Robust hovering and trajectory tracking control of a quadrotor helicopter using acceleration feedback and a novel disturbance observer

Hovering and trajectory tracking control of rotary-wing aircrafts in the presence of uncertainties and external disturbances is a very challenging task. This thesis focuses on the development of the robust hovering and trajectory tracking control algorithms for a quadrotor helicopter subject to both periodic and aperiodic disturbances along with noise and parametric uncertainties. A hierarchical control structure is employed where high-level position controllers produce reference attitude angles for the low-level attitude controllers. Reference attitude angles are usually determined analytically from the position command signals that control the positional dynamics. However, such analytical formulas may produce large and non-smooth reference angles which must be saturated and low-pass filtered. In this thesis, desired attitude angles are determined numerically using constrained nonlinear optimization where certain magnitude and rate constraints are imposed. Furthermore, an acceleration based disturbance observer (AbDOB) is designed to estimate and suppress disturbances acting on the positional dynamics of the quadrotor. For the attitude control, a nested position, velocity, and inner acceleration feedback control structure consisting of PID and PI type controllers are developed to provide high sti ness against external disturbances. Reliable angular acceleration is estimated through an extended Kalman filter (EKF) cascaded with a classical Kalman lter (KF). This thesis also proposes a novel disturbance observer which consists of a bank of band-pass filters connected parallel to the low-pass filter of a classical disturbance observer. Band-pass filters are centered at integer multiples of the fundamental frequency of the periodic disturbance. Number and bandwidth of the band-pass filters are two crucial parameters to be tuned in the implementation of the new structure. Proposed disturbance observer is integrated with a sliding mode controller to tackle the robust hovering and trajectory tracking control problem. The sensitivity of the proposed disturbance observer based control system to the number and bandwidth of the band-pass filters are thoroughly investigated via several simulations. Simulations are carried out on a high delity model where sensor biases and measurement noise are also considered. Results show that the proposed controllers are very effective in providing robust hovering and trajectory tracking performance when the quadrotor helicopter is subject to the wind gusts generated by the Dryden wind model along with plant uncertainties and measurement noise. A comparison with the classical disturbance observer-based control is also provided where better tracking performance with improved robustness is achieved in the presence of noise and external disturbance

Tracking and Grasping of Moving Objects Using Aerial Robotic Manipulators: A Brief Survey

Unmanned Aerial Vehicles (UAV) has evolved in recent years, their features have changed to be more useful to the society, although some years ago the drones had been thought to be teleoperated by humans and to take some pictures from above, which is useful; nevertheless, nowadays the drones are capable of developing autonomous tasks like tracking a dynamic target or even grasping different kind of objects. Some task like transporting heavy loads or manipulating complex shapes are more challenging for a single UAV, but for a fleet of them might be easier. This brief survey presents a compilation of relevant works related to tracking and grasping with aerial robotic manipulators, as well as cooperation among them. Moreover, challenges and limitations are presented in order to contribute with new areas of research. Finally, some trends in aerial manipulation are foreseeing for different sectors and relevant features for these kind of systems are standing out

A Bayesian optimization framework for the automatic tuning of MPC-based shared controllers

This paper presents a Bayesian optimization framework for the automatic tuning of shared controllers which are defined as a Model Predictive Control (MPC) problem. The proposed framework includes the design of performance metrics as well as the representation of user inputs for simulation-based optimization. The framework is applied to the optimization of a shared controller for an Image Guided Therapy robot. VR-based user experiments confirm the increase in performance of the automatically tuned MPC shared controller with respect to a hand-tuned baseline version as well as its generalization ability

