Title :
Obstacle Detection for Small Autonomous Aircraft Using Sky Segmentation
Author :
McGee, Timothy G. ; Sengupta, Raja ; Hedrick, Karl
Author_Institution :
AINS Center for Collaborative Control of Unmanned Vehicles University of California, Berkeley 2105 Bancroft Way, Berkeley, CA 94720; tmcgee@me.berkeley.edu
Abstract :
A vision-based obstacle detection system for small unmanned aerial vehicles (UAVs) is presented. Obstacles are detected by segmenting the image into sky and non-sky regions and treating the non-sky regions as obstacles. The feasibility of this approach is demonstrated by using the vision output to steer a small unmanned aircraft to fly towards an obstacle. The experiment was first verified in a hardware in the loop (HIL) simulation and then successfully implemented on a small modified remote control plane using a large inflatable balloon as the obstacle.
Keywords :
UAV; obstacle avoidance; sky segmentation; support vector machine; Aircraft navigation; Cameras; Computer vision; Helicopters; Image motion analysis; Laser radar; Motion detection; Radar detection; Unmanned aerial vehicles; Vehicle detection; UAV; obstacle avoidance; sky segmentation; support vector machine;
Conference_Titel :
Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on
Print_ISBN :
0-7803-8914-X
DOI :
10.1109/ROBOT.2005.1570842
