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

Autor:	Huili Yu, Randy Beard
Rok vydání:	2013
Předmět:	Computer science business.industry Frame (networking) Any-angle path planning Computer Science::Robotics Extended Kalman filter Artificial Intelligence Depth map Obstacle avoidance Computer vision Motion planning Micro air vehicle Artificial intelligence business Collision avoidance
Zdroj:	Autonomous Robots. 34:93-109
ISSN:	1573-7527 0929-5593
DOI:	10.1007/s10514-012-9314-z
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::ea44a4ad13bff957fa5dc8ec1cf7f6e7 https://doi.org/10.1007/s10514-012-9314-z Zobrazit plný text záznamu Full text from SpringerLink