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公开(公告)号：US20230366698A1
公开(公告)日：2023-11-16
申请号：US18352578
申请日：2023-07-14
Applicant: NVIDIA Corporation
Inventor： David Nister , Ruchi Bhargava , Vaibhav Thukral , Michael Grabner , Ibrahim Eden , Jeffrey Liu
CPC classification number: G01C21/3841 , G01C21/3896 , G01C21/3878 , G01C21/1652 , G01C21/3867 , G06N3/02 , G01C21/3811
Abstract: An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.
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公开(公告)号：US11803192B2
公开(公告)日：2023-10-31
申请号：US17900622
申请日：2022-08-31
Applicant: NVIDIA Corporation
Inventor： Michael Grabner , Jeremy Furtek , David Nister
CPC classification number: G05D1/0253 , G05D1/0251 , G06T7/246 , G06T7/285 , G06T7/35 , G06T2207/10021 , G06T2207/10028 , G06T2207/30252
Abstract: Systems and methods for performing visual odometry more rapidly. Pairs of representations from sensor data (such as images from one or more cameras) are selected, and features common to both representations of the pair are identified. Portions of bundle adjustment matrices that correspond to the pair are updated using the common features. These updates are maintained in register memory until all portions of the matrices that correspond to the pair are updated. By selecting only common features of one particular pair of representations, updated matrix values may be kept in registers. Accordingly, matrix updates for each common feature may be collectively saved with a single write of the registers to other memory. In this manner, fewer write operations are performed from register memory to other memory, thus reducing the time required to update bundle adjustment matrices and thus speeding the bundle adjustment process.
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公开(公告)号：US11657532B2
公开(公告)日：2023-05-23
申请号：US17103680
申请日：2020-11-24
Applicant: NVIDIA Corporation
Inventor： Minwoo Park , Yue Wu , Michael Grabner , Cheng-Chieh Yang
CPC classification number: G06T7/60 , G06T7/579 , G06V20/588 , G06T2200/08 , G06T2207/10028 , G06T2207/30256
Abstract: In various examples, surface profile estimation and bump detection may be performed based on a three-dimensional (3D) point cloud. The 3D point cloud may be filtered in view of a portion of an environment including drivable free-space, and within a threshold height to factor out other objects or obstacles other than a driving surface and protuberances thereon. The 3D point cloud may be analyzed—e.g., using a sliding window of bounding shapes along a longitudinal or other heading direction—to determine one-dimensional (1D) signal profiles corresponding to heights along the driving surface. The profile itself may be used by a vehicle—e.g., an autonomous or semi-autonomous vehicle—to help in navigating the environment, and/or the profile may be used to detect bumps, humps, and/or other protuberances along the driving surface, in addition to a location, orientation, and geometry thereof.
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公开(公告)号：US20230357076A1
公开(公告)日：2023-11-09
申请号：US18311172
申请日：2023-05-02
Applicant: NVIDIA Corporation
Inventor： Michael Kroepfl , Amir Akbarzadeh , Ruchi Bhargava , Viabhav Thukral , Neda Cvijetic , Vadim Cugunovs , David Nister , Birgit Henke , Ibrahim Eden , Youding Zhu , Michael Grabner , Ivana Stojanovic , Yu Sheng , Jeffrey Liu , Enliang Zheng , Jordan Marr , Andrew Carley
IPC: C03C17/36
CPC classification number: C03C17/3607 , C03C17/3639 , C03C17/3644 , C03C17/366 , C03C17/3626 , C03C17/3668 , C03C17/3642 , C03C17/3681 , C03C2217/70 , C03C2217/216 , C03C2217/228 , C03C2217/24 , C03C2217/256 , C03C2217/281 , C03C2217/22 , C03C2217/23 , C03C2218/156
Abstract: An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.
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公开(公告)号：US20210063200A1
公开(公告)日：2021-03-04
申请号：US17007873
申请日：2020-08-31
Applicant: NVIDIA Corporation
Inventor： Michael Kroepfl , Amir Akbarzadeh , Ruchi Bhargava , Vaibhav Thukral , Neda Cvijetic , Vadim Cugunovs , David Nister , Birgit Henke , Ibrahim Eden , Youding Zhu , Michael Grabner , Ivana Stojanovic , Yu Sheng , Jeffrey Liu , Enliang Zheng , Jordan Marr , Andrew Carley
Abstract: An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.
