TY - GEN
T1 - High-speed vision-based autonomous indoor navigation of a quadcopter
AU - Garcia, Adriano
AU - Mattison, Edward
AU - Ghose, Kanad
N1 - Publisher Copyright: © 2015 IEEE.
PY - 2015/7/7
Y1 - 2015/7/7
N2 - A monocular vision-based approach to indoor autonomous navigation for an off-the-shelf, low-cost Micro Air Vehicle (MAV) quadcopter is presented. Our approach is fully automated and relies on the extraction and analysis of the visual contours of the surrounding physical environment to successfully steer the MAV in hallways and to turn at intersections. All image analysis and processing necessary for deriving and controlling the flight trajectory take place off-board on a system external to the MAV. This permits the use of sophisticated multithreaded real-time algorithms that do not limit the speed of the drone. Furthermore, due to the elimination of on-board processing and possibly the use of additional sensors for realizing such autonomy, stock drones can be used and flight times realized on a single charge remain unaffected. We describe a prototype implementation on a Parrot AR.Drone quadcopter and initial results for autonomous navigation in a structured indoor environment that establishes the viability of the approach.
AB - A monocular vision-based approach to indoor autonomous navigation for an off-the-shelf, low-cost Micro Air Vehicle (MAV) quadcopter is presented. Our approach is fully automated and relies on the extraction and analysis of the visual contours of the surrounding physical environment to successfully steer the MAV in hallways and to turn at intersections. All image analysis and processing necessary for deriving and controlling the flight trajectory take place off-board on a system external to the MAV. This permits the use of sophisticated multithreaded real-time algorithms that do not limit the speed of the drone. Furthermore, due to the elimination of on-board processing and possibly the use of additional sensors for realizing such autonomy, stock drones can be used and flight times realized on a single charge remain unaffected. We describe a prototype implementation on a Parrot AR.Drone quadcopter and initial results for autonomous navigation in a structured indoor environment that establishes the viability of the approach.
UR - https://www.scopus.com/pages/publications/84941066172
U2 - 10.1109/ICUAS.2015.7152308
DO - 10.1109/ICUAS.2015.7152308
M3 - Conference contribution
T3 - 2015 International Conference on Unmanned Aircraft Systems, ICUAS 2015
SP - 338
EP - 347
BT - 2015 International Conference on Unmanned Aircraft Systems, ICUAS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 International Conference on Unmanned Aircraft Systems, ICUAS 2015
Y2 - 9 June 2015 through 12 June 2015
ER -