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Patent Agency Ranking
公开(公告)号：US20210402602A1
公开(公告)日：2021-12-30
申请号：US17117718
申请日：2020-12-10
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jinwook Huh , Galen Kailun Xing , Ziyun Wang , Ibrahim Volkan Isler , Daniel Dongyuel Lee
Abstract: A method for generating a trajectory of a robot from a first configuration to a second configuration within an environment while steering away from obstacles may include obtaining physical workspace information associated with the environment in which the robot is configured to operate; obtaining, using a first neural network, a set of weights of a second neural network that is configured to generate a set of values associated with a set of configurations of the robot with respect to the second configuration; obtaining, by applying the set of weights to the second neural network, the set of values associated with the set of configurations of the robot with respect to the second configuration; and generating the trajectory of the robot from the first configuration to the second configuration within the environment, based on the set of values.
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公开(公告)号：US12299899B2
公开(公告)日：2025-05-13
申请号：US17978873
申请日：2022-11-01
Inventor： Ziyun Wang , Fernando Cladera Ojeda , Anthony Robert Bisulco , Dae Won Lee , Camillo J. Taylor , Konstantinos Daniilidis , Ani Hsieh , Ibrahim Volkan Isler
Abstract: Provided is a method for predicting a location of a fast-moving object. The method includes receiving event information from an event camera, the event information corresponding to an event detected by the event camera, generating a Binary Event History Image (BEHI) based on the event information, providing the BEHI as an input to an event-based neural network, obtaining, as an output of the event-based neural network, a first predicted location of the fast-moving object, a normal distribution indicating prediction uncertainty of the predicted location, and a predicted time-to-collision (TTC). The method further includes estimating a second predicted location of the fast-moving object based on the first predicted location, the normal distribution, and the predicted TTC output by the event-based neural network, and actuating a mechanical catching device to be at the second predicted location.
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公开(公告)号：US11642787B2
公开(公告)日：2023-05-09
申请号：US17117718
申请日：2020-12-10
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jinwook Huh , Galen Kailun Xing , Ziyun Wang , Ibrahim Volkan Isler , Daniel Dongyuel Lee
CPC classification number: B25J9/1666 , B25J9/161 , B25J9/163 , G01C21/3446 , G05D1/0221 , G05D1/0251 , G05B2219/33028 , G05B2219/40455 , G05B2219/40506
Abstract: A method for generating a trajectory of a robot from a first configuration to a second configuration within an environment while steering away from obstacles may include obtaining physical workspace information associated with the environment in which the robot is configured to operate; obtaining, using a first neural network, a set of weights of a second neural network that is configured to generate a set of values associated with a set of configurations of the robot with respect to the second configuration; obtaining, by applying the set of weights to the second neural network, the set of values associated with the set of configurations of the robot with respect to the second configuration; and generating the trajectory of the robot from the first configuration to the second configuration within the environment, based on the set of values.
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公开(公告)号：US11380061B2
公开(公告)日：2022-07-05
申请号：US17177896
申请日：2021-02-17
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Ziyun Wang , Eric Anthony Mitchell , Ibrahim Volkan Isler , Daniel Dongyuel Lee
Abstract: An apparatus for reconstructing a 3D object, includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain, using a first neural network, mapping function weights of a mapping function of a second neural network, based on an image feature vector corresponding to a 2D image of the 3D object, set the mapping function of the second neural network, using the obtained mapping function weights, and based on sampled points of a canonical sampling domain, obtain, using the second neural network of which the mapping function is set, 3D point coordinates and geodesic lifting coordinates of each of the sampled points in the 3D object corresponding to the 2D image, wherein the 3D point coordinates are first three dimensions of an embedding vector of a respective one of the sampled points, and the geodesic lifting coordinates are remaining dimensions of the embedding vector.
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公开(公告)号：US20210390776A1
公开(公告)日：2021-12-16
申请号：US17177896
申请日：2021-02-17
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Ziyun Wang , Eric Anthony Mitchell , Ibrahim Volkan Isler , Daniel Dongyuel Lee
Abstract: An apparatus for reconstructing a 3D object, includes a memory storing instructions, and at least one processor configured to execute the instructions to obtain, using a first neural network, mapping function weights of a mapping function of a second neural network, based on an image feature vector corresponding to a 2D image of the 3D object, set the mapping function of the second neural network, using the obtained mapping function weights, and based on sampled points of a canonical sampling domain, obtain, using the second neural network of which the mapping function is set, 3D point coordinates and geodesic lifting coordinates of each of the sampled points in the 3D object corresponding to the 2D image, wherein the 3D point coordinates are first three dimensions of an embedding vector of a respective one of the sampled points, and the geodesic lifting coordinates are remaining dimensions of the embedding vector.
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