The Ohio State University

Tireaudit.com, Inc.

Alper Yilmaz

Jack Marshall Zoken

Edward W Martin

Charles L Hitchcock

Richard Denning

Tunc Aldemir

Enver Ozer

Stephen P Povoski

Ronald Xu

Ashish Gupta

Nima Ajam Gard

Ji Hyun Lee

Bing Zha

An object of initial unknown position on a map may be determined by traversing through moving and turning to establish motion trajectory to reduce its spatial uncertainty to a single location that would fit only to a certain map trajectory. An artificial neural network model learns from object motion on different map topologies may establish the object's end-to-end positioning from embedding map topologies and object motion. The proposed method includes learning potential motion patterns from the map and perform trajectory classification in the map's edge-space. Two different trajectory representations, namely angle representation and augmented angle representation (incorporates distance traversed) are considered and both a Graph Neural Network and an RNN are trained from the map for each representation to compare their performances. The results from the actual visual-inertial odometry have shown that the proposed approach is able to learn the map and localize the object based on its motion trajectories.

Systems, methods and devices for map-based object's localization deep learning and object's motion trajectories on geospatial maps using neural network

Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.

Systems and methods for real-time data processing and for emergency planning

An automated tread analysis system and methods for using are described. The automated tread analysis system may include a sensing system having a plurality of cameras providing a plurality of sequential two-dimensional images. The automated tread analysis system may also include an analysis system configured to provide at least one surface model of a first object via photogrammetry using the plurality of sequential two-dimensional images. The automated tread system may execute processing software reading data corresponding to the at least one surface model of the first object. The surface model may correspond to a current condition of the first object. The processing software executed by the user system may analyze the at least one surface model of the first object and provide at least one indicative wear metric based on the analysis of the surface model of the first object.

Mesh registration system and method for diagnosing tread wear

Systems and methods are described for performing navigation-assisted medical procedures such as biopsies, surgeries and pathology procedures by obtaining location information of an item of interest located within at least a portion of a subject; sensing position information of a moveable device; determining a relative position of the moveable device to the item of interest using the location information of the item of interest and the position information of the moveable device; and providing feedback based on the relative position of the moveable device to the item of interest that can be used to change the relative position of the moveable device to the item of interest.

Methods and systems for performing navigation-assisted medical procedures

An automated tread analysis system and methods for using are described. The automated tread analysis system may include a sensing system having a plurality of cameras providing a plurality of sequential two-dimensional images. The automated tread analysis system may also include an analyzing system configured to provide at least one surface model of a first object via photogrammetry using the plurality of sequential two-dimensional images. The automated tread system may execute processing software reading data corresponding to the at least one surface model of the first object. The surface model may correspond to a current condition of the first object. The processing software executed by the user system may analyze the at least one surface model of the first object and provide at least one indicative wear metric based on the analysis of the surface model of the first object.

According to the embodiments provided herein, a trajectory determination device for geo-localization can include one or more relative position sensors, one or more processors, and memory. The one or more processors can execute machine readable instructions to receive the relative position signals from the one or more relative position sensors. The relative position signals can be transformed into a sequence of relative trajectories. Each of the relative trajectories can include a distance and directional information indicative of a change in orientation of the trajectory determination device. A progressive topology can be created based upon the sequence of relative trajectories; this progressive topology can be compared to map data. A geolocation of the trajectory determination device can be determined.

Systems, methods, and devices for geo-localization

An automated tread registration system includes a sensing system configured to provide at least one surface model of a first object. The surface model of the first object has at least one pattern with at least one groove and at least one protrusion. The automated tread registration system also includes a user system executing processing software reading data corresponding to the at least one surface model of the first object. The surface model corresponds to a current condition of the first object. The processing software executed by the user system may analyze the at least one surface model of the first object and provide at least one indicative metric based on the analysis of the surface model. The indicative metric may be camber wear, toe wear, heel toe wear, overinflation, underinflation, and/or the like.

Disclosed is a system and method for documenting and analyzing a tire tread using a guidance dolly for use in creating a three-dimensional image file of a target object from a plurality of two-dimensional image files including: a first dolly surface adapted to enable placement of the guidance dolly into physical contact with the target object; a second dolly surface generally conforming to the shape of the first dolly surface; and a guide channel for guiding a digital imaging device along a specified path so as to acquire the plurality of two-dimensional image files of the target object.

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Lewis Center, OH, United States of America

Alper Yilmaz