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Delayed telop aid

  • US 9,519,286 B2
  • Filed: 03/19/2014
  • Issued: 12/13/2016
  • Est. Priority Date: 03/19/2013
  • Status: Active Grant
First Claim
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1. A method for the teleoperation of robots, stored and executed by a computer platform, comprising the steps of:

  • predicting robot motion from an operator'"'"'s queued commands to an Operator Control Unit (OCU);

    creating synthetic images to produce a video feed that looks as if the robot communication link had no delay and no reduced bandwidth;

    controlling the robot'"'"'s movement using closed loop; and

    displaying the synthetic image to an operatorcreating a 3D model of the environment;

    accurately controlling the vehicle to the predicted pose;

    providing an OpenGL based image reconstruction algorithm;

    providing a command interface to the robot for receiving distance and yaw input commands;

    dividing the required image processing between the vehicle and the OCU, taking into consideration the video quality and computational assets available;

    wherein the algorithm is chosen from one of the following for the group comprising;

    SIFT;

    a SURF feature for detection and tracking;

    Lucas-Kanade method;

    combined SURF feature tracking with Delaunay mesh generation;

    Kalman filtering techniques; and

    thin plate spline interpolation and curve fitting for synthetic image reconstruction;

    extracting SURF features for every frame;

    projecting SURF features from the image into the world frame using navigation data and our fish-eye camera model;

    performing ray intersection checks in 3D to determine if the ray originating at the camera location goes through the feature location in world frame;

    comparing each feature in the last frame is with every feature in the current frame;

    if the rays are close enough, a 3D location for that feature is computed;

    comparing the similarity of the SURF descriptors of the features in question, to each other, to increase the tracking accuracy; and

    if both conditions are satisfied, the track is considered good and added as a node to be used during an image reconstruction phase.

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