Real-Time Setup with PD and Backstepping Control for a Pelican Quadrotor

In this paper, a real-time setup and an implementation of a Proportional Derivative (PD) controller for orientation and comparison between PD and BackStepping (BS) controllers for linear positioning are presented using a Pelican quadrotor from Ascending Technologies (AscTec). An onboard Inertial Measurement Unit (IMU) was used for orientation control and Optitrack Vision Tracking System for linear positioning control. A linear Kalman filter was implemented for linear velocity estimation. The software and hardware integration was achieved with the help of the Robot Operating System (ROS). Simulations and experiments with this drone platform are achieved in order to implement different controller algorithms and analyse them in order to achieve better aircraft performance

A review of aerial manipulation of small-scale rotorcraft unmanned robotic systems

Small-scale rotorcraft unmanned robotic systems (SRURSs) are a kind of unmanned rotorcraft with manipulating devices. This review aims to provide an overview on aerial manipulation of SRURSs nowadays and promote relative research in the future. In the past decade, aerial manipulation of SRURSs has attracted the interest of researchers globally. This paper provides a literature review of the last 10 years (2008–2017) on SRURSs, and details achievements and challenges. Firstly, the definition, current state, development, classification, and challenges of SRURSs are introduced. Then, related papers are organized into two topical categories: mechanical structure design, and modeling and control. Following this, research groups involved in SRURS research and their major achievements are summarized and classified in the form of tables. The research groups are introduced in detail from seven parts. Finally, trends and challenges are compiled and presented to serve as a resource for researchers interested in aerial manipulation of SRURSs. The problem, trends, and challenges are described from three aspects. Conclusions of the paper are presented, and the future of SRURSs is discussed to enable further research interests

Modeling and nonlinear adaptive control of an aerial manipulation system

Autonomous aerial robots have become an essential part of many civilian and military applications. The workspace and agility of these vehicles motivated great research interest resulting in various studies addressing their control architectures and mechanical configurations. Increasing autonomy enabled them to perform tasks such as surveillance, inspection and remote sensing in hazardous and challenging environments. The ongoing research promises further contributions to the society, in both theory and practice. To furthermore extend their vast applications, aerial robots are equipped with the tools to enable physical interaction with the environment. These tasks represent a great challenge due to the technological limitations as well as the lack of sophisticated methods necessary for the control of the system to perform desired operations in an efficient and stable manner. Modeling and control problem of an aerial manipulation is still an open research topic with many studies addressing these issues from different perspectives. This thesis deals with the nonlinear adaptive control of an aerial manipulation system (AMS). The system consists of a quadrotor equipped with a 2 degrees of freedom (DOF) manipulator. The complete modeling of the system is done using the Euler-Lagrange method. A hierarchical nonlinear control structure which consists of outer and inner control loops has been utilized. Model Reference Adaptive Controller (MRAC) is designed for the outer loop where the required command signals are generated to force the quadrotor to move on a reference trajectory in the presence of mass uncertainties and reaction forces coming from the manipulator. For the inner loop, the attitude dynamics of the quadrotor and the joint dynamics of the 2-DOF robotic arm are considered as a fully actuated 5-DOF unified part of the AMS. Nonlinear adaptive control has been utilized for the low-level controller where the changes in inertias have been considered. The proposed controller is tested on a high fidelity AMS model in the presence of uncertainties, wind disturbances and measurement noise, and satisfactory trajectory tracking performance with improved robustness is achieved

Model-Based Control of Flying Robots for Robust Interaction under Wind Influence

Model-Based Control of Flying Robots for Robust Interaction under Wind Influence The main goal of this thesis is to bridge the gap between trajectory tracking and interaction control for flying robots in order to allow physical interaction under wind influence by making aerial robots aware of the disturbance, interaction, and faults acting on them. This is accomplished by reasoning about the external wrench (force and torque) acting on the robot, and discriminating (distinguishing) between wind, interactions, and collisions. This poses the following research questions. First, is discrimination between the external wrench components even possible in a continuous real-time fashion for control purposes? Second, given the individual wrench components, what are effective control schemes for interaction and trajectory tracking control under wind influence? Third, how can unexpected faults, such as collisions with the environment, be detected and handled efficiently and effectively? In the interest of the first question, a fourth can be posed: is it possible to obtain a measurement of the wind speed that is independent of the external wrench? In this thesis, model-based methods are applied in the pursuit of answers to these questions. This requires a good dynamics model of the robot, as well as accurately identified parameters. Therefore, a systematic parameter identification procedure for aerial robots is developed and applied. Furthermore, external wrench estimation techniques from the field of robot manipulators are extended to be suitable for aerial robots without the need of velocity measurements, which are difficult to obtain in this context. Based on the external wrench estimate, interaction control techniques (impedance and admittance control) are extended and applied to flying robots, and a thorough stability proof is provided. Similarly, the wrench estimate is applied in a geometric trajectory tracking controller to compensate external disturbances, to provide zero steady-state error under wind influence without the need of integral control action. The controllers are finally combined into a novel compensated impedance controller, to facilitate the main goal of the thesis. Collision detection is applied to flying robots, providing a low level reflex reaction that increases safety of these autonomous robots. In order to identify aerodynamic models for wind speed estimation, flight experiments in a three-dimensional wind tunnel were performed using a custom-built hexacopter. This data is used to investigate wind speed estimation using different data-driven aerodynamic models. It is shown that good performance can be obtained using relatively simple linear regression models. In this context, the propeller aerodynamic power model is used to obtain information about wind speed from available motor power measurements. Leveraging the wind tunnel data, it is shown that power can be used to obtain the wind speed. Furthermore, a novel optimization-based method that leverages the propeller aerodynamics model is developed to estimate the wind speed. Essentially, these two methods use the propellers as wind speed sensors, thereby providing an additional measurement independent of the external force. Finally, the novel topic of simultaneously discriminating between aerodynamic, interaction, and fault wrenches is opened up. This enables the implementation of novel types of controllers that are e.g. compliant to physical interaction, while compensating wind disturbances at the same time. The previously unexplored force discrimination topic has the potential to even open a new research avenue for flying robots

