公开(公告)号：US20180189576A1

公开(公告)日：2018-07-05

申请号：US15629311

申请日：2017-06-21

Applicant: QUALCOMM Incorporated

Inventor： Avdhut Joshi ,  Arvind Ramanandan ,  Murali Chari

IPC: G06K9/00 ,  G01B11/30 ,  G06K9/62

CPC classification number: G06K9/00798 ,  G01B11/30 ,  G01C21/165 ,  G01C22/00 ,  G06K9/6267 ,  G06T2207/30244

Abstract: An electronic device is described. The electronic device includes a memory and a processor in communication with the memory. The memory is configured to store precalibration data for a camera mounted on a vehicle, the precalibration data including a camera height determined relative to a road plane the vehicle is configured to contact during operation. The processor is configured to receive a plurality of images. The processor is also configured to classify one or more features in the plurality of images as road features based on the precalibration data.

公开(公告)号：US20180188384A1

公开(公告)日：2018-07-05

申请号：US15703588

申请日：2017-09-13

Applicant: QUALCOMM Incorporated

Inventor： Arvind Ramanandan ,  Murali Chari ,  Yiming Chen ,  Avdhut Joshi ,  John Steven Lima

IPC: G01S19/47 ,  G01S19/52

CPC classification number: G01S19/45 ,  G01S11/12 ,  G01S19/47 ,  G01S19/52 ,  G01S19/53

Abstract: A method for visual inertial odometry (VIO)-aided global positioning is described. The method includes updating an extended Kalman filter (EKF) state including a current pose and a sliding window of multiple prior poses. The sliding window includes poses at a number of most recent global positioning system (GPS) time epochs. Updating the EKF includes updating an EKF covariance matrix for the prior poses and the current pose in the EKF state. The method also includes determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose. The method further includes determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix. The method additionally includes using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs.

公开(公告)号：US10371530B2

公开(公告)日：2019-08-06

申请号：US15703483

申请日：2017-09-13

Applicant: QUALCOMM Incorporated

Inventor： Arvind Ramanandan ,  Murali Chari ,  Avdhut Joshi

IPC: G01C21/10 ,  G01C21/16 ,  G01S19/52 ,  G01S19/49 ,  G01S19/53

Abstract: A method performed by an electronic device is described. The method includes determining a predicted velocity relative to Earth corresponding to a first epoch using a camera and an inertial measurement unit (IMU). The method also includes determining, using a Global Positioning System (GPS) receiver, a GPS velocity relative to Earth. The method further includes determining a difference vector between the predicted velocity and the GPS velocity. The method additionally includes refining a bias estimate and a scale factor estimate of IMU measurements proportional to the difference vector. The method also includes refining a misalignment estimate between the camera and the IMU based on the difference vector. The method further includes providing pose information based on the refined bias estimate, the refined scale factor, and the refined misalignment estimate.

公开(公告)号：US10267924B2

公开(公告)日：2019-04-23

申请号：US15703588

申请日：2017-09-13

Applicant: QUALCOMM Incorporated

Inventor： Arvind Ramanandan ,  Murali Chari ,  Yiming Chen ,  Avdhut Joshi ,  John Steven Lima

IPC: G01S11/12 ,  G01S19/45 ,  G01S19/47 ,  G01S19/52 ,  G01S19/53

Abstract: A method for visual inertial odometry (VIO)-aided global positioning is described. The method includes updating an extended Kalman filter (EKF) state including a current pose and a sliding window of multiple prior poses. The sliding window includes poses at a number of most recent global positioning system (GPS) time epochs. Updating the EKF includes updating an EKF covariance matrix for the prior poses and the current pose in the EKF state. The method also includes determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose. The method further includes determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix. The method additionally includes using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs.

公开(公告)号：US20180188032A1

公开(公告)日：2018-07-05

申请号：US15703483

申请日：2017-09-13

Applicant: QUALCOMM Incorporated

Inventor： Arvind Ramanandan ,  Murali Chari ,  Avdhut Joshi

IPC: G01C21/16 ,  G01S19/52

CPC classification number: G01C21/165 ,  G01S19/49 ,  G01S19/52 ,  G01S19/53

Abstract: A method performed by an electronic device is described. The method includes determining a predicted velocity relative to Earth corresponding to a first epoch using a camera and an inertial measurement unit (IMU). The method also includes determining, using a Global Positioning System (GPS) receiver, a GPS velocity relative to Earth. The method further includes determining a difference vector between the predicted velocity and the GPS velocity. The method additionally includes refining a bias estimate and a scale factor estimate of IMU measurements proportional to the difference vector. The method also includes refining a misalignment estimate between the camera and the IMU based on the difference vector. The method further includes providing pose information based on the refined bias estimate, the refined scale factor, and the refined misalignment estimate.

公开(公告)号：US11941836B2

公开(公告)日：2024-03-26

申请号：US17547366

申请日：2021-12-10

Applicant: QUALCOMM Incorporated

Inventor： Urs Niesen ,  Murali Chari

IPC: G06T7/70 ,  G06T3/40 ,  G06T7/277 ,  G06T7/62 ,  G06V10/22 ,  G06V20/56

CPC classification number: G06T7/70 ,  G06T3/40 ,  G06T7/277 ,  G06T7/62 ,  G06V10/22 ,  G06V20/56 ,  G06T2207/30252 ,  G06V2201/08

Abstract: Disclosed are techniques for performing object detection and tracking. In some implementations, a process for performing object detection and tracking is provided. The process can include steps for obtaining, at a tracking object, an image comprising a target object, obtaining, at the tracking object, a first set of messages associated with the target object, determining a bounding box for the target object in the image based on the first set of messages associated with the target object, and extracting a sub-image from the image. In some approaches, the process can further include steps for detecting, using an object detection model, a location of the target object within the sub-image. Systems and machine-readable media are also provided.