公开(公告)号：US20210283785A1

公开(公告)日：2021-09-16

申请号：US16926289

申请日：2020-07-10

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Yuan CHEN ,  Colin PREPSCIUS ,  Dae Won LEE ,  Ibrahim Volkan ISLER ,  Daniel Dongyuel LEE

IPC: B25J13/08 ,  B25J9/16 ,  B25J15/08

Abstract: A tool control system may include: a tactile sensor configured to, when a tool holds a target object and slides the target object downward across the tool, obtain tactile sensing data from the tool; one or more memories configured to store a target velocity and computer-readable instructions; and one or more processors configured execute the computer-readable instructions to: receive the tactile sensing data from the tactile sensor; estimate a velocity of the target object based on the tactile sensing data, by using one or more neural networks that are trained based on a training image of an sample object captured while the sample object is sliding down; and generate a control parameter of the tool based on the estimated velocity and the target velocity.

公开(公告)号：US20230136306A1

公开(公告)日：2023-05-04

申请号：US17978873

申请日：2022-11-01

Applicant: SAMSUNG ELECTRONICS CO., LTD. ,  The Trustees of the University of Pennsylvania

Inventor： Ziyun WANG ,  Fernando Cladera OJEDA ,  Anthony Robert BISULCO ,  Dae Won LEE ,  Camillo J. TAYLOR ,  Konstantinos DANIILIDIS ,  Ani HSIEH ,  Ibrahim Volkan ISLER

IPC: G06T7/20 ,  G06V10/82 ,  G06V20/40 ,  A63B65/12

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.

公开(公告)号：US20210293918A1

公开(公告)日：2021-09-23

申请号：US17084257

申请日：2020-10-29

Applicant: Samsung Electronics Co., Ltd.

Inventor： Xiaoran FAN ,  Yuan CHEN ,  Dae Won LEE ,  Colin PREPSCIUS ,  Ibrahim Volkan ISLER ,  Lawrence David JACKEL ,  Hyunjune Sebastian SEUNG ,  Daniel Dongyuel LEE

IPC: G01S5/22 ,  B25J19/02

Abstract: A method of collision localization on a robotic device includes obtaining audio signals from a plurality of acoustic sensors spaced apart along the robotic device; identifying, based on a collision being detected, a strongest audio signal; identifying a primary onset time for an acoustic sensor producing the strongest audio signal, the primary onset time being a time at which waves propagating from the collision reach the acoustic sensor producing the strongest audio signal; generating a virtual onset time set, by shifting a calibration manifold, based on the identified primary onset time, the calibration manifold representing relative onset times from evenly spaced marker locations on the robotic device to the plurality of acoustic sensors; determining scores for the marker locations based a standard deviation of elements in the virtual onset time set; and estimating a location of the collision based on a highest score of the determined scores.