Semi-Dense Visual-Inertial Odometry and Mapping for Quadrotors with SWAP Constraints

Micro Aerial Vehicles have the potential to assist humans in real life tasks involving applications such as smart homes, search and rescue, and architecture construction. To enhance autonomous navigation capabilities these vehicles need to be able to create dense 3D maps of the environment, while concurrently estimating their own motion. In this paper, we are particularly interested in small vehicles that can navigate cluttered indoor environments. We address the problem of visual inertial state estimation, control and 3D mapping on platforms with Size, Weight, And Power (SWAP) constraints. The proposed approach is validated through experimental results on a 250 g, 22 cm diameter quadrotor equipped only with a stereo camera and an IMU with a computationally-limited CPU showing the ability to autonomously navigate, while concurrently creating a 3D map of the environment.