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1.
公开(公告)号:US12223734B2
公开(公告)日:2025-02-11
申请号:US17151001
申请日:2021-01-15
Applicant: Aurora Operations, Inc.
Inventor: Xuanyuan Tu , Raquel Urtasun , Tsun-Hsuan Wang , Sivabalan Manivasagam , Jingkang Wang , Mengye Ren
IPC: G06V20/56 , G01S17/931 , G05D1/00 , G06F18/21 , G06F18/24 , G06N20/00 , G06V10/764 , G06V10/82
Abstract: Systems and methods for vehicle-to-vehicle communications are provided. An adverse system can obtain sensor data representative of an environment proximate to a targeted system. The adverse system can generate an intermediate representation of the environment and a representation deviation for the intermediate representation. The representation deviation can be designed to disrupt a machine-learned model associated with the target system. The adverse system can communicate the intermediate representation modified by the representation deviation to the target system. The target system can train the machine-learned model associated with the target system to detect the modified intermediate representation. Detected modified intermediate representations can be discarded before disrupting the machine-learned model.
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公开(公告)号:US20240391097A1
公开(公告)日:2024-11-28
申请号:US18670288
申请日:2024-05-21
Applicant: Aurora Operations, Inc.
Inventor: Sergio Casas , Davi Eugenio Nascimento Frossard , Shun Da Suo , Xuanyuan Tu , Raquel Urtasun
Abstract: Systems and methods for streaming sensor packets in real-time are provided. An example method includes obtaining a sensor data packet representing a first portion of a three-hundred and sixty degree view of a surrounding environment of a robotic platform. The method includes generating, using machine-learned model(s), a local feature map based at least in part on the sensor data packet. The local feature map is indicative of local feature(s) associated with the first portion of the three-hundred and sixty degree view. The method includes updating, based at least in part on the local feature map, a spatial map to include the local feature(s). The spatial map includes previously extracted local features associated with a previous sensor data packet representing a different portion of the three-hundred and sixty degree view than the first portion. The method includes determining an object within the surrounding environment based on the updated spatial map.
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3.
公开(公告)号:US12214801B2
公开(公告)日:2025-02-04
申请号:US17528549
申请日:2021-11-17
Applicant: Aurora Operations, Inc.
Inventor: Jingkang Wang , Ava Alison Pun , Xuanyuan Tu , Mengye Ren , Abbas Sadat , Sergio Casas , Sivabalan Manivasagam , Raquel Urtasun
Abstract: Techniques for generating testing data for an autonomous vehicle (AV) are described herein. A system can obtain sensor data descriptive of a traffic scenario. The traffic scenario can include a subject vehicle and actors in an environment. Additionally, the system can generate a perturbed trajectory for a first actor in the environment based on perturbation values. Moreover, the system can generate simulated sensor data. The simulated sensor data can include data descriptive of the perturbed trajectory for the first actor in the environment. Furthermore, the system can provide the simulated sensor data as input to an AV control system. The AV control system can be configured to process the simulated sensor data to generate an updated trajectory for the subject vehicle in the environment. Subsequently, the system can evaluate an adversarial loss function based on the updated trajectory for the subject vehicle to generate an adversarial loss value.
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公开(公告)号:US12127085B2
公开(公告)日:2024-10-22
申请号:US17150998
申请日:2021-01-15
Applicant: Aurora Operations, Inc.
Inventor: Nicholas Baskar Vadivelu , Mengye Ren , Xuanyuan Tu , Raquel Urtasun , Jingkang Wang
CPC classification number: H04W4/46 , B60W60/00272 , B60W60/00276 , G05D1/0088 , G05D1/0274 , G06F18/2415 , G06N20/00 , G06V20/56
Abstract: Systems and methods for improved vehicle-to-vehicle communications are provided. A system can obtain sensor data depicting its surrounding environment and input the sensor data (or processed sensor data) to a machine-learned model to perceive its surrounding environment based on its location within the environment. The machine-learned model can generate an intermediate environmental representation that encodes features within the surrounding environment. The system can receive a number of different intermediate environmental representations and corresponding locations from various other systems, aggregate the representations based on the corresponding locations, and perceive its surrounding environment based on the aggregated representations. The system can determine relative poses between the each of the systems and an absolute pose for each system based on the representations. Each representation can be aggregated based on the relative or absolute poses of each system and weighted according to an estimated accuracy of the location corresponding to the representation.
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