Intel Corporation

Mobileye Vision Technologies Ltd.

Javier Felip Leon

David Israel Gonzalez Aguirre

Ignacio Javier Alvarez

Javier Sebastian Turek

Maria Soledad Elli

Luis Carlos Maria Remis

Justin E Gottschlich

Javier Perez-Ramirez

Marcos Emanuel Carranza

David Gomez Gutierrez

Cesar Martinez-Spessot

Mateo Guzman

Mariano Tepper

Nilesh Amar Ahuja

Dario Oliver

Leobardo E Campos Macias

Ranganath Krishnan

Julio Zamora Esquivel

Javier Sebastián Turek

Glen J Anderson

Alexander F Heinecke

Omesh Tickoo

Julio Cesar Zamora Esquivel

Rafael De La Guardia Gonzalez

David Arditti Ilitzky

Mahesh M Subedar

Shengtian Zhou

Evangelos Georganas

Ibrahima J Ndiour

Patrick Mead

Vy Vo

Omar Florez

David Israel González Aguirre

Francesc Guim Bernat

Kshitij Arun Doshi

Rita H Wouhaybi

Satish Chandra Jha

Dave A Cavalcanti

S M Iftekharul Alam

Jose Rodrigo Camacho Perez

Paulo Lopez Meyer

Hector A Cordourier Maruri

Sridhar G Sharma

Li Chen

Mikhail T Galeev

Rebecca Chierichetti

Todd A Anderson

Sindhu Pandian

Jesus Cruz Vargas

Andrea E Johnson

Parual Datta

Lakshmi N Talluru

Rufeng Meng

Leobardo Campos Macias

Naveen Aerrabotu

David I Gonzalez-Aguirre

Razia Shaik

Nilesh Ahuja

A device may determine a plurality of link settings for a communication link within a time sensitive network. The device may determine a threshold value for the communication link based on the plurality of link settings. The device may determine a current value of a parameter of the communication link based on the plurality of link settings. The device may compare the current value of the parameter to a threshold value. Responsive to the current value of the parameter being less than the threshold value, the device may successively update a link setting of the plurality of link settings to cause the current value of the parameter to approach the threshold value.

Dynamic adaptation of time-aware communications in time-sensitive systems

Various aspects of techniques, systems, and use cases for robot movement within human-robot collaboration (HRC) areas are disclosed. Convex free-space regions around points of interest in the HRC are detected and updated using one or more sensors. Collision-free motion plans for robots use a Hierarchical Convex Polytope (HCP) region in which the robot is removed from the occupied space in the scene using depth cameras.

Hierarchical polytope workspace mapping for human-robot collaboration

Methods, apparatus, systems and articles of manufacture are disclosed to facilitate knowledge sharing among neural networks. An example apparatus includes a trainer to train, at a first computing system, a first Bayesian Neural Network (BNN) on a first subset of training data to generate a first weight distribution, and train, at a second computing system, a second BNN on a second subset of the training data to generate a second weight distribution, the second subset of the training data different from the first subset of training data. The example apparatus includes a knowledge sharing controller to generate a third BNN based on the first weight distribution and the second weight distribution.

Methods and apparatus to facilitate efficient knowledge sharing among neural networks

Various aspects of techniques, systems, and use cases may be used for operating, controlling, programming, or configuring an energy efficient robotic arm. An example technique may include identifying a planned trajectory for a robotic arm, selecting a candidate joint of the robotic arm to lock, and recomputing the planned trajectory to determine a joint-locked trajectory while the candidate joint is locked. The example technique may include outputting a control signal to lock the candidate joint and causing the robotic arm to use the joint-locked trajectory.

Energy efficient robotic arm

A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

Safety system for a vehicle

Various systems and methods for implementing an enhanced occupant collision safety system in a vehicle are described herein. A system for controlling deployment of vehicle safety mechanisms of a host vehicle, includes a sensor array interface to receive acceleration data from an impact sensor; an image processor to receive events from an event camera, the event camera configured to monitor a scene of an interior of the host vehicle that includes an occupant; and an occupant safety system controller to: cluster the events to discriminate between events associated with a background of the scene and events associated with a body part of the occupant; detect a collision based on the acceleration data; verify the collision based on the events associated with the background of the scene; and in response to verifying the collision, cause a collision safety mechanism of the host vehicle to deploy.

Enhanced occupant collision safety system

A localization system includes a first sensor, configured to detect a vibration and generate a first electrical signal in response to the detection of the vibration; a second sensor, configured to detect a vibration and generate a second electrical signal in response to the detection of the vibration; a third sensor, configured to detect a vibration and generate a third electrical signal in response to the detection of the vibration; and

Localization system and method

Estimating a head pose may include obtaining sensor data corresponding to a head and at least a portion of the body of a human subject and determining an estimate of a three-dimensional (3D) body pose using the obtained sensor data. The estimation can further include generating a first rendering of at least the human subject's head using the obtained sensor data and generating a plurality of head pose sample data sets by applying the estimated 3D body pose to a head-pose generative model. Further, the head pose estimation can include generating a plurality of second renderings respectively from each of the plurality of head pose sample data sets; determining which of the plurality of second renderings is closest to the first rendering; and selecting the second rendering determined to be closest to the first rendering.

Systems, methods, and devices for head pose determination

Disclosed herein are systems and methods for privacy-preserving facemask-compliance-level measurement. In an embodiment, a mask-compliance measurement system includes a processor that is configured to generate, from an image of a person, a facial depth image of a region of a face of the person, and to generate facial wavelet descriptors from the facial depth image. The processor is also configured to determine spectral-density values of the wavelet descriptors, and to analyze the spectral-density values to generate a mask-wearing-compliance result for the person. In an embodiment, the analyzing includes using a classification model that is trained to classify sets of spectral-density values with respect to facemask wearing in images from which the spectral-density values were derived.

Systems and methods for privacy-preserving facemask-compliance-level measurement

Disclosed herein are systems and methods for vehicle-occupancy-based and user-preference-based smart routing, and autonomous volumetric-occupancy measurement. In an embodiment, a system is configured to receive from a user device associated with a user, a routing-options request for routing options between two locations, and to responsively identify one or more routing options between the two locations based at least in part on occupancy data for a vehicle that would be utilized for at least a portion of at least one of the identified routing options. The occupancy data is based on an output of an automated occupancy-measurement system onboard the vehicle. The system is also configured to provide the one or more identified routing options to the user device. In some embodiments, the occupancy data is obtained using volumetric-occupancy measurement. Some embodiments relate to volumetric-occupancy measurement conducted by autonomous mesh nodes.

Systems and methods for vehicle-occupancy-based and user-preference-based smart routing and autonomous volumetric-occupancy measurement

A robotic manipulation planning system, including at least one processor; and a non-transitory computer-readable storage medium including instructions that, when executed by the at least one processor, cause the at least one processor to: process perception data to detect known, familiar, and unknown objects to generate manipulation candidates; filter manipulation candidates against constraints to reduce the manipulation candidates; and determine quality metrics for the reduced manipulation candidates using a soft-body simulation technique.

Robotic manipulation planning based on probalistic elastoplastic deformation material point method

Methods, apparatus, systems and articles of manufacture for providing query selection systems are disclosed. An example query selection system includes a processor to: analyze a graph database; identify respective ones of objects associated with the graph database; obtain properties associated with the objects; identify common properties present in the respective ones of the objects; in response to determining the common properties present in the identified objects, output a list of the common properties corresponding to the respective ones of the objects; generate a table for the common properties and the respective ones of the objects; and populate the table with the common properties and the respective ones of the objects from the graph database to establish a relational database. The system further includes a machine learning model classifier to enable relational database query searching via the relational database.

Methods, apparatus, systems and articles of manufacture for providing query selection systems

A vehicle control system (VCS) for a vehicle may include an in-vehicle bus and an intrusion detection system (IDS). The IDS may: calculate a planned output of the vehicle based on a message of a message stream received from at least one electronic control unit (ECU) coupled to the in-vehicle bus, calculate a reachable set based on an uncertainty metric, and identify an intrusion of the VCS based on a comparison of the planned output and the reachable set.

Systems and methods for intrusion detection in vehicle systems

Apparatuses, methods and storage medium associated with compensating for a sensor deficiency in a heterogeneous sensor array are disclosed herein. In embodiments, an apparatus may include a compute device to aggregate perception data from individual perception pipelines, each of which is associated with respective one of different types of sensors of a heterogeneous sensor set, to identify a characteristic associated with a space to be monitored by the heterogeneous sensor set; detect a sensor deficiency associated with a first sensor of the sensors; and in response to a detection of the sensor deficiency, derive next perception data for more than one of the individual perception pipelines from sensor data originating from at least one second sensor of the sensors. Other embodiments may be disclosed or claimed.

Compensating for a sensor deficiency in a heterogeneous sensor array

Apparatus, systems, articles of manufacture, and methods to generate acceptability criteria for autonomous systems plans are disclosed. An example apparatus includes a data compiler to compile data generated by the autonomous system into an autonomous system task dataset, a data encoder to encode the dataset for input into a rule distillation neural network architecture, a model trainer to train the rule distillation neural network architecture, an adaptor to adapt the trained rule distillation neural network architecture to a new input data domain using the autonomous system task dataset, a verifier to generate formally verified acceptability criteria, and an inferer to evaluate a control command, the evaluation resulting in an acceptance or rejection of the command.

Methods and apparatus to generate acceptability criteria for autonomous systems plans

Growing community of inventors

Hillsboro, OR, United States of America

Javier Felip Leon