The new open-source quadrotor platform called X4-MaG presented here was developed for academic and research applications. X4-MaG is a small, low-cost open quadrotor of only 307–grammes which offers two levels of controllers providing a manual mode and an automatic mode thanks to powerful Linux-based controller embedded onboard. The experiments presented here show the reliability of the open hardware and software embedded onboard the quadrotor. To estimate the robot s attitude, a quaternion-based complementary filter requiring very few computational resources was developed and implemented on an 8-bit Arduino board. It was also established that the stabilization feedback system based on quaternions tracks the attitude setpoints with precision up to twice greater than a classical cascaded PI controller. The controllers and estimators were designed in the Matlab/Simulink environment and directly implemented onboard the tiny Linux-based autopilot board using a custom made toolbox (RT-MaG toolbox). The autopilot was tested in the brand-new Marseilles Flying Arena with various 3-D flight trajectories and found to be highly accurate with errors of only 0.7cm in hover and less than 3.2cm at 1.2m.s⁻¹. The X4-MaG quadrotor was able to reach speeds greater than 2m.s⁻¹ and reject attitude disturbances of 20′ within 0.8s.

Precise navigation is often performed by sensor fusion of different sensors. Among these sensors, optical sensors use image features to obtain the position and attitude of the camera. Runway relative navigation during final approach is a special case where robust and continuous detection of the runway is required. This paper presents a robust threshold marker detection method for monocular cameras and introduces an on-board real-time implementation with flight test results. Results with narrow and wide field-of-view optics are compared. The image processing approach is also evaluated on image data captured by a different on-board system. The pure optical approach of this paper increases sensor redundancy because it does not require input from an inertial sensor as most of the robust runway detectors.