公开(公告)号：US20190266418A1

公开(公告)日：2019-08-29

申请号：US16286329

申请日：2019-02-26

Applicant: NVIDIA Corporation

Inventor： Yifang Xu ,  Xin Liu ,  Chia-Chih Chen ,  Carolina Parada ,  Davide Onofrio ,  Minwoo Park ,  Mehdi Sajjadi Mohammadabadi ,  Vijay Chintalapudi ,  Ozan Tonkal ,  John Zedlewski ,  Pekka Janis ,  Jan Nikolaus Fritsch ,  Gordon Grigor ,  Zuoguan Wang ,  I-Kuei Chen ,  Miguel Sainz

IPC: G06K9/00 ,  G06K9/32 ,  G05D1/02 ,  G05D1/00 ,  G06N3/08 ,  G06T7/10

Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.

公开(公告)号：US20140368505A1

公开(公告)日：2014-12-18

申请号：US13917406

申请日：2013-06-13

Applicant: Nvidia Corporation

Inventor： Louis Bavoil ,  Miguel Sainz ,  Byungmoon Kim

IPC: G06T15/80

CPC classification number: G06T15/005

Abstract: A graphics processing subsystem for recovering projection parameters for rendering effects and a method of use thereof. One embodiment of the graphics processing subsystem includes: (1) a memory configured to store a buffer having a plurality of constants determinable upon execution of an application for which a scene is rendered, and (2) a central processing unit (CPU) operable to determine projection parameters from the buffer according to shader-reflection metadata attached to a programmable shader submitted for execution, and employ the projection parameters to cause an effect to be rendered on the scene by a graphics processing unit (GPU).

Abstract translation: 用于恢复渲染效果的投影参数的图形处理子系统及其使用方法。 图形处理子系统的一个实施例包括：（1）存储器，被配置为存储具有在执行场景被渲染的应用程序时可确定的多个常数的缓冲器，以及（2）可操作以 根据附加到可执行的可编程着色器的着色反射元数据，从缓冲器确定投影参数，并且使用投影参数来使图形处理单元（GPU）在场景上呈现效果。

公开(公告)号：US12266148B2

公开(公告)日：2025-04-01

申请号：US18309882

申请日：2023-05-01

Applicant: NVIDIA Corporation

Inventor： Yifang Xu ,  Xin Liu ,  Chia-Chih Chen ,  Carolina Parada ,  Davide Onofrio ,  Minwoo Park ,  Mehdi Sajjadi Mohammadabadi ,  Vijay Chintalapudi ,  Ozan Tonkal ,  John Zedlewski ,  Pekka Janis ,  Jan Nikolaus Fritsch ,  Gordon Grigor ,  Zuoguan Wang ,  I-Kuei Chen ,  Miguel Sainz

IPC: G06V10/44 ,  G05D1/00 ,  G06F18/2413 ,  G06N3/084 ,  G06T7/10 ,  G06V10/46 ,  G06V10/764 ,  G06V10/82 ,  G06V20/40 ,  G06V20/56

Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.

公开(公告)号：US20230267701A1

公开(公告)日：2023-08-24

申请号：US18309882

申请日：2023-05-01

Applicant: NVIDIA Corporation

Inventor： Yifang Xu ,  Xin Liu ,  Chia-Chin Chen ,  Carolina Parada ,  Davide Onofrio ,  Minwoo Park ,  Mehdi Sajjadi Mohammadabadi ,  Vijay Chintalapudi ,  Ozan Tonkal ,  John Zedlewski ,  Pekka Janis ,  Jan Nikolaus Fritsch ,  Gordon Grigor ,  Zuoguan Wang ,  I-Kuei Chen ,  Miguel Sainz

IPC: G06V10/44 ,  G06T7/10 ,  G05D1/00 ,  G06N3/084 ,  G05D1/02 ,  G06V20/56 ,  G06V10/46 ,  G06V20/40 ,  G06F18/2413 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V10/44 ,  G06T7/10 ,  G05D1/0088 ,  G06N3/084 ,  G05D1/0221 ,  G06V20/588 ,  G06V10/46 ,  G06V10/457 ,  G06V20/41 ,  G06F18/24143 ,  G06V10/764 ,  G06V10/82 ,  G06V10/471

Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.

公开(公告)号：US11474519B2

公开(公告)日：2022-10-18

申请号：US16286330

申请日：2019-02-26

Applicant: NVIDIA Corporation

Inventor： Gary Hicok ,  Michael Cox ,  Miguel Sainz ,  Martin Hempel ,  Ratin Kumar ,  Timo Roman ,  Gordon Grigor ,  David Nister ,  Justin Ebert ,  Chin Shih ,  Tony Tam ,  Ruchi Bhargava

IPC: G05D1/00 ,  G06Q50/30 ,  G05B13/02 ,  G05D1/02 ,  G06Q10/02

Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.

