NDLI: A vision-based collision avoidance technique for micro air vehicles using local-level frame mapping and path planning

Content Provider	Springer Nature Link
Author	Yu, Huili Beard, Randy
Copyright Year	2013
Abstract	This paper presents a vision-based collision avoidance technique for small and miniature air vehicles (MAVs) using local-level frame mapping and path planning. Using computer vision algorithms, a depth map that represents the range and bearing to obstacles is obtained. Based on the depth map, we estimate the range, azimuth to, and height of obstacles using an extended Kalman filter that takes into account the correlations between obstacles. We then construct maps in the local-level frame using cylindrical coordinates for three dimensional path planning and plan Dubins paths using the rapidly-exploring random tree algorithm. The behavior of our approach is analyzed and the characteristics of the environments where the local path planning technique guarantees collision-free paths and maneuvers the MAV to a specific goal region are described. Numerical results show the proposed technique is successful in solving path planning and multiple obstacle avoidance problems for fixed wing MAVs.
Starting Page	93
Ending Page	109
Page Count	17
File Format	PDF
ISSN	09295593
Journal	Autonomous Robots
Volume Number	34
Issue Number	1-2
e-ISSN	15737527
Language	English
Publisher	Springer US
Publisher Date	2013-01-11
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Path planning Collision avoidance Micro Air Vehicle Computer vision Robotics and Automation Control, Robotics, Mechatronics Artificial Intelligence (incl. Robotics) Computer Imaging, Vision, Pattern Recognition and Graphics
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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