Indoor SLAM for Micro Aerial Vehicles Using Visual and Laser Sensor Fusion [chapter]

Elena López, Rafael Barea, Alejandro Gómez, Álvaro Saltos, Luis M. Bergasa, Eduardo J. Molinos, Abdelkrim Nemra
2015 Advances in Intelligent Systems and Computing  
This paper represents research in progress in Simultaneous Localization and Mapping (SLAM) for Micro Aerial Vehicles (MAVs) in the context of rescue and/or recognition navigation tasks in indoor environments. In this kind of applications, the MAV must rely on its own onboard sensors to autonomously navigate in unknown, hostile and GPS denied environments, such as ruined or semidemolished buildings. This article aims to investigate a new SLAM technique that fuses laser and visual information,
more » ... ides measurements from the inertial unit, to robustly obtain the 6DOF pose estimation of a MAV within a local map of the environment. Laser is used to obtain a local 2D map and a footprint estimation of the MAV position, while a monocular visual SLAM algorithm enlarges the pose estimation through an Extended Kalman Filter (EKF). The system consists of a commercial drone and a remote control unit to computationally afford the SLAM algorithms using a distributed node system based on ROS (Robot Operating System). Some experimental results show how sensor fusion improves the position estimation and the obtained map under different test conditions. The growing research on MAVs and the consequent improvement of technologies like microcomputers and onboard sensor devices, have increased the performance
doi:10.1007/978-3-319-27146-0_41 fatcat:2wnhgdevrvfdblkfxqkwx5yrze