Organizational Unit:
Unmanned Aerial Vehicle Research Facility

Research Organization Registry ID
Description
Previous Names
Parent Organization
Parent Organization
Includes Organization(s)

Publication Search Results

Now showing 1 - 2 of 2
  • Item
    Autonomous Flight in GPS-Denied Environments Using Monocular Vision and Inertial Sensors
    (Georgia Institute of Technology, 2013-04) Wu, Allen D. ; Johnson, Eric N. ; Kaess, Michael ; Dellaert, Frank ; Chowdhary, Girish
    A vision-aided inertial navigation system that enables autonomous flight of an aerial vehicle in GPS-denied environments is presented. Particularly, feature point information from a monocular vision sensor are used to bound the drift resulting from integrating accelerations and angular rate measurements from an Inertial Measurement Unit (IMU) forward in time. An Extended Kalman filter framework is proposed for performing the tasks of vision-based mapping and navigation separately. When GPS is available, multiple observations of a single landmark point from the vision sensor are used to estimate the point’s location in inertial space. When GPS is not available, points that have been sufficiently mapped out can be used for estimating vehicle position and attitude. Simulation and flight test results of a vehicle operating autonomously in a simplified loss-of-GPS scenario verify the presented method.
  • Item
    Development and Evaluation of an Automated Path Planning Aid
    (Georgia Institute of Technology., 2012-11) Watts, Robert ; Christmann, Hans Claus ; Johnson, Eric N. ; Feigh, Karen M. ; Tsiotras, Panagiotis
    Handling en route emergencies in modern transport aircraft through adequate teamwork between the pilot, the crew and the aircraft’s automation systems is an ongoing and active field of research. An automated path planning aid tool can assist pilots with the tasks of selecting a convenient landing site and developing a safe path to land at this site in the event of an onboard emergency. This paper highlights the pilot evaluation results of a human factors study as part of such a proposed automated planning aid. Focusing on the interactions between the pilot and the automated planning aid, the presented results suggest that a particular implementation of the pilot aid interface, which uses a simple dial to sort the most promising landing sites, was effective. This selectable sorting capability, motivated by the anticipated cognitive mode of the pilot crew, improved the quality of the selected site for the majority of the cases tested. Although the presented approach increased the average time required for the selection of an alternate landing site, it decreased the time to complete the task in the case of emergencies unfamiliar to the pilot crew.