비선형 최적화를 이용한 멀티로터 현수 운송의 경로 계획 및 제어 기법

학위논문(박사) -- 서울대학교대학원 : 공과대학 기계항공공학부, 2021.8. 김현진.경로 계획과 제어는 안전하고 안정적으로 멀티로터를 운용하기 위해서 필수적인 요소이다. 충돌을 회피하며 효율적인 경로를 생성하고 이를 실제로 추종하기 위해서는 동역학 모델이 고려되어야 한다. 일반 멀티로터의 동역학 모델은 높은 차원을 가진 비선형식으로 표현되는데, 현수 운송 물체를 추가할 경우 계산이 더욱 복잡해진다. 본 논문은 멀티로터를 이용한 현수 운송에 있어 경로 계획과 제어에 대한 효율적인 기법을 제안한다. 첫 번째로 단일 멀티로터를 이용한 현수 운송을 다룬다. 물체가 별도의 엑츄에이터 없이 운송될 경우 물체는 기체의 움직임에 의해서만 제어가 가능하다. 하지만, 동역학식의 높은 비선형성으로 운용에 어려움이 존재한다. 이를 경감시키기 위해서 회전 동역학식의 비선형성을 줄이고 자세 제어에 존재하는 시간 지연을 고려하여 동역학식을 간소화한다. 경로 계획에 있어서는 충돌 회피를 위해 기체, 케이블, 그리고 운송 물체를 다른 크기와 모양을 가진 타원체들로 감싸며, 효과적이면서도 덜 보수적인 방식으로 충돌 회피 구속조건을 부과한다. Augmented Lagrangian 방법을 이용하여 비선형 구속조건이 부과된 비선형 문제를 실시간 최적화하여 경로를 생성한다. 생성된 경로를 추종하기 위해서 Sequential linear quadratic 솔버를 이용한 모델 예측 제어기로 최적 제어 입력을 계산한다. 제안된 기법은 여러 시뮬레이션과 실험을 통해 검증한다. 다음으로, 다중 멀티로터를 이용한 협업 현수 운송 시스템을 다룬다. 해당 시스템의 상태 변수나 동역학식에서 연결된(coupled) 항의 개수는 기체의 수에 비례하여 증가하기 때문에, 효과적인 기법 없이는 최적화에 많은 시간이 소요된다. 높은 비선형성을 가진 동역학식의 복잡성을 낮추기 위하여 미분 평탄성을 사용한다. 경로 또한 piece-wise Bernstein 다항식을 이용하여 매개변수화하여 최적화 변수의 개수를 줄인다. 최적화 문제를 분해하고 충돌 회피 구속조건들에 대해 볼록화(convexification)를 수행하여 운송 물체의 경로와 장력의 경로에 대한 볼록한(convex) 하위문제들이 만들어진다. 첫 번째 하위문제인 물체 경로 생성에서는, 장애물 회피와 멀티로터의 공간을 확보하기 위하여 안전 비행 통로(safe flight corridor, SFC)와 여유 간격 구속조건을 고려하여 최적화한다. 다음으로, 장력 벡터들의 경로는 장애물 회피와 상호 충돌을 방지하기 위하여 안전 비행 섹터(safe flight sector, SFS)와 상대 안전 비행 섹터(relative safe flight sector, RSFS) 구속조건을 부과하여 최적화한다. 시뮬레이션과 실험으로 복잡한 환경에서 효율적인 경로 계획 기법을 시연하며 검증한다.Trajectory generation and control are fundamental requirements for safe and stable operation of multi-rotors. The dynamic model should be considered to generate efficient and collision-free trajectories with feasibility. While the dynamic model of a bare multi-rotor is expressed non-linearly with high dimensions which results in computational loads, the suspended load increases the complexity further. This dissertation presents efficient algorithms for trajectory generation and control of multi-rotors with a suspended load. A single multi-rotor with a suspended load is addressed first. Since the load is suspended through a cable without any actuator, movement of the load must be controlled via maneuvers of the multi-rotor. However, the highly non-linear dynamics of the system results in difficulties. To relive them, the rotational dynamics is simplified to reduce the non-linearity and consider the delay in attitude control. For trajectory generation, the vehicle, cable, and load are considered as ellipsoids with different sizes and shapes, and collision-free constraints are expressed in an efficient and less-conservative way. The augmented Lagrangian method is applied to solve a nonlinear optimization problem with nonlinear constraints in real-time. Model predictive control with the sequential linear quadratic solver is used to track the generated trajectories. The proposed algorithm is validated with several simulations and experiment. A system with multiple multi-rotors for cooperative transportation of a suspended load is addressed next. As the system has more state variables and coupling terms in the dynamic equation than the system with a single multi-rotor, optimization takes a long time without an efficient method. The differential flatness of the system is used to reduce the complexity of the highly non-linear dynamic equation. The trajectories are also parameterized using piece-wise Bernstein polynomials to decrease the number of optimization variables. By decomposing an optimization problem and performing convexification, convex sub-problems are formulated for the load and the tension trajectories optimization, respectively. In each sub-problem, a light-weight sampling method is used to find a feasible and low-cost trajectory as initialization. In the first sub-problem, the load trajectory is optimized with safe flight corridor (SFC) and clearance constraints for collision avoidance and security of space for the multi-rotors. Then, the tension histories are optimized with safe flight sector (SFS) and relative safe flight sector (RSFS) constraints for obstacle and inter-agent collision avoidance. Simulations and experiments are conducted to demonstrate efficient trajectory generation in a cluttered environment and validate the proposed algorithms.Chapter 1 Introduction 1 1.1 Literature Survey 5 1.2 Contributions 9 1.3 Outline 10 Chapter 2 Single Multi-rotor with a Suspended Load 11 2.1 Dynamics 11 2.2 Trajectory Generation 23 2.3 Optimal Control 31 Chapter 3 Multiple Multi-rotors with a Suspended Load 36 3.1 Problem Setting 36 3.2 Load Trajectory Generation 45 3.3 Tension History Generation 54 Chapter 4 Experimental Validation 68 4.1 Single Multi-rotor with a Suspended Load 68 4.2 Multiple Multi-rotors with a Suspended Load 79 Chapter 5 Conclusion 100 Appendix A Detailed Derivation of Dierential Flatness 102 B Preliminaries of Bernstein Polynomials 108 B.1 Denition of a Bernstein Polynomial 108 B.2 Convex hull property of a Bernstein Polynomial 110 B.3 Representation of a General Polynomial with Bernstein Basis Polynomials 111 B.4 Representation of the Derivative of a Bernstein Polynomial with Bernstein Basis Polynomials 112 References 113 Abstract (in Korean) 119박

A Human-Embodied Drone for Dexterous Aerial Manipulation

Current drones perform a wide variety of tasks in surveillance, photography, agriculture, package delivery, etc. However, these tasks are performed passively without the use of human interaction. Aerial manipulation shifts this paradigm and implements drones with robotic arms that allow interaction with the environment rather than simply sensing it. For example, in construction, aerial manipulation in conjunction with human interaction could allow operators to perform several tasks, such as hosing decks, drill into surfaces, and sealing cracks via a drone. This integration with drones will henceforth be known as dexterous aerial manipulation. Our recent work integrated the worker’s experience into aerial manipulation using haptic technology. The net effect was such a system could enable the worker to leverage drones and complete tasks while utilizing haptics on the task site remotely. However, the tasks were completed within the operator’s line-of-sight. Until now, immersive AR/VR frameworks has rarely been integrated in aerial manipulation. Yet, such a framework allows the drones to embody and transport the operator’s senses, actions, and presence to a remote location in real-time. As a result, the operator can both physically interact with the environment and socially interact with actual workers on the worksite. This dissertation presents a human-embodied drone interface for dexterous aerial manipulation. Using VR/AR technology, the interface allows the operator to leverage their intelligence to collaboratively perform desired tasks anytime, anywhere with a drone that possesses great dexterity

Motion Planning of UAV Swarm: Recent Challenges and Approaches

The unmanned aerial vehicle (UAV) swarm is gaining massive interest for researchers as it has huge significance over a single UAV. Many studies focus only on a few challenges of this complex multidisciplinary group. Most of them have certain limitations. This paper aims to recognize and arrange relevant research for evaluating motion planning techniques and models for a swarm from the viewpoint of control, path planning, architecture, communication, monitoring and tracking, and safety issues. Then, a state-of-the-art understanding of the UAV swarm and an overview of swarm intelligence (SI) are provided in this research. Multiple challenges are considered, and some approaches are presented. Findings show that swarm intelligence is leading in this era and is the most significant approach for UAV swarm that offers distinct contributions in different environments. This integration of studies will serve as a basis for knowledge concerning swarm, create guidelines for motion planning issues, and strengthens support for existing methods. Moreover, this paper possesses the capacity to engender new strategies that can serve as the grounds for future work

Towards autonomy of a quadrotor UAV

As the potential of unmanned aerial vehicles rapidly increases, there is a growing interest in rotary vehicles as well as fixed wing. The quadrotor is small agile rotary vehicle controlled by variable speed prop rotors. With no need for a swash plate the vehicle is low cost as well as dynamically simple. In order to achieve autonomous flight, any potential control algorithm must include trajectory generation and trajectory following. Trajectory generation can be done using direct or indirect methods. Indirect methods provide an optimal solution but are hard to solve for anything other than the simplest of cases. Direct methods in comparison are often sub-optimal but can be applied to a wider range of problems. Trajectory optimization is typically performed within the control space, however, by posing the problem in the output space, the problem can be simplified. Differential flatness is a property of some dynamical systems which allows dynamic inversion and hence, output space optimization. Trajectory following can be achieved through any number of linear control techniques, this is demonstrated whereby a single trajectory is followed using LQR, this scheme is limited however, as the vehicle is unable to adapt to environmental changes. Model based predictive control guarantees constraint satisfaction at every time step, this however is time consuming and therefore, a combined controller is proposed benefiting from the adaptable nature of MBPC and the robustness and simplicity of LQR control. There are numerous direct methods for trajectory optimization both in the output and control space. Taranenko’s direct method has a number of benefits over other techniques, including the use of a virtual argument, which separates the optimal path and the speed problem. This enables the algorithm to solve the optimal time problem, the optimal fuel problem or a combination of the two, without a deviation from the optimal path. In order to implement such a control scheme, the issues of feedback, communication and control action computation, require consideration. This work discusses the issues with instrumentation and communication encountered when developing the control system and provides open loop test results. This work also extends the proposed control schemes to consider the problem of multiple vehicle flight rendezvