Stereo Vision based indoor/outdoor Navigation for Flying Robots

Abstract

We introduce our new quadrotor platform for realizing autonomous navigation in unknown indoor/outdoor environments. Autonomous waypoint navigation, obstacle avoidance and flight control is implemented on-board. The system does not require a special environment, artificial markers or an external reference system. We developed a monolithic, mechanically damped perception unit which is equipped with a stereo camera pair, an Inertial Measurement Unit (IMU), two processor-and an FPGA board. Stereo images are processed on the FPGA by the Semi-Global Matching algorithm. Keyframe based stereo odometry is fused with IMU data compensating for time delays that are induced by the vision pipeline. The system state estimate is used for control and on-board 3D mapping. An operator can set waypoints in the map, while the quadrotor autonomously plans its path avoiding obstacles. We show experiments with the quadrotor flying from inside a building to the outside and vice versa, traversing a window and a door respectively. A video of the experiments is part of this work. To the best of our knowledge, this is the first autonomously flying system with complete on-board processing that performs waypoint navigation with obstacle avoidance in geometrically unconstrained, complex indoor/outdoor environments.