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公开(公告)号：US12291240B1
公开(公告)日：2025-05-06
申请号：US17529866
申请日：2021-11-18
Applicant: Zoox, Inc.
Inventor： Andres Guillermo Morales Morales , Samir Parikh , Kai Zhenyu Wang
IPC: B60W60/00
Abstract: Techniques for determining a response of a simulated vehicle to a simulated object in a simulation are discussed herein. Log data captured by a physical vehicle in an environment can be received. Object data representing an object in the log data can be used to instantiate a simulated object in a simulation to determine a response of a simulated vehicle to the simulated object. Additionally, one or more trajectory segments in a trajectory library representing the log data can be determined and instantiated as a trajectory of the simulated object in order to increase the accuracy and realism of the simulation.
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公开(公告)号：US12013693B1
公开(公告)日：2024-06-18
申请号：US16730948
申请日：2019-12-30
Applicant: Zoox, Inc.
Inventor： Jonathan Philip Wai Wah Chan , Kai Zhenyu Wang
CPC classification number: G05D1/0061 , G05D1/0221 , G05D1/0289 , G06N20/00
Abstract: Techniques are disclosed for component verification for complex systems. The techniques may include receiving log data, obtaining ground truth data based on the log data and determining an outcome at least in part by simulating a prediction by a prediction component based on the log data and the ground truth data. The techniques may further include simulating a second prediction by the prediction component based on the ground truth data, determining whether the second prediction resulted in the negative outcome of the scenario and determining the disengagement event is attributable to a perception component of the autonomous operation system at least partly in response to determining the second prediction based on the ground truth data did not result in the negative outcome.
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公开(公告)号：US11810225B2
公开(公告)日：2023-11-07
申请号：US17218010
申请日：2021-03-30
Applicant: Zoox, Inc.
Inventor： Gerrit Bagschik , Andrew Scott Crego , Gowtham Garimella , Michael Haggblade , Andraz Kavalar , Kai Zhenyu Wang
Abstract: Techniques for top-down scene generation are discussed. A generator component may receive multi-dimensional input data associated with an environment. The generator component may generate, based at least in part on the multi-dimensional input data, a generated top-down scene. A discriminator component receives the generated top-down scene and a real top-down scene. The discriminator component generates binary classification data indicating whether an individual scene in the scene data is classified as generated or classified as real. The binary classification data is provided as a loss to the generator component and the discriminator component.
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公开(公告)号：US20230159060A1
公开(公告)日：2023-05-25
申请号：US17535418
申请日：2021-11-24
Applicant: Zoox, Inc.
Inventor： Gowtham Garimella , Marin Kobilarov , Andres Guillermo Morales Morales , Ethan Miller Pronovost , Kai Zhenyu Wang , Xiaosi Zeng
CPC classification number: B60W60/0027 , G06N3/02 , B60W2556/40 , B60W2554/4041 , B60W2554/4045 , B60W2555/60 , B60W2554/4042 , B60W2554/4043 , B60W2554/4046 , B60W2554/402
Abstract: Techniques for determining unified futures of objects in an environment are discussed herein. Techniques may include determining a first feature associated with an object in an environment and a second feature associated with the environment and based on a position of the object in the environment, updating a graph neural network (GNN) to encode the first feature and second feature into a graph node representing the object and encode relative positions of additional objects in the environment into one or more edges attached to the node. The GNN may be decoded to determine a distribution of predicted positions for the object in the future that meet a criterion, allowing for more efficient sampling. A predicted position of the object in the future may be determined by sampling from the distribution.
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公开(公告)号：US20230150549A1
公开(公告)日：2023-05-18
申请号：US17529803
申请日：2021-11-18
Applicant: Zoox, Inc.
Inventor： Andres Guillermo Morales Morales , Samir Parikh , Kai Zhenyu Wang
IPC: B60W60/00
CPC classification number: B60W60/00272 , B60W60/0017 , B60W60/0016 , B60W2420/42 , B60W2554/4049
Abstract: Techniques for determining a response of a simulated vehicle to a simulated object in a simulation are discussed herein. Log data captured by a physical vehicle in an environment can be received. Object data representing an object in the log data can be used to instantiate a simulated object in a simulation to determine a response of a simulated vehicle to the simulated object. Additionally, one or more trajectory segments in a trajectory library representing the log data can be determined and instantiated as a trajectory of the simulated object in order to increase the accuracy and realism of the simulation.
