Map-aided inertial odometry with neural network for augmented reality devices

    公开(公告)号:US12248625B2

    公开(公告)日:2025-03-11

    申请号:US18527953

    申请日:2023-12-04

    Applicant: GOOGLE LLC

    Abstract: Techniques of providing continual augmented reality navigation include combining first and second 6DoF poses from, respectively, a localization from a map in a vicinity of a location to an image and from predicted 6DoF poses based on IMU data. The first 6DoF pose is based on a visual positioning system that uses map data from a vicinity of a location combined with an image from the world-facing camera of the AR smartglasses that provides 6DoF pose in world coordinates independent of the IMU. The second 6DoF pose is based on compensated rotational velocity and acceleration measurements derived from IMU intrinsic values.

    TRACKING ALGORITHM FOR CONTINUOUS AR EXPERIENCES

    公开(公告)号:US20230359286A1

    公开(公告)日:2023-11-09

    申请号:US18312448

    申请日:2023-05-04

    Applicant: Google LLC

    CPC classification number: G06F3/0346 G06T7/70 G06T2207/20084

    Abstract: A tracking system and associated algorithms are disclosed that can provide a user with a continuous, reset-free augmented reality (AR) experience. When the user wears an AR headset equipped with a camera and an inertial measurement unit (IMU), motion sensor data from the IMU can be combined with image data from the camera to create a device pose, representing a position and an orientation of the headset relative to its environment. In some implementations, when a reset occurs, a six-degrees-of-freedom (6DoF) algorithm can be configured to support the pose until a re-initialization is completed. In some implementations, a neural network can be used to correct for IMU integration drifts in the 6DoF algorithm. In some implementations, the IMU-based 6DoF uses a neural network that exploits the device's past motion to infer its future motion.

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