During last decade the scientific research on Unmanned Aerial Vehicless (UAVs) increased spectacularly and led to the design of multiple types of aerial platforms. The major challenge today is the development of autonomously operating aerial agents capable of completing missions independently of human interaction. To this extent, visual sensing techniques have been integrated in the control pipeline of the UAVs in order to enhance their navigation and guidance skills. The aim of this article is to present a comprehensive literature review on vision based applications for UAVs focusing mainly on current developments and trends. These applications are sorted in different categories according to the research topics among various research groups. More specifically vision based position-attitude control, pose estimation and mapping, obstacle detection as well as target tracking are the identified components towards autonomous agents. Aerial platforms could reach greater level of autonomy by integrating all these technologies onboard. Additionally, throughout this article the concept of fusion multiple sensors is highlighted, while an overview on the challenges addressed and future trends in autonomous agent development will be also provided.

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Survey on Computer Vision for UAVs: Current Developments and Trends

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods.

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties.

The problem of distributed formation control for multiple quadrotor aircraft in the form of leader–follower structure is considered in this paper. Based on a nonsmooth backstepping design, a novel consensus formation control algorithm is proposed and utilized. First, for the position control subsystem, based on the linear quadratic regulator optimal design method, a formation control law for multiple quadrotor aircraft is designed such that the positions of all the quadrotor aircraft converge to the desired formation pattern. The designed formation control law for position systems will generate the desired attitude for the attitude control systems. Second, for the attitude control subsystem described by unit quaternion, by employing the technique of finite-time control and switch control, a global bounded finite-time attitude tracking controller is designed such that the desired attitude can be tracked by the multiple quadrotor aircraft in finite time. Finally, numerical example is performed to demonstrate that all quadrotor aircraft converge to the desired formation pattern in the 3-D-space.

Distributed Formation Control of Multiple Quadrotor Aircraft Based on Nonsmooth Consensus Algorithms

This paper develops a novel integral sliding mode controller (ISMC) for a general type of underwater robots based on multiple-input and multiple-output extended-state-observer (MIMO-ESO). The difficulties associated with the unmeasured velocities, unknown disturbances, and uncertain hydrodynamics of the robot have been successfully solved in the control design. An adaptive MIMO-ESO is designed not only to estimate the unmeasurable linear and angular velocities, but also to estimate the unknown external disturbances. An ISMC is then designed using Lyapunov synthesis, and an adaptive gain update algorithm is introduced to estimate the upper bound of the uncertainties. Rigorous theoretical analysis is performed to show that the proposed control method is able to achieve asymptotical tracking performance for the underwater robot. Experimental studies are also carried out to validate the effectiveness of the proposed control, and to show that the proposed approach performs better than a conventional potential difference (PD) control approach.

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Corrections to “Extended State Observer-Based Integral Sliding Mode Control for an Underwater Robot With Unknown Disturbances and Uncertain Nonlinearities”

The attitude control of quadrotor unmanned aerial vehicle (UAV) is investigated. The aim of this paper is to develop a continuous multivariable attitude control law, which drives the attitude tracking errors of quadrotor UAV to zero in finite time. First, a multivariable super-twisting-like algorithm (STLA) is proposed for arbitrary order integrator systems subject to matched disturbances. A discontinuous integral term is incorporated in the control law in order to compensate the disturbances. A rigorous proof of the finite time stability of the close-loop system is derived by utilizing the Lyapunov method and the homogeneous technique. Then, the implementation of the developed method in an indoor quadrotor UAV is performed. The remarkable features of the developed algorithm includes the finite time convergence, the chattering suppression and the nominal performance recovery. Finally, the efficiency of the proposed method is illustrated by numerical simulations and experimental verification.

Multivariable Finite Time Attitude Control for Quadrotor UAV: Theory and Experimentation

This paper presents a novel asymptotic tracking controller for an underactuated quadrotor unmanned aerial vehicle using the robust integral of the signum of the error (RISE) method and an immersion and invariance (I&I)-based adaptive control methodology The control system is decoupled into two parts: the inner loop for attitude control and the outer loop for position control The RISE approach is applied in the inner loop for disturbance rejection, whereas the I&I approach is chosen for the outer loop to compensate for the parametric uncertainties The asymptotic tracking of the time-varying 3-D position and the yaw motion reference trajectories is proven via the Lyapunov-based stability analysis and LaSalle's invariance theorem Real-time experiment results, which are performed on a hardware-in-the-loop simulation testbed, are presented to illustrate the performance of the proposed control scheme

Nonlinear Robust Adaptive Tracking Control of a Quadrotor UAV Via Immersion and Invariance Methodology

Nonlinear robust sliding mode control of a quadrotor unmanned aerial vehicle based on immersion and invariance method

In this paper, a nano quadrotor helicopter which weighs about only 45 grams and has a diameter less than 0.15 m is employed for the autonomous flight control development in GPS-denied environments. Due to the very limited payload ability of the helicopter, a micro onboard vision system is designed to provide visual pose measurement. Then the attitude data obtained from a low cost micro inertial measurement unit (IMU) are fused with the visual measurement to provide accurate estimation of the helicopter's translational position and velocity. Nonlinear flight controller is designed to hold the quadrotor in a certain position and altitude without external ground motion capture system. Moreover, trajectory tracking ability is achieved with the help of a modified visual simultaneous localization and mapping (SLAM) algorithm. Experimental results are included to demonstrate the good hovering and tracking control performance of the proposed design in GPS-denied indoor and outdoor environments. To our best knowledge, few of previous works have demonstrated autonomous control ability of a quadrotor helicopter weighs less than 50 grams without the help of external ground motion capture system in GPS-denied indoor and outdoor environments.

Autonomous Flight Control of a Nano Quadrotor Helicopter in a GPS-Denied Environment Using On-Board Vision

In this paper, a new quaternion-based nonlinear robust output feedback tracking controller is developed to address the attitude and altitude tracking problem of a quadrotor unmanned aerial vehicle which is subject to structural uncertainties and unknown external disturbances By using the unit quaternion representation, the singularity associated with orientation representations can be avoided A set of non-model-based filters are introduced to provide estimations for the unmeasurable angular velocities and translational velocity in the altitude direction of the quadrotor in the case that velocity feedback is unavailable Approximation components based on neural network (NN) are introduced to estimate the modeling uncertainties, and robust feedback components are designed to compensate for external disturbances and NN reconstruction errors The Lyapunov-based stability analysis is employed to prove that a semiglobally asymptotic tracking result is achieved and all the closed-loop states remain bounded Numerical simulation results are provided to illustrate the good tracking performance of the proposed control methodologies

Bo Zhao

Papers

Nonlinear Robust Adaptive Tracking Control of a Quadrotor UAV Via Immersion and Invariance Methodology

Nonlinear robust sliding mode control of a quadrotor unmanned aerial vehicle based on immersion and invariance method

Autonomous Flight Control of a Nano Quadrotor Helicopter in a GPS-Denied Environment Using On-Board Vision

Nonlinear robust output feedback tracking control of a quadrotor UAV using quaternion representation

Nonlinear Control of a Quadrotor With Deviated Center of Gravity