Real-time implementation of airborne inertial-SLAM

This paper addresses the challenges in 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, difficulty in loop closure, and high nonlinearity in both vehicle dynamics and observations. Airborne SLAM is formulated to relieve the computational complexity in both direct and indirect ways. The implementation is based on an Extended Kalman filter which fuses data from an Inertial Measurement Unit (IMU) and a passive vision system. Real-time results from flight trials are provided.