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    GENERATING THREE DIMENSIONAL MODELS USING SINGLE TWO DIMENSIONAL IMAGES
    51.
    发明申请
    GENERATING THREE DIMENSIONAL MODELS USING SINGLE TWO DIMENSIONAL IMAGES 审中-公开

    公开(公告)号：US20180211438A1

    公开(公告)日：2018-07-26

    申请号：US15412853

    申请日：2017-01-23

    Applicant: Intel Corporation

    Inventor： David I. Gonzalez Aguirre ,  Javier Felip Leon ,  Ignacio J. Alvarez

    IPC: G06T15/20 ,  G06T17/10 ,  G06T17/20 ,  G06T15/04

    CPC classification number: G06T7/50 ,  G06T17/00

    Abstract: An example system for generating a three dimensional (3D) model includes a receiver to receive a single two dimensional (2D) image of an object to be modeled. The system includes a segment extractor to extract a binary segment, a textured segment, and a segment characterization based on the single 2D image. The system further includes a skeleton cue extractor to generate a medial-axis transform (MAT) approximation based on the binary segment and the segment characterization and extract a skeleton cue and a regression cue from the MAT approximation. The system also includes a contour generator to generate a contour based on the binary segment and the regression cue. The system can also further include a 3D model generator to generate a 3D model based on the contour and the skeleton cue.

    EDGE-BASED END DEVICE CONTROL USING ASYNCHRONOUS ADAPTIVE MOTION PRIMITIVES
    52.
    发明申请
    EDGE-BASED END DEVICE CONTROL USING ASYNCHRONOUS ADAPTIVE MOTION PRIMITIVES 有权

    公开(公告)号：US20250004820A1

    公开(公告)日：2025-01-02

    申请号：US18343376

    申请日：2023-06-28

    Applicant: Intel Corporation

    Inventor： David Gonzalez Aquirre ,  Rafael De La Guardia Gonzalez ,  Javier Felip Leon ,  Javier Perez-Ramirez ,  Julio Zamora Esquivel

    IPC: G06F9/46

    Abstract: A component of an edge server, 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: distribute, to a client device, tokens that enable its end device to execute respective asynchronous adaptive motion primitives (A2MPs) of a task graph of a task, wherein an A2MP is a motion primitive of encoded motion factoring in motion updates from the end device; receive A2MP task execution status messages during execution of the A2MPs; and dynamically update the distribution of the token or the task graph based on the A2MP task execution status messages to modify a trajectory of the end device.

    PROBABILISTIC AUTOCOMPLETE SYSTEM FOR ROBOT PROGRAMMING
    53.
    发明申请
    PROBABILISTIC AUTOCOMPLETE SYSTEM FOR ROBOT PROGRAMMING 有权

    公开(公告)号：US20250001605A1

    公开(公告)日：2025-01-02

    申请号：US18216187

    申请日：2023-06-29

    Applicant: Intel Corporation

    Inventor： Javier Felip Leon ,  David Gomez Gutierrez ,  Rafael De La Guardia Gonzalez ,  David Gonzalez Aguirre ,  Leobardo Campos Macias

    IPC: B25J9/16

    Abstract: Various aspects of techniques, systems, and use cases may be used for probabilistic automatic determination of an action for a robotic device. A technique may include identifying a current context of a robotic device, determining from the current context, a set of actions performable by the robotic device corresponding to at least one object, the set of actions including one or more affordances generated from a basic skills library for the robotic device, and automatically selecting an action of the set of actions based on an acyclic graph describing action paths. The technique may include outputting control signals that, when executed, cause the robotic device to perform the action to interact with the at least one object.

    OCCUPANCY MAPPING BASED ON GEOMETRIC ENTITIES WITH HIERARCHICAL RELATIONSHIPS
    57.
    发明公开
    OCCUPANCY MAPPING BASED ON GEOMETRIC ENTITIES WITH HIERARCHICAL RELATIONSHIPS 审中-公开

    公开(公告)号：US20230259665A1

    公开(公告)日：2023-08-17

    申请号：US18303782

    申请日：2023-04-20

    Applicant: Intel Corporation

    Inventor： Leobardo Campos Macias ,  Rafael De La Guardia Gonzalez ,  David Gonzalez Aguirre ,  Javier Felip Leon ,  Julio Cesar Zamora Esquivel

    IPC: G06F30/10 ,  G06F30/27

    CPC classification number: G06F30/10 ,  G06F30/27

    Abstract: A system can map occupancy of objects. The system may generate an occupancy representation of an object based on a point cloud of the object. The system may generate first geometric entities based on the point cloud. Each first geometric entity contains one or more points in the point cloud. The system may also generate one or more second geometric entities, each of which contains one or more first geometric entities. The occupancy representation of the object includes the one or more second geometric entities and the plurality of first geometric entities. The occupancy representation may have a hierarchical structure where the first geometric entities may be on a lower level than the one or more second geometric entities. The system can also detect collision of the object with another object by using the occupancy representation of the object and an occupancy representation of the other object.

    Automatic robot perception programming by imitation learning
    60.
    发明授权
    Automatic robot perception programming by imitation learning 有权

    公开(公告)号：US11577388B2

    公开(公告)日：2023-02-14

    申请号：US16455190

    申请日：2019-06-27

    Applicant: Intel Corporation

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

    IPC: B25J9/16

    Abstract: Apparatus, systems, methods, and articles of manufacture for automatic robot perception programming by imitation learning are disclosed. An example apparatus includes a percept mapper to identify a first percept and a second percept from data gathered from a demonstration of a task and an entropy encoder to calculate a first saliency of the first percept and a second saliency of the second percept. The example apparatus also includes a trajectory mapper to map a trajectory based on the first percept and the second percept, the first percept skewed based on the first saliency, the second percept skewed based on the second saliency. In addition, the example apparatus includes a probabilistic encoder to determine a plurality of variations of the trajectory and create a collection of trajectories including the trajectory and the variations of the trajectory. The example apparatus also includes an assemble network to imitate an action based on a first simulated signal from a first neural network of a first modality and a second simulated signal from a second neural network of a second modality, the action representative of a perceptual skill.

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