Robust visual simultaneous localization and mapping for MAV using smooth variable structure filter

Abstract

The work presented in this paper is a part of research work on autonomous navigation for Micro Aerial Vehicles (MAVs). Simultaneous Localization and Mapping (SLAM) is crucial for any task of MAV navigation. The limited payload of the MAV makes the single camera as best solution for SLAM problem. In this paper the Large Scale Dense SLAM (LSD-SLAM) pose is fused with inertial data using Smooth Variable Structure Filter which is a robust filter. Our MAV-SVSFSLAM application is developed under Linux using Robotic Operating System (ROS) so that the code can be distributed in different nodes, to be used in other applications of guidance, control and navigation. The proposed approach is validated first in simulation, then experimentally using the Bebop Quadrotor in indoor and outdoor environment and good results have been obtained.