This paper presents a novel Nonlinear Model Predictive Control (NMPC) scheme for underwater robotic vehicles operating in a constrained workspace including static obstacles. The purpose of the controller is to guide the vehicle towards specific way points. Various limitations such as: obstacles, workspace boundary, thruster saturation and predefined desired upper bound of the vehicle velocity are captured as state and input constraints and are guaranteed during the control design. The proposed scheme incorporates the full dynamics of the vehicle in which the ocean currents are also involved. Hence, the control inputs calculated by the proposed scheme are formulated in a way that the vehicle will exploit the ocean currents, when these are in favor of the way-point tracking mission which results in reduced energy consumption by the thrusters. The performance of the proposed control strategy is experimentally verified using a 4 Degrees of Freedom (DoF) underwater robotic vehicle inside a constrained test tank with obstacles.

This paper proposes an autonomous landing scheme for a small-scale flybarless helicopter equipped with low-cost navigation sensors. The main contribution of this paper is the design of a model-free motion controller that guarantees autonomous landing with prescribed transient and steady state response, despite the presence of external disturbances acting on the vehicle. The proposed control scheme is of low complexity and does not require any knowledge of the helicopter dynamic parameters. Hence, it can be easily implemented in embedded control platforms integrated on small-scale helicopters. In order to provide the controller with accurate estimation of the vehicle's state vector during the landing procedure, an asynchronous sensor fusion and state estimation algorithm, based on an Unscented Kalman Filter (UKF), has been also implemented. The performance and the efficiency of the overall scheme are experimentally verified using a small-scale flybarless helicopter in a real autonomous landing process.

In this work we study the problem of landing a quadrotor on an inclined moving platform. The aerial robot employs an forward looking on-board camera to detect and observe the landing platform, which is carried by a mobile robot moving independently on an inclined surface. The platform may also be tilted with respect to the mobile robot. The overall goal is to design the aerial robot's control inputs such that it initially approaches the platform, while maintaining it within the camera's field of view and finally lands on it, in a way that minimizes the errors in position, attitude and velocity, while avoiding collision. Owing to the inclined ground and landing surface, the desired final state of the aerial robot is not an equilibrium state, which complicates significantly the control design. In that respect, a discrete-time non-linear model predictive controller was developed that optimizes both the trajectories and the time horizon, towards achieving the aforementioned objectives while respecting the input constraints as well. Finally, an extensive experimental study, with a Pioneer mobile robot and a Parrot ARDrone quadrotor, clarifies and verifies the theoretical findings.

In this paper, we address the attitude and vertical stabilization problem for small-scale helicopters. An emergency controller that would successfully stabilize the helicopter in a safe flight mode when a pilot/autopilot fails to control it, owing to unexpected reasons, is of outmost importance in flight control systems. In this direction, we propose a low complexity nonlinear control scheme that drives the angles and the vertical speed to zero with prescribed transient and steady state response, without incorporating any knowledge of the dynamic model parameters in the control design. The stereographic coordinates were employed to model the attitude state of the helicopter in an attempt to guarantee the safe stabilization for every possible initial orientation without introducing any representation singularities as in the Euler angles representation or increasing complexity as in conventional four element quaternions. Moreover, the transient and steady state performance of the proposed scheme is a priori determined even in the presence of external disturbances. Furthermore, the overall control scheme can be easily implemented on embedded flight systems equipped with low-cost sensors. Finally, simulation and experimental results on a realistic platform verify the efficacy of the proposed method.