Kim, JonghyukSukkarieh, Salah2015-12-070921-8890http://hdl.handle.net/1885/25898This paper addresses some challenges to the real-time implementation of Simultaneous Localisation and Mapping (SLAM) on a UAV platform. When compared to the implementation of SLAM in 2D environments, airborne implementation imposes several difficulties in terms of computational complexity and loop closure, with high nonlinearity in both vehicle dynamics and observations. An implementation of airborne SLAM is formulated to relieve this computational complexity in both direct and indirect ways. Our implementation is based on an Extended Kalman Filter (EKF), which fuses data from an Inertial Measurement Unit (IMU) with data from a passive vision system. Real-time results from flight trials are provided.Keywords: Autonomous agents; Computational complexity; Conformal mapping; Kalman filtering; Motion estimation; Real time systems; Vision; Airborne simultaneous Localisation and Mapping (SLAM); Inertial Measurement Unit (IMU); Passive vision systems; Vehicle dynamic Airborne SLAM; Inertial Measurement Unit (IMU); UAV; Vision200710.1016/j.robot.2006.06.0062015-12-07