In this paper, we address the hover flight and speed regulation of a quadrotor rotorcraft to perform autonomous navigation. For this purpose, we have developed a vision system which estimates the altitude, the lateral position and the forward speed of the engine during flights. We show that the visual information allows the construction of control strategies for different kinds of flying modes: hover flight, forward flight at constant speed. A hierarchical control strategy is developed and implemented. The local stabilization of the vehicle is proven. Experimental autonomous flight was successfully achieved which validates the visual algorithm and the control law.

Autonomous navigation of an unmanned aerial vehicle (UAV) can be achieved with a reactive system which allows the robot to overcome all the unexpected changes in its environment. In this article, we propose a new approach to avoid frontal obstacles using known properties of the optical flow and by taking advantage of the capability of stationary flight of the rotorcraft. A state machine is proposed as a solution to equip the UAV with all reactions necessary for indoor navigation. We show how smooth transitions can be achieved by decreasing the speed of the vehicle proportional to the distance to an obstacle and by brief instants of hovering flight. Each stage of our algorithm has been tested in a mobile robot.

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Abstract-This article presents a comparison of three control techniques: Nested Saturations, Backstepping and Sliding Modes. The control objective consists of obtaining the best control strategy to stabilize the position of a quad-rotor unmanned aerial vehicle (UAV) when using visual feedback. We propose a visionbased method to measure translational speed as well as the UAV 3D position in a local frame. The three selected controllers were implemented and tested in real-time experiments. The obtained results demonstrate the performance of such methodologies applied to the quad-rotor system.

We address the problem of hover flight and translational velocity regulation of a quad-rotorcraft unmanned aerial vehicle (UAV) with the main objective of allowing the vehicle to navigate autonomously. This paper complements and improves previous researches considering multiple-camera systems and nonconventional sensors, which deal only with stabilizing the aerial vehicle in hover or in take-off and landing tasks. A vision system has been implemented to estimate the vehicle's altitude, lateral position, and forward velocity during flights. It is shown that, using visual information, it is possible to develop control strategies for different kinds of flying modes, such as hover flight and forward flight at constant velocity. The stability of the closed-loop system is ensured by implementing a hierarchical control strategy. In the first stage, the performance of the proposed methodologies was validated under a simulation environment, showing satisfactory and promising results. Next, real-time experimental applications, consisting of autonomous hover and forward flight at constant velocity, were successfully achieved, validating the effectiveness of the proposed imaging algorithm and vision-based controller.