公开(公告)号：US20140160124A1

公开(公告)日：2014-06-12

申请号：US13712797

申请日：2012-12-12

Applicant: NVIDIA CORPORATION

Inventor： Louis Bavoil ,  Miguel Sainz

IPC: G06T17/10

CPC classification number: G06T15/06 ,  G06T15/506

Abstract: A visible polygon data structure and method of use thereof. One embodiment of the visible polygon data structure includes: (1) a memory configured to store a data structure containing vertices of at least partially visible polygons of the scene but lacking vertices of at least some wholly invisible polygons of the scene, and (2) a graphics processing unit (GPU) configured to employ the vertices of the at least partially visible polygons to approximate an ambient occlusive effect on a point in the scene, the effect being independent of the wholly invisible polygons.

Abstract translation: 可见多边形数据结构及其使用方法。 可见多边形数据结构的一个实施例包括：（1）存储器，其被配置为存储包含场景的至少部分可见多边形的顶点但缺少场景的至少一些完全不可见的多边形的顶点的数据结构，以及（2） 被配置为使用所述至少部分可见多边形的顶点的图形处理单元（GPU）来近似场景中的点上的环境闭塞效应，该效果独立于完全不可见的多边形。

公开(公告)号：US20250139934A1

公开(公告)日：2025-05-01

申请号：US19005672

申请日：2024-12-30

Applicant: NVIDIA Corporation

Inventor： Yifang Xu ,  Xin Liu ,  Chia-Chih Chen ,  Carolina Parada ,  Davide Onofrio ,  Minwoo Park ,  Mehdi Sajjadi Mohammadabadi ,  Vijay Chintalapudi ,  Ozan Tonkal ,  John Zedlewski ,  Pekka Janis ,  Jan Nikolaus Fritsch ,  Gordon Grigor ,  Zuoguan Wang ,  I-Kuei Chen ,  Miguel Sainz

IPC: G06V10/44 ,  G06F18/2413 ,  G06N3/084 ,  G06T7/10 ,  G06V10/46 ,  G06V10/764 ,  G06V10/82 ,  G06V20/40 ,  G06V20/56

Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.

公开(公告)号：US11874663B2

公开(公告)日：2024-01-16

申请号：US17896825

申请日：2022-08-26

Applicant: NVIDIA Corporation

Inventor： Gary Hicok ,  Michael Cox ,  Miguel Sainz ,  Martin Hempel ,  Ratin Kumar ,  Timo Roman ,  Gordon Grigor ,  David Nister ,  Justin Ebert ,  Chin-Hsien Shih ,  Tony Tam ,  Ruchi Bhargava

IPC: G05D1/00 ,  G06Q50/30 ,  G05B13/02 ,  G05D1/02 ,  G06Q10/02

CPC classification number: G05D1/0088 ,  G05B13/027 ,  G05D1/0055 ,  G05D1/0242 ,  G05D1/0246 ,  G05D1/0257 ,  G06Q10/02 ,  G06Q50/30 ,  G05D2201/0213

Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.

公开(公告)号：US11676364B2

公开(公告)日：2023-06-13

申请号：US17222680

申请日：2021-04-05

Applicant: NVIDIA Corporation

Inventor： Yifang Xu ,  Xin Liu ,  Chia-Chih Chen ,  Carolina Parada ,  Davide Onofrio ,  Minwoo Park ,  Mehdi Sajjadi Mohammadabadi ,  Vijay Chintalapudi ,  Ozan Tonkal ,  John Zedlewski ,  Pekka Janis ,  Jan Nikolaus Fritsch ,  Gordon Grigor ,  Zuoguan Wang ,  I-Kuei Chen ,  Miguel Sainz

IPC: G06V10/44 ,  G06T7/10 ,  G05D1/00 ,  G06N3/084 ,  G05D1/02 ,  G06V20/56 ,  G06V10/46 ,  G06V20/40 ,  G06F18/2413 ,  G06V10/764 ,  G06V10/82

CPC classification number: G06V10/44 ,  G05D1/0088 ,  G05D1/0221 ,  G06F18/24143 ,  G06N3/084 ,  G06T7/10 ,  G06V10/457 ,  G06V10/46 ,  G06V10/764 ,  G06V10/82 ,  G06V20/41 ,  G06V20/588 ,  G06V10/471

Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.

公开(公告)号：US20210224556A1

公开(公告)日：2021-07-22

申请号：US17222680

申请日：2021-04-05

Applicant: NVIDIA Corporation

Inventor： Yifang Xu ,  Xin Liu ,  Chia-Chih Chen ,  Carolina Parada ,  Davide Onofrio ,  Minwoo Park ,  Mehdi Sajjadi Mohammadabadi ,  Vijay Chintalapudi ,  Ozan Tonkal ,  John Zedlewski ,  Pekka Janis ,  Jan Nikolaus Fritsch ,  Gordon Grigor ,  Zuoguan Wang ,  I-Kuei Chen ,  Miguel Sainz

IPC: G06K9/00 ,  G06K9/32 ,  G06T7/10 ,  G05D1/00 ,  G06N3/08 ,  G05D1/02 ,  G06K9/46 ,  G06K9/48 ,  G06K9/62

Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.