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Showing 1 to 5 of 5 for “"Cross-Track Error"”.

  1. Autonomous Vehicle Pose Estimation in GNSS-Denied Areas Using Cross-Track Error Measurements

    … novel approach to vehicle pose estimation using cross-track error (CTE) measurements as supplemental inputs for GNSS denied environments. The proposed method leverages CTE, a measure of lateral deviation from a desired trajectory, to estimate the vehicle’s position and orientation in real-time …

    vt Repository record for Autonomous Vehicle Pose Estimation in GNSS-Denied Areas Using Cross-Track Error Measurements (opens in a new tab)

  2. High performance path following for marine vehicles using azimuthing podded propulsion

    … of such vessels allow the time constant of cross-track error response to be greatly reduced. Additionally these vessels can follow course changes and waypoints more precisely than ruddered vessels.

    mit Repository record for High performance path following for marine vehicles using azimuthing podded propulsion (opens in a new tab)

  3. Minimizing current effects on autonomous surface craft operations in Singapore harbor

    … ASCs under the influence of currents. The first, Cross-Track Error Minimization, ensures that the vehicle follows a straight-line trajectory between two waypoints under the effects of surface waves and currents. The second controller, Time-Optimal, uses Zermelo's problem and function minimization …

    mit Repository record for Minimizing current effects on autonomous surface craft operations in Singapore harbor (opens in a new tab)

  4. An Airspace Simulator for Separation Management Research

    … and autopilot flight control with an average cross track error of 0.05 nmi for waypoint-defined routes in variable wind-fields. Trajectories are computed using the BADA v3.8 tabulated database to model the performance of 318 aircraft types. The simulator was demonstrated with up to 4000 total …

    whiterose Repository record for An Airspace Simulator for Separation Management Research (opens in a new tab)

  5. A Collection of Computer Vision Algorithms Capable of Detecting Linear Infrastructure for the Purpose of UAV Control

    … resulted in a classification accuracy of 96.6% across a 62 image dataset collected at Kentland Farm. A trajectory can then be generated by fitting the classified road pixels to polynomial curves. These trajectories can even be used to take specific turns at intersections based on a user defined …

    vt Repository record for A Collection of Computer Vision Algorithms Capable of Detecting Linear Infrastructure for the Purpose of UAV Control (opens in a new tab)