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Patent Agency Ranking
公开(公告)号：US11631200B2
公开(公告)日：2023-04-18
申请号：US17325562
申请日：2021-05-20
Applicant: Zoox, Inc.
IPC: G06T11/00 , G08G1/04 , G08G1/01 , G06T11/60 , G08G1/052 , G08G1/056 , G05B13/02 , G06V20/56 , G06F18/214 , G06V10/82
Abstract: Techniques for determining predictions on a top-down representation of an environment based on vehicle action(s) are discussed herein. Sensors of a first vehicle (such as an autonomous vehicle) can capture sensor data of an environment, which may include object(s) separate from the first vehicle (e.g., a vehicle or a pedestrian). A multi-channel image representing a top-down view of the object(s) and the environment can be generated based on the sensor data, map data, and/or action data. Environmental data (object extents, velocities, lane positions, crosswalks, etc.) can be encoded in the image. Action data can represent a target lane, trajectory, etc. of the first vehicle. Multiple images can be generated representing the environment over time and input into a prediction system configured to output prediction probabilities associated with possible locations of the object(s) in the future, which may be based on the actions of the autonomous vehicle.
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公开(公告)号：US20230100014A1
公开(公告)日：2023-03-30
申请号：US17966037
申请日：2022-10-14
Applicant: Zoox, Inc.
Inventor： Pengfei Duan , James William Vaisey Philbin , Cooper Stokes Sloan , Sarah Tariq , Feng Tian , Chuang Wang , Kai Zhenyu Wang , Yi Xu
Abstract: Techniques relating to monitoring map consistency are described. In an example, a monitoring component associated with a vehicle can receive sensor data associated with an environment in which the vehicle is positioned. The monitoring component can generate, based at least in part on the sensor data, an estimated map of the environment, wherein the estimated map is encoded with policy information for driving within the environment. The monitoring component can then compare first information associated with a stored map of the environment with second information associated with the estimated map to determine whether the estimated map and the stored map are consistent. Component(s) associated with the vehicle can then control the object based at least in part on results of the comparing.
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公开(公告)号：US20220319057A1
公开(公告)日：2022-10-06
申请号：US17218010
申请日：2021-03-30
Applicant: Zoox, Inc.
Inventor： Gerrit Bagschik , Andrew Scott Crego , Gowtham Garimella , Michael Haggblade , Andraz Kavalar , Kai Zhenyu Wang
Abstract: Techniques for top-down scene generation are discussed. A generator component may receive multi-dimensional input data associated with an environment. The generator component may generate, based at least in part on the multi-dimensional input data, a generated top-down scene. A discriminator component receives the generated top-down scene and a real top-down scene. The discriminator component generates binary classification data indicating whether an individual scene in the scene data is classified as generated or classified as real. The binary classification data is provided as a loss to the generator component and the discriminator component.
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公开(公告)号：US11433922B1
公开(公告)日：2022-09-06
申请号：US16723937
申请日：2019-12-20
Applicant: Zoox, Inc.
Inventor： Matthew Van Heukelom , Tencia Lee , Kai Zhenyu Wang
Abstract: Techniques for determining an uncertainty metric associated with an object in an environment can include determining the object in the environment and a set of candidate trajectories associated with the object. Further, a vehicle, such as an autonomous vehicle, can be controlled based at least in part on the uncertainty metric. The vehicle can determine a traversed trajectory associated with the object and determine a difference between the traversed trajectory and the set of candidate trajectories. Based on the difference, the vehicle can determine an uncertainty metric associated with the object. In some instances, the vehicle can input the traversed trajectory and the set of candidate trajectories to a machine-learned model that can output the uncertainty metric.
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公开(公告)号：US11409304B1
公开(公告)日：2022-08-09
申请号：US16586620
申请日：2019-09-27
Applicant: Zoox, Inc.
Inventor： Tianyi Cai , James William Vaisey Philbin , Kai Zhenyu Wang
Abstract: The described techniques relate to predicting object behavior based on top-down representations of an environment comprising top-down representations of image features in the environment. For example, a top-down representation may comprise a multi-channel image that includes semantic map information along with additional information for a target object and/or other objects in an environment. A top-down image feature representation may also be a multi-channel image that incorporates various tensors for different image features with channels of the multi-channel image, and may be generated directly from an input image. A prediction component can generate predictions of object behavior based at least in part on the top-down image feature representation, and in some cases, can generate predictions based on the top-down image feature representation together with the additional top-down representation.
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