between the first time instance and the second time instance to determine a change in pose of the mobile device, where a position of the stationary node is unknown.

Ranging-aided robot navigation using ranging nodes at unknown locations

During GPS-denied/restricted navigation, images proximate a platform device are captured using a camera, and corresponding motion measurements of the platform device are captured using an IMU device. Features of a current frame of the images captured are extracted. Extracted features are matched and feature information between consecutive frames is tracked. The extracted features are compared to previously stored, geo-referenced visual features from a plurality of platform devices. If one of the extracted features does not match a geo-referenced visual feature, a pose is determined for the platform device using IMU measurements propagated from a previous pose and relative motion information between consecutive frames, which is determined using the tracked feature information. If at least one of the extracted features matches a geo-referenced visual feature, a pose is determined for the platform device using location information associated with the matched, geo-referenced visual feature and relative motion information between consecutive frames.

Collaborative navigation and mapping

A computing system for virtual personal assistance includes technologies to, among other things, correlate an external representation of an object with a real world view of the object, display virtual elements on the external representation of the object and/or display virtual elements on the real world view of the object, to provide virtual personal assistance in a multi-step activity or another activity that involves the observation or handling of an object and a reference document.

Augmented reality virtual personal assistant for external representation

Biofeedback virtual reality sleep assistant technologies monitor one or more physiological parameters while presenting an immersive environment. The presentation of the immersive environment changes over time in response to changes in the values of the physiological parameters. The changes in the presentation of the immersive environment are configured using biofeedback technology and are designed to promote sleep.

Biofeedback virtual reality sleep assistant

Growing community of inventors

Jamison, PA, United States of America

Glenn Murray