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Patent Agency Ranking
公开(公告)号：US11788861B2
公开(公告)日：2023-10-17
申请号：US17008074
申请日：2020-08-31
Applicant: NVIDIA Corporation
Inventor： David Nister , Ruchi Bhargava , Vaibhav Thukral , Michael Grabner , Ibrahim Eden , Jeffrey Liu
CPC classification number: G01C21/3841 , G01C21/1652 , G01C21/3811 , G01C21/3867 , G01C21/3878 , G01C21/3896 , G06N3/02
Abstract: An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.
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公开(公告)号：US20220413509A1
公开(公告)日：2022-12-29
申请号：US17900622
申请日：2022-08-31
Applicant: NVIDIA Corporation
Inventor： Michael Grabner , Jeremy Furtek , David Nister
Abstract: Systems and methods for performing visual odometry more rapidly. Pairs of representations from sensor data (such as images from one or more cameras) are selected, and features common to both representations of the pair are identified. Portions of bundle adjustment matrices that correspond to the pair are updated using the common features. These updates are maintained in register memory until all portions of the matrices that correspond to the pair are updated. By selecting only common features of one particular pair of representations, updated matrix values may be kept in registers. Accordingly, matrix updates for each common feature may be collectively saved with a single write of the registers to other memory. In this manner, fewer write operations are performed from register memory to other memory, thus reducing the time required to update bundle adjustment matrices and thus speeding the bundle adjustment process.
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公开(公告)号：US20210183093A1
公开(公告)日：2021-06-17
申请号：US17103680
申请日：2020-11-24
Applicant: NVIDIA Corporation
Inventor： Minwoo Park , Yue Wu , Michael Grabner , Cheng-Chieh Yang
Abstract: In various examples, surface profile estimation and bump detection may be performed based on a three-dimensional (3D) point cloud. The 3D point cloud may be filtered in view of a portion of an environment including drivable free-space, and within a threshold height to factor out other objects or obstacles other than a driving surface and protuberances thereon. The 3D point cloud may be analyzed—e.g., using a sliding window of bounding shapes along a longitudinal or other heading direction—to determine one-dimensional (1D) signal profiles corresponding to heights along the driving surface. The profile itself may be used by a vehicle—e.g., an autonomous or semi-autonomous vehicle—to help in navigating the environment, and/or the profile may be used to detect bumps, humps, and/or other protuberances along the driving surface, in addition to a location, orientation, and geometry thereof
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公开(公告)号：US20210063198A1
公开(公告)日：2021-03-04
申请号：US17008074
申请日：2020-08-31
Applicant: NVIDIA Corporation
Inventor： David Nister , Ruchi Bhargava , Vaibhav Thukral , Michael Grabner , Ibrahim Eden , Jeffrey Liu
Abstract: An end-to-end system for data generation, map creation using the generated data, and localization to the created map is disclosed. Mapstreams—or streams of sensor data, perception outputs from deep neural networks (DNNs), and/or relative trajectory data—corresponding to any number of drives by any number of vehicles may be generated and uploaded to the cloud. The mapstreams may be used to generate map data—and ultimately a fused high definition (HD) map—that represents data generated over a plurality of drives. When localizing to the fused HD map, individual localization results may be generated based on comparisons of real-time data from a sensor modality to map data corresponding to the same sensor modality. This process may be repeated for any number of sensor modalities and the results may be fused together to determine a final fused localization result.
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公开(公告)号：US20240078695A1
公开(公告)日：2024-03-07
申请号：US18504916
申请日：2023-11-08
Applicant: NVIDIA Corporation
Inventor： Minwoo Park , Yue Wu , Michael Grabner , Cheng-Chieh Yang
CPC classification number: G06T7/60 , G06T7/579 , G06V20/588 , G06T2200/08 , G06T2207/10028 , G06T2207/30256
Abstract: In various examples, surface profile estimation and bump detection may be performed based on a three-dimensional (3D) point cloud. The 3D point cloud may be filtered in view of a portion of an environment including drivable free-space, and within a threshold height to factor out other objects or obstacles other than a driving surface and protuberances thereon. The 3D point cloud may be analyzed—e.g., using a sliding window of bounding shapes along a longitudinal or other heading direction—to determine one-dimensional (1D) signal profiles corresponding to heights along the driving surface. The profile itself may be used by a vehicle—e.g., an autonomous or semi-autonomous vehicle—to help in navigating the environment, and/or the profile may be used to detect bumps, humps, and/or other protuberances along the driving surface, in addition to a location, orientation, and geometry thereof.
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