Autonomous Aerial Manipulation Using a Quadrotor

This paper presents an implementation of autonomous indoor aerial gripping using a low-cost, custom-built quadrotor. Such research extends the typical functionality of micro air vehicles (MAV) from passive observation and sensing to dynamic interaction with the environment. To achieve this, three major challenges are overcome: precise positioning, sensing and manipulation of the object, and stabilization in the presence of disturbance due to interaction with the object. Navigation in both indoor and outdoor unstructured, Global Positioning System-denied (GPS-denied) environments is achieved using a visual Simultaneous Localization and Mapping (SLAM) algorithm that relies on an onboard monocular camera. A secondary camera, capable of detecting infrared light sources, is used to estimate the 3D location of the object, while an under-actuated and passively compliant manipulator is designed for effective gripping under uncertainty. The system utilizes nested ProportionalIntegral-Derivative (PID) controllers for attitude stabilization, vision-based navigation, and gripping. The quadrotor is therefore able to autonomously navigate, locate, and grasp an object, using only onboard sensors

Aerodynamic force interactions and measurements for micro quadrotors

Unmanned Aerial Vehicles (UAVs) have become mainstream through the success of several large commercial drone manufacturers. Quadrotors have been widely adopted due to their mechanical simplicity, ability to take off from a small area and hover at a fixed location. As these aircraft are increasingly being used in urban environments and indoors their ability to maintain stable flight in the presence of disturbances and nearby obstacles is of growing importance.Understanding the aerodynamics acting in these environments is the first step to improving quadrotor behaviour. This presents a challenge, as to characterise and verify models of the aerodynamic phenomena it is essential to collect numerous consistent experimental data points. On a typical quadrotor the motor response changes as the battery discharges, leading to variation in flight performance. Typically, this is addressed through the use high gain feedback control regulating attitude and position. To overcome this a unique voltage regulator for quadrotor power was developed to maintain constant supply voltage over the quadrotors flight. This enables the quadrotor to produce consistent and repeatable behaviour as the battery discharges.One way to improve the performance of quadrotors flying in constrained environments with limited sensing is to exploit aerodynamic effects for passive control and stability. Ground effect and rotor inflow damping are two effects of interest: ground effect provides a quadratic increase in thrust as a rotor moves closer to the ground; rotor inflow damping acts to resist axial motion by causing a change thrust opposing the movement. By canting the rotors of a quadrotor these effects were brought from the vertical axis into the lateral axis as well. A canted quadrotor flying over a v-shaped channel was modeled and found to exhibit passive stability in position. A demonstrator aircraft and v-shaped channel were tested in a number of configurations and shown to be stable for a channel slope of 10, 15 or 20 degrees with a rotor cant of 15 or 20 degrees.In order to observe more subtle aerodynamic effects, such as wall effect, it is necessary to have a method to measure rotor forces directly during quadrotor flight. Existing force torque sensors are too bulky, heavy, expensive or insensitive. To overcome these limitations a novel force torque sensor was developed that costs less than $50, weighs 3g and is capable of measuring sub mN forces. These sensors utilise an array of micro-electro-mechanical system (MEMS) barometers encapsulated in rubber to measure the strain field imparted by forces acting on the attached load plate. Mounting force torque sensors under the motors of a quadrotor allows the lateral rotor forces to be transmitted through the motor body and measured as torques at the base.Closely related to this, one of the key limitations faced by quadrotors is their inability to directly measure the airspeed of the aircraft. Providing an oncoming wind speed measurement will allow them to compensate for disturbances improving trajectory tracking and gust rejection. Blade flapping and induced drag are aerodynamic phenomena which relate lateral motion to a force acting in opposition to the rotors motion. By measuring this force using a rotor force sensor the airspeed of the aircraft is computed directly using induced drag and rotor blade flapping models. It was found that lateral velocity could be measured for the velocities tested, up to 1.5m/s, and showed a strong linear relationship to ground truth measurements.The work of this thesis has led to the development of: a quadrotor platform for consistent flight behaviour; a passive position-keeping quadrotor; and a novel rotor force sensor for direct measurement of quadrotor airspeed. These technologies open up avenues to improve the flight performance of quadrotors and better understand subtle aerodynamic interactions in flight

Rotorcraft Flight Dynamics and Control in Wind for Autonomous Sampling of Spatiotemporal Processes

In recent years, there has been significant effort put into the design and use small, autonomous, multi-agent, aerial teams for a variety of military and commercial applications. In particular, small multi-rotor systems have been shown to be especially useful for carrying sensors as they have the ability to rapidly transit between locations as well as hover in place. This dissertation seeks to use multi-agent teams of autonomous rotorcraft to sample spatiotemporal fields in windy conditions. For many sampling objectives, there is the problem of how to accomplish the sampling objective in the presence of strong wind fields caused by external means or by other rotorcraft flying in close proximity. This dissertation develops several flight control strategies for both wind compensation, using nonlinear control techniques, and wind avoidance, using artificial potential-based control. To showcase the utility of teams of unmanned rotorcraft for spatiotemporal sampling, optimal algorithms are developed for two sampling objectives: (1) sampling continuous spatiotemporal fields modeled as Gaussian processes, and (2) optimal motion planning for coordinated target detection, which is an example of a discrete spatiotemporal field. All algorithms are tested in simulation and several are tested in a motion capture based experimental testbed

Nonlinear and Geometric Controllers for Rigid Body Vehicles

In this thesis we investigate the motion control problem for a class of vehicles C V , which includes satellites, quadrotors, underwater vehicles, and tailsitters. Given a globally represented model of C V , and a curve, the motion control problem entails following the curve using control inputs. In this thesis the motion control problem is viewed under two settings, 1) as a local path following problem, 2) as a geometric trajectory tracking problem. We provide solutions to both problems by designing controllers based on the concept of feedback linearization. In the local path following problem, the C V class of vehicles is represented by a local chart. The problem is solved in a monolithic control setting, and the path that needs to be followed is treated as a set to be stabilized. The nonlinear model under study is first dynamically extended and then converted into a fully linear form through a coordinate transformation and smooth feed- back. This approach achieves path invariance. We also design a fault tolerant local controller that ensure path following and path invariance in the presence of a one rotor failure for a quadrotor. The second major problem addressed is the geometric trajectory tracking problem, which is treated in an inner-outer loop setting. Specifically, we design a controller class for the attitude dy- namics of the C V class of vehicles. The novel notion of Lie algebra valued functions are defined on the Special Orthogonal group SO(3), which constitutes a family of functions. This family of functions induces a novel geometric controller class, which consists of almost globally stable and locally stable controllers. This class is designed using the idea of feedback linearization, and is proven to be asymptotically stable through a Lyapunov-like argument. This allows the system to perform multiple flips. We also design geometric controllers for the position loop, which are demonstrated to work with the attitude controller class through simulations with noisy sensor data

Robust Control of Vectored Thrust Aerial Vehicles via Variable Structure Control Methods

The popularity of Unmanned Aerial Vehicles (UAVs) has grown rapidly in many civil and military applications in the last few decades. Recent UAV applications include crop monitoring, terrain mapping and aerial photography, where one or several image sensors attached to the UAV provide important terrain information. A thrust vectoring aerial vehicle, a vehicle with the ability to change the direction of thrust generated while keeping the UAV body at a zero roll and pitch orientation, can serve well in such applications by allowing the sensors to capture stable image data without additional gimbals, reducing the payload and cost while increasing the flight endurance. Furthermore, thrust vectoring UAVs can perform fast forward flight as well as hover operations with non-zero pitch: features which can serve well in military applications. The first part of this research focuses on developing a comprehensive dynamic model and a low level attitude and position control structure for a tri-rotor UAV with thrust vectoring capability, namely the Vectored Thrust Aerial Vehicle. Nonlinear dynamics of UAVs require robust control methods to realize stable flight. Special attention needs to be given to wind gust disturbances, and parametric uncertainties. Sliding Mode Control , a type of Variable Structure Controller, has served well over the years in controlling UAVs and other dynamic systems. However, conventional Sliding Mode Control results in a high frequency switching behavior of the control signal. Furthermore, Sliding Mode Control does not focus on fast set-point regulation or tracking, which can be advantageous for UAVs and many other robotic systems. Taking these research gaps into account, this work presents an Adaptive Variable Structure Control method, which can acquire fast set-point regulation while maintaining robustness against external disturbances and uncertainties. The adaptive algorithm developed in this work is fundamentally different from current Adaptive Sliding Mode Control and other Variable Structure methods. Simulation and experimental results are provided to demonstrate the superiority of the proposed approach compared to Sliding Mode Control. The novel adaptive algorithm is applicable to many nonlinear dynamic systems including UAVs, robot arm manipulators and space robots. The same adaptive concept is then utilized to develop an Adaptive Second Order Sliding Mode Controller. Compared to existing Second Order Sliding Mode Control methods, the proposed methodology is able to produce reduced sliding manifold reach times and consume less amount of control resources: features which are particularly advantageous for systems with limited control resources. Simulations are conducted to evaluate the performance of the proposed Adaptive Second Order Sliding Mode Control algorithm