Self-localization using visual markers is widely used for precise control of Unmanned aerial vehicles (UAVs). This paper presents a novel method of 6-DoF pose estimation using a monocular camera and non co-planar markers. We conducted numerical simulations comparing pose estimation using co-planar markers and using non co-planar markers, and designed a non co-planar marker feasible for robotics applications. Our method uses a single CPU core and a field programmable gate array (FPGA) and can conduct fast and precise 6-DoF pose estimation at the same frequency of the camera input (100 fps). In addition, to show the performance of our method, we applied our 6-DoF pose estimation algorithm to a palm-sized quadcopter and flew it autonomously using only an on-board system with a monocular camera and three-axis gyro sensor. To the authors' knowledge, this is the first study on fully on-board autonomous flight control of an MAV in 6-DoF space without an accelerometer.

We describe an algorithm and hardware system of a 3D self-localization method for very cost effective hovering robots. The hardware system consists of very compact calculation and sensor units, instead of using a high performance calculation unit like a laptop PC. In the experiment, the comparison with the ground truth sensor is discussed and implementation of the system on a palm-sized quad-copter is studied to realize a very compact, on-board, fully autonomous quad-copter.