Effective Target Aware Visual Navigation for UAVs

In this paper we propose an effective vision-based navigation method that allows a multirotor vehicle to simultaneously reach a desired goal pose in the environment while constantly facing a target object or landmark. Standard techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast maneuvers) do not allow to constantly maintain the line of sight with a target of interest. Instead, we compute the optimal trajectory by solving a non-linear optimization problem that minimizes the target re-projection error while meeting the UAV's dynamic constraints. The desired trajectory is then tracked by means of a real-time Non-linear Model Predictive Controller (NMPC): this implicitly allows the multirotor to satisfy both the required constraints. We successfully evaluate the proposed approach in many real and simulated experiments, making an exhaustive comparison with a standard approach.Comment: Conference paper at "European Conference on Mobile Robotics" (ECMR) 201

Advanced Feedback Linearization Control for Tiltrotor UAVs: Gait Plan, Controller Design, and Stability Analysis

Three challenges, however, can hinder the application of Feedback Linearization: over-intensive control signals, singular decoupling matrix, and saturation. Activating any of these three issues can challenge the stability proof. To solve these three challenges, first, this research proposed the drone gait plan. The gait plan was initially used to figure out the control problems in quadruped (four-legged) robots; applying this approach, accompanied by Feedback Linearization, the quality of the control signals was enhanced. Then, we proposed the concept of unacceptable attitude curves, which are not allowed for the tiltrotor to travel to. The Two Color Map Theorem was subsequently established to enlarge the supported attitude for the tiltrotor. These theories were employed in the tiltrotor tracking problem with different references. Notable improvements in the control signals were witnessed in the tiltrotor simulator. Finally, we explored the control theory, the stability proof of the novel mobile robot (tilt vehicle) stabilized by Feedback Linearization with saturation. Instead of adopting the tiltrotor model, which is over-complicated, we designed a conceptual mobile robot (tilt-car) to analyze the stability proof. The stability proof (stable in the sense of Lyapunov) was found for a mobile robot (tilt vehicle) controlled by Feedback Linearization with saturation for the first time. The success tracking result with the promising control signals in the tiltrotor simulator demonstrates the advances of our control method. Also, the Lyapunov candidate and the tracking result in the mobile robot (tilt-car) simulator confirm our deductions of the stability proof. These results reveal that these three challenges in Feedback Linearization are solved, to some extents.Comment: Doctoral Thesis at The University of Toky

Survey on Aerial Multirotor Design: a Taxonomy Based on Input Allocation

This paper reviews the impact of multirotor aerial vehicles designs on their abilities in terms of tasks and system properties. We propose a general taxonomy to characterize and describe multirotor aerial vehicles and their design, which we apply exhaustively on the vast literature available. Thanks to the systematic characterization of the designs we exhibit groups of designs having the same abilities in terms of achievable tasks and system properties. In particular, we organize the literature review based on the number of atomic actuation units and we discuss global properties arising from their choice and spatial distribution in the designs. Finally, we provide a discussion on the common traits of the designs found in the literature and the main future open problems

Linear and Non-Linear Control of a Quadrotor UAV

This thesis describes two controllers designed specifically for a quadrotor helicopter unmanned aerial vehicle (UAV). A linear controller and a non-linear controller are discussed for use on the quadrotor helicopter using feedback that is obtained from microelectromechanical systems and GPS. The linear controller is an orientation based PID controller that controls the angles of the quadrotor UAV. The controller was first simulated and the results displayed graphically using FlightGear. Experiments were conducted using this controller on a DraganFlyer X-Pro quadrotor helicopter to prove the proposed method used for closing the feedback loop. The non-linear controller is developed using Lyapunov stability methods. The design goal for this controller is to add a two degree-of-freedom camera postioner to the quadrotor for a total of six degree-of-freedom camera actuator. The UAV will track three desired translational velocities and three angular velocities using only translational and rotational velocities for feedback

Advanced trajectory tracking for UAVs using combined feedforward/feedback control design

Trajectory tracking is a major challenge for UAVs. The more complex the trajectory is, the more accurate tracking is required with minimum divergence from the trajectory. Apart from active trajectory tracking mechanisms, current solutions to accurate trajectory tracking in narrow areas require low speed motions. This paper presents a systematic design methodology using centralised feedforward/feedback control architecture for advanced trajectory tracking without compromising the speed of the vehicle. Using the norm as a measure for the design criteria, the proposed method proves fast tracking with no overshooting and less actuators energy compared with single degree-of-freedom feedback control method. The results are verified using simulations for two systems: a tri-rotor VTOL UAV (fully actuated system), and a quadrotor trainer (over-actuated system)