公开(公告)号：US20220058828A1

公开(公告)日：2022-02-24

申请号：US17466583

申请日：2021-09-03

Applicant: Intel Corporation

Inventor： Zhongxuan LIU

IPC: G06T7/73 ,  G06T7/55 ,  G06F17/15 ,  G06F17/16 ,  G06N3/04 ,  G06N3/08 ,  G06T17/00

Abstract: Embodiments described herein provide a processing apparatus comprising compute logic to train a convolutional neural network (CNN) to perform autonomous re-localization for a service robot or mobile device. In one embodiment the apparatus comprises an image processor to process visual data received via a sensor and a general purpose graphics processing engine perform camera pose estimation for image data and generate a transformation matrix to transform positions of camera pose estimations to positions within a human readable map of the location. The images and transformed positions are uses to train the CNN to perform re-localization.

公开(公告)号：US20200082262A1

公开(公告)日：2020-03-12

申请号：US16468280

申请日：2016-12-21

Applicant: INTEL CORPORATION

Inventor： Zhongxuan LIU ,  Liwei MA

IPC: G06N3/08 ,  G06N3/04

Abstract: An apparatus for facilitating accurate camera re-localization in autonomous machines includes an image capturing device to capture an image of an object, selection/comparison logic to select a middle layer from a plurality of convolutional network (CNN) layers, processing/training logic to process superiority of one or more original keyframes of the image with one or more layer-based keyframes associated with the middle layer, and execution/outputting logic to output a first result based on the one or more original keyframes if one of the one or more original keyframes is superior than the one or more layer-based keyframes. A method, a machine-readable medium, a system, an apparatus, a computing device, and a communications device of the embodiments are also described.

公开(公告)号：US20210308863A1

公开(公告)日：2021-10-07

申请号：US17271779

申请日：2018-09-28

Applicant: Intel Corporation

Inventor： Zhongxuan LIU ,  Zhe WENG

IPC: B25J9/16

Abstract: Apparatus, systems, articles of manufacture, and methods for robot movement are disclosed. An example robot movement apparatus includes a sequence generator to generate a sequence of context variable vectors and policy variable vectors. The context variable vectors are related to a movement target, and the policy variable vectors are related to a movement trajectory. The example apparatus includes a calculator to calculate an upper policy and a loss function based on the sequence. The upper policy is indicative of a robot movement, and the loss function is indicative of a degree to which a movement target is met. The example apparatus also includes a comparator to determine if the loss function satisfies a threshold and an actuator to cause the robot to perform the robot movement of the upper policy when the loss function satisfies the threshold.

公开(公告)号：US20180293756A1

公开(公告)日：2018-10-11

申请号：US15567596

申请日：2016-11-18

Applicant: Intel Corporation

Inventor： Zhongxuan LIU ,  Liwei MA

IPC: G06T7/80 ,  G06K9/62 ,  G06T7/73 ,  G06T7/37 ,  G06N3/04 ,  G01P15/08

Abstract: Methods, apparatus, and system to obtain a pose from image regression in a trained convolutional neural network (“CNN”), to refine the CNN pose based on inertial measurements from an inertial measurement unit, and to infer a pose of a camera which took the image based on the refined CNN pose.