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：US12148169B2

公开(公告)日：2024-11-19

申请号：US17480016

申请日：2021-09-20

Applicant: QUALCOMM Incorporated

Inventor： Jayakrishnan Unnikrishnan ,  Avdhut Joshi

IPC: G06T7/20 ,  G06T7/73 ,  G06V10/46

Abstract: Systems and techniques are described for performing object detection and tracking. For example, a tracking object can obtain an image comprising a target object at least partially in contact with a surface. The tracking object can obtain a plurality of two-dimensional (2D) keypoints based on one or more features associated with one or more portions of the target object in contact with the surface in the image. The tracking object can obtain information associated with a contour of the surface. Based on the plurality of 2D keypoints and the information associated with the contour of the surface, the tracking object can determine a three-dimensional (3D) representation associated with the plurality of 2D keypoints.

公开(公告)号：US20240371035A1

公开(公告)日：2024-11-07

申请号：US18310132

申请日：2023-05-01

Applicant: QUALCOMM Incorporated

Inventor： Sai Madhuraj Jadhav ,  Amin Ansari ,  Avdhut Joshi

IPC: G06T7/80 ,  G01S7/497 ,  G01S17/86 ,  G01S17/89 ,  G01S17/931 ,  G06T5/00 ,  G06T5/20 ,  G06T7/13 ,  G06T7/521 ,  H04N17/00

Abstract: A processing system for cross-sensor calibration is configured to perform a first edge detection process on a camera image to generate an edge detected camera image, and perform a second edge detection process on a point cloud frame to generate an edge detected point cloud frame. The processing system projects the edge detected point cloud frame onto the edge detected camera image using an initial calibration matrix, determines an objective function representing an overlap of points in the edge detected point cloud frame and corresponding edge pixel values in the edge detected camera image, and determines a final calibration matrix based on the objective function.

公开(公告)号：US20240367674A1

公开(公告)日：2024-11-07

申请号：US18310403

申请日：2023-05-01

Applicant: QUALCOMM Incorporated

Inventor： Sai Madhuraj Jadhav ,  Amin Ansari ,  Yunxiao Shi ,  Avdhut Joshi

IPC: B60W60/00 ,  G06T7/13 ,  G06T7/521

Abstract: Example systems and techniques are described for controlling operation of a vehicle and training a machine learning model for controlling operation of a vehicle. A system includes memory configured to store point cloud data associated with the vehicle and one or more processors communicatively coupled to the memory. The one or more processors are configured to determine a depth map indicative of distance of one or more objects to the vehicle and control operation of a vehicle based on the depth map. The depth map is based on executing a machine learning model, the machine learning model being trained with a slice loss function determined from training point cloud data having a respective depth that is greater than the average depth for a set of points of the point cloud data plus a threshold.

公开(公告)号：US20240202949A1

公开(公告)日：2024-06-20

申请号：US18067183

申请日：2022-12-16

Applicant: QUALCOMM Incorporated

Inventor： Amin Ansari ,  Sai Madhuraj Jadhav ,  Yunxiao Shi ,  Gautam Sachdeva ,  Avdhut Joshi

IPC: G06T7/55 ,  G01S7/4865 ,  G01S7/4915 ,  G01S17/89 ,  G01S17/931

CPC classification number: G06T7/55 ,  G01S7/4865 ,  G01S7/4915 ,  G01S17/89 ,  G01S17/931 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/30252

Abstract: This disclosure provides systems, methods, and devices for vehicle driving assistance systems that support image processing. In a first aspect, a computing device may receive a predicted depth map and a measured depth map and may determine a time difference between the predicted depth map and the measured depth map. A supervision loss term may be determined based on the time difference, such as by weighting the supervision loss term based on the time difference. The computing device may train a model based on the supervision loss term, such as a model that generated the predicted depth map. Other aspects and features are also claimed and described.

公开(公告)号：US11630197B2

公开(公告)日：2023-04-18

申请号：US16733222

申请日：2020-01-02

Applicant: QUALCOMM Incorporated

Inventor： Jayakrishnan Unnikrishnan ,  Avdhut Joshi ,  Shivam Agarwal ,  Amir Salimi ,  Sree Sesha Aravind Vadrevu ,  Gautam Sachdeva ,  Yoga Y Nadaraajan ,  Ravi Teja Sukhavasi ,  Xinzhou Wu ,  Young-Ki Baik ,  Duck Hoon Kim ,  Hyun-Mook Cho

IPC: G06T7/277 ,  G01S13/58 ,  G06T7/246 ,  G01S13/931 ,  B60R11/04 ,  G06V20/58 ,  G06V20/56 ,  G06V10/25 ,  G06V10/762 ,  G06V10/80

Abstract: Disclosed are techniques for determining a motion state of a target object. In an aspect, an on-board computer of an ego vehicle detects the target object in one or more images, determines one or more first attributes of the target object based on measurements of the one or more images, determines one or more second attributes of the target object based on measurements of a map of a roadway on which the target object is travelling, and determines the motion state of the target object based on the one or more first attributes and the one or more second attributes of the target object.