-
公开(公告)号:US20190321974A1
公开(公告)日:2019-10-24
申请号:US16455263
申请日:2019-06-27
Applicant: Intel Corporation
Inventor: Javier Felip Leon , David Israel Gonzalez Aguirre , Javier Sebastián Turek , Ignacio Javier Alvarez , Luis Carlos Maria Remis , Justin Gottschlich
IPC: B25J9/16
Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for object manipulation via action sequence optimization. An example method disclosed herein includes determining an initial state of a scene, generating a first action phase sequence to transform the initial state of the scene to a solution state of the scene by selecting a plurality of action phases based on action phase probabilities, determining whether a first simulated outcome of executing the first action phase sequence satisfies an acceptability criterion and, when the first simulated outcome does not satisfy the acceptability criterion, calculating a first cost function output based on a difference between the first simulated outcome and the solution state of the scene, the first cost function output utilized to generate updated action phase probabilities.
-
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.
-
公开(公告)号:US20190314984A1
公开(公告)日:2019-10-17
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.
-
公开(公告)号:US11213947B2
公开(公告)日:2022-01-04
申请号:US16455263
申请日:2019-06-27
Applicant: Intel Corporation
Inventor: Javier Felip Leon , David Israel Gonzalez Aguirre , Javier Sebastián Turek , Ignacio Javier Alvarez , Luis Carlos Maria Remis , Justin Gottschlich
IPC: B25J9/16
Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for object manipulation via action sequence optimization. An example method disclosed herein includes determining an initial state of a scene, generating a first action phase sequence to transform the initial state of the scene to a solution state of the scene by selecting a plurality of action phases based on action phase probabilities, determining whether a first simulated outcome of executing the first action phase sequence satisfies an acceptability criterion and, when the first simulated outcome does not satisfy the acceptability criterion, calculating a first cost function output based on a difference between the first simulated outcome and the solution state of the scene, the first cost function output utilized to generate updated action phase probabilities.
-
公开(公告)号:US20210157968A1
公开(公告)日:2021-05-27
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.
-
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.
-
公开(公告)号:US20220193895A1
公开(公告)日:2022-06-23
申请号:US17646689
申请日:2021-12-31
Applicant: Intel Corporation
Inventor: Javier Felip Leon , David Israel Gonzalez Aguirre , Javier Sebastián Turek , Ignacio Javier Alvarez , Luis Carlos Maria Remis , Justin Gottschlich
IPC: B25J9/16
Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for object manipulation via action sequence optimization. An example method disclosed herein includes determining an initial state of a scene, generating a first action phase sequence to transform the initial state of the scene to a solution state of the scene by selecting a plurality of action phases based on action phase probabilities, determining whether a first simulated outcome of executing the first action phase sequence satisfies an acceptability criterion and, when the first simulated outcome does not satisfy the acceptability criterion, calculating a first cost function output based on a difference between the first simulated outcome and the solution state of the scene, the first cost function output utilized to generate updated action phase probabilities.
-
公开(公告)号:US20190325108A1
公开(公告)日:2019-10-24
申请号:US16456825
申请日:2019-06-28
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
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.
-
-
-
-
-
-
-