Nonlinear Visual Control of Unmanned Aerial Vehicles in GPS-Denied Environments (original) (raw)

2015, IEEE Transactions on Robotics

In this paper, we propose a nonlinear controller that stabilizes unmanned aerial vehicles in GPS-denied environments with respect to visual targets by using only onboard sensing. The translational velocity of the vehicle is estimated online with a nonlinear observer, which exploits spherical visual features as the main source of information. With the proposed solution, only four visual features have shown to be enough for the observer to operate in a real scenario. In addition, the observer is computationally light with constant numerical complexity, involving small-dimension matrices. The observer output is then exploited in a nonlinear controller designed with an integral backstepping approach, thus yielding a novel robust control system. By means of Lyapunov analysis, the stability of the closed-loop system is proved. Extensive simulation and experimental tests with a quadrotor are carried out to verify the validity and robustness of the proposed approach. The control system runs fully onboard on a standard processor, and only a low-cost sensing suite is employed. Tracking of a target whose speed exceeds 2 m/s is also considered in the real-hardware experiments. Index Terms-Image-based visual servoing, nonlinear controller, nonlinear observer, unmanned aerial vehicle (UAV), velocity estimation. I. INTRODUCTION A UTONOMOUS control of robotic vehicles requires information of their state, followed by a proper control action. For unmanned aerial vehicles (UAVs), extracting their translational velocity solely from the onboard sensing is still an open issue. Yet, the translational velocity is a key information for UAV control [1]. The most adopted sensing modalities for this purpose are GPS and vision. GPS relies on external source (satellites) for providing vehicle global position information, and as such, it does not operate in cluttered urban areas, is not reliable at low altitudes, suffers from satellite signal cuts, and is a nonpassive sensing modality [2], [3]. On the other hand, vision Manuscript