3D Obstacle Avoidance in Adversarial Environments for Unmanned Aerial Vehicles.

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/36907

Title: 3D Obstacle Avoidance in Adversarial Environments for Unmanned Aerial Vehicles.
Author: Geyer, Mark S. ; Johnson, Eric N.
Abstract: As unmanned aerial vehicles (UAVs) are considered for a wider variety of military and commercial applications, the ability to navigate autonomously in unknown and hazardous environments is increasingly vital to the effectiveness of UAVs. Reliable and efficient obstacle detection is a fundamental prerequisite to performing autonomous navigation in an unknown environment. Traditional two-dimensional (planar) obstacle detection techniques, though computationally friendly, are often insufficient for safe navigation through complex environments in which commanded trajectories are simultaneously restricted vertically and horizontally by multiple buildings or by increases in terrain elevation. To this end, a pan/tilt-mounted laser rangefinder is explored as a means of identifying and characterizing potential obstacles in three dimensions (3D). From GPS position data and inertial sensor measurements, the filtered laser rangefinder data are transformed into local inertial coordinates and compiled into a dynamic three-dimensional grid-based mapping of the specified domain. Utilizing the grid-based map data, path planning algorithms generate the necessary obstacle avoidance trajectories. The Georgia Tech GTMax UAV helicopter and simulation environment provide a suitable test-bed for verification of the proposed obstacle detection and avoidance methodology.
Description: Copyright © 2006 by by the Authors. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.
Type: Article
URI: http://hdl.handle.net/1853/36907
Citation: 3D Obstacle Avoidance in Adversarial Environments for Unmanned Aerial Vehicles. Mark S. Geyer, Eric N. Johnson. AIAA 2006-6542AIAA Guidance, Navigation, and Control Conference and Exhibit, Keystone, Colorado, August, 2006.
Date: 2006-08
Contributor: Georgia Institute of Technology. School of Aerospace Engineering
Publisher: Georgia Institute of Technology
American Institute of Aeronautics and Astronautics
Subject: Obstacle avoidance
Unmanned aerial vehicles
Navigation

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