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

Mateo Guzman

Cesar Martinez-Spessot

Mariano Tepper

Nilesh Amar Ahuja

Dario Oliver

David Gomez Gutierrez

Leobardo E Campos Macias

Javier Sebastián Turek

Glen J Anderson

Alexander F Heinecke

Omesh Tickoo

Julio Cesar Zamora Esquivel

David Arditti Ilitzky

Mahesh M Subedar

Shengtian Zhou

Evangelos Georganas

Ibrahima J Ndiour

Ranganath Krishnan

Patrick Mead

Vy Vo

Omar Florez

Julio Zamora Esquivel

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

Jesus Cruz Vargas

Sindhu Pandian

Andrea E Johnson

Lakshmi N Talluru

Parual Datta

Rufeng Meng

David Israel González Aguirre

Naveen Aerrabotu

David I Gonzalez-Aguirre

Razia Shaik

Nilesh Ahuja

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

Systems, apparatuses and methods may provide for controlling one or more end effectors by generating a semantic labelled image based on image data, wherein the semantic labelled image is to identify a shape of an object and a semantic label of the object, associating a first set of actions with the object, and generating a plan based on an intersection of the first set of actions and a second set of actions to satisfy a command from a user through actuation of one or more end effectors, wherein the second set of actions are to be associated with the command.

Affordance-aware, multi-resolution, free-form object manipulation planning

Methods, apparatus, systems and articles of manufacture are disclosed to improve spatial-temporal data management. An example apparatus includes a hypervoxel data structure generator to generate a root hexatree data structure having sixteen hypernodes, an octree manager to improve a spatiotemporal data access efficiency by generating a first degree of symmetry in the root hexatree, the octree manager to assign a first portion of the hypernodes to a positive temporal subspace and to assign a second portion of the hypernodes to a negative temporal subspace, and a quadtree manager to improve the spatiotemporal data access efficiency by generating a second degree of symmetry in the root hexatree, the quadtree manager to assign respective hypernodes of the positive temporal subspace and the negative temporal subspace to respective positive and negative spatial subspaces.

Methods, systems and apparatus to improve spatial-temporal data management

Systems, apparatuses and methods may provide for technology that identifies a cognitive space that is to be a compressed representation of activations of a neural network, maps a plurality of activations of the neural network to a cognitive initial point and a cognitive destination point in the cognitive space and generates a first cognitive trajectory through the cognitive space, wherein the first cognitive trajectory traverses the cognitive space from the cognitive initial point to the cognitive destination point.

Neural network verification based on cognitive trajectories

Growing community of inventors

Hillsboro, OR, United States of America

Javier Felip Leon