公开(公告)号：US20190051158A1

公开(公告)日：2019-02-14

申请号：US15941515

申请日：2018-03-30

Applicant: Intel Corporation

Inventor： Javier Felip Leon ,  Omar Florez ,  David Gonzalez Aguirre ,  Glen J. Anderson

IPC: G08G1/01 ,  G08G1/00 ,  G05D1/00

Abstract: Various systems and methods for implementing intelligent traffic management for vehicle platoons are described herein. A road controller system includes A road controller system comprising: a data store to store an active traffic policy; a processor subsystem to: determine a speed or platoon size of a vehicle platoon traveling on an area controlled by the road controller system; and determine a change to the speed or platoon size of the vehicle platoon, the change based on the active traffic policy; and a transceiver to transmit a control message to the vehicle platoon to implement the change to the speed or platoon size of the vehicle platoon.

公开(公告)号：US20190051015A1

公开(公告)日：2019-02-14

申请号：US15869933

申请日：2018-01-12

Applicant: Intel Corporation

Inventor： David Gonzalez Aguirre ,  Omar Florez ,  Julio Zamora Esquivel ,  Mahesh Subedar ,  Javier Felip Leon ,  Rebecca Chierichetti ,  Andrea Johnson ,  Glen Anderson

IPC: G06T7/80 ,  G06T7/00 ,  G06T7/32

Abstract: In one example a management system for an autonomous vehicle, comprises a first image sensor to collect first image data in a first geographic region proximate the autonomous vehicle and a second image sensor to collect second image data in a second geographic region proximate the first geographic region and a controller communicatively coupled to the first image sensor and the second image sensor and comprising processing circuitry to collect the first image data from the first image sensor and second image data from the second image sensor, generate a first reliability index for the first image sensor and a second reliability index for the second image sensor, and determine a correlation between the first image data and the second image data. Other examples may be described.

公开(公告)号：US20250128560A1

公开(公告)日：2025-04-24

申请号：US19000963

申请日：2024-12-24

Applicant: Intel Corporation

Inventor： Javier Felix Rendon ,  Leobardo Campos Macias ,  Javier Felip Leon ,  David Gonzalez Aguirre ,  Julio Zamora Esquivel

IPC: B60G17/0165 ,  G01S17/08 ,  G01S17/931 ,  G05D1/65 ,  G05D109/10

Abstract: A transport system, including: a plurality of self-lifting wheel units individually controllable and mounted to a transport platform; one or more sensors mounted to the transport platform and configured to detect a floor obstacle, floor elevation change, or floor surface irregularity; a control system operatively connected to the plurality of self-lifting wheel units and the one or more sensors, wherein the control system is configured to: receive floor obstacle, elevation change, or surface irregularity detection data from the one or more sensors; plan and control the plurality of self-lifting wheel units to selectively lift or lower to maintain stability of the transport platform when traversing the floor obstacle, the floor elevation change, or the floor surface irregularity; and regulate movement of the transport platform to traverse the floor obstacle, the floor elevation change, or the floor surface irregularity based the plan and control.

公开(公告)号：US20250001597A1

公开(公告)日：2025-01-02

申请号：US18344526

申请日：2023-06-29

Applicant: Intel Corporation

Inventor： Javier Sebastian Turek ,  Leobardo Campos Macias ,  Javier Felip Leon

IPC: B25J9/16

Abstract: Techniques are disclosed for task error correction for robots, such as collaborative robots (cobots). A controller of a robot may include an error detector to detect an error in a performance of a human-robot collaborative task, and an error corrector to correct the detected error. The error corrector may include a correction planner and a facilitator. The correction planner may determine an error correction plan based on the detected error. The error correction plan may include corrective subtasks to control the cobot to correct the detected error. The facilitator may determine a facilitation plan based on the determined error correction plan. The facilitation plan including an assistance subtask configured to control the cobot to assist a human operator in correcting the detected error. The error corrector may generate a control signal to control the cobot based on the correction plan and the facilitation plan.

公开(公告)号：US20240326254A1

公开(公告)日：2024-10-03

申请号：US18127620

申请日：2023-03-28

Applicant: Intel Corporation

Inventor： Javier Felip Leon ,  Leobardo Campos Macias ,  David Gomez Gutierrez ,  Javier Turek ,  David Gonzalez Aguirre

IPC: B25J9/16 ,  G06V10/26 ,  H04N23/695

CPC classification number: B25J9/1697 ,  B25J9/1664 ,  G06V10/26 ,  H04N23/695

Abstract: Various aspects of techniques, systems, and use cases may be used for camera and end-effector planning for visual servoing for example in redundant manipulators. A technique may include generating a set of paths of an end effector of a robotic arm, and ranking the set of paths using an objective function that results in an improvement to a distance between the end effector and a target while maintaining a collision mitigation path for the end effector and minimizing occlusion of a camera affixed to a joint of the robotic arm. The technique may include converting a path of the set of paths into a trajectory based on the ranking, and outputting the trajectory for controlling the robotic arm to move the end effector.

公开(公告)号：US20240131704A1

公开(公告)日：2024-04-25

申请号：US18542305

申请日：2023-12-15

Applicant: Intel Corporation

Inventor： David Israel Gonzalez Aguirre ,  Javier Felip Leon ,  Javier Sebastian Turek ,  Javier Perez-Ramirez ,  Ignacio J. Alvarez

IPC: B25J9/16 ,  B25J19/02

CPC classification number: B25J9/1661 ,  B25J9/1612 ,  B25J19/023

Abstract: 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

公开(公告)号：US11921473B2

公开(公告)日：2024-03-05

申请号：US16456957

申请日：2019-06-28

Applicant: Intel Corporation

Inventor： Javier Felip Leon ,  Javier Sebastian Turek ,  David I. Gonzalez Aguirre ,  Ignacio Javier Alvarez ,  Luis Carlos Maria Remis ,  Justin Gottschlich

IPC: G05B13/02 ,  G05B13/04 ,  G06N3/086 ,  G06N3/088 ,  G06N20/00

CPC classification number: G05B13/027 ,  G05B13/04 ,  G06N3/086 ,  G06N3/088 ,  G06N20/00

Abstract: 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.

公开(公告)号：US20240025042A1

公开(公告)日：2024-01-25

申请号：US18478747

申请日：2023-09-29

Applicant: Intel Corporation

Inventor： David Gonzalez Aguirre ,  Leobardo Campos Macias ,  Rafael De La Guardia Gonzalez ,  Javier Felip Leon ,  David Gomez Gutierrez ,  Edgar Macias Garcia ,  Javier Turek ,  Julio Zamora Esquivel

IPC: B25J9/16

CPC classification number: B25J9/1664 ,  B25J9/163 ,  B25J9/1607 ,  B25J9/161

Abstract: A component of a robotic system, including: processor circuitry; and a non-transitory computer-readable storage medium including instructions that, when executed by the processor circuitry, cause the processor circuitry to: train a neuro-capability map plugin, which is a continuous or semi-continuous resolution neural network component encoded with kinematic capability attributes with respect to an action to be performed by a robot in a workspace; and publish the neuro-capability map plugin to a robotic skills repository where it is obtainable by robotic controller circuitry for embedding within a neural network usable perform one or more inferences to control the robot to perform the action.

公开(公告)号：US11472414B2

公开(公告)日：2022-10-18

申请号：US16830413

申请日：2020-03-26

Applicant: Intel Corporation

Inventor： David Israel González Aguirre ,  Ignacio Alvarez ,  Maria Soledad Elli ,  Javier Felip Leon ,  Javier Turek

IPC: B60W40/068 ,  B60W40/10 ,  B60W50/00 ,  G05D1/00

Abstract: 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.

公开(公告)号：US11386256B2

公开(公告)日：2022-07-12

申请号：US17107444

申请日：2020-11-30

Applicant: Intel Corporation

Inventor： Javier Sebastián Turek ,  Javier Felip Leon ,  Alexander Heinecke ,  Evangelos Georganas ,  Luis Carlos Maria Remis ,  Ignacio Javier Alvarez ,  David Israel Gonzalez Aguirre ,  Shengtian Zhou ,  Justin Gottschlich

IPC: G06F30/398 ,  G06N3/04 ,  G06N3/08

Abstract: Systems and methods for determining a configuration for a microarchitecture are described herein. An example system includes a proposal generator to generate a first candidate configuration of parameters for the microarchitecture, a machine learning model to process the first candidate configuration of parameters to output estimated performance indicators for the microarchitecture, an uncertainty checker to determine whether the estimated performance indicators are reliable, and a performance checker. In response to a determination that the estimated performance indicators are reliable, the performance checker is to determine whether the estimated performance indicators have improved toward a target. Further, if the estimated performance indicators have improved, the performance checker is to store the first candidate configuration of parameters in a memory as a potential solution for a microarchitecture without performing a full simulation on the first candidate configuration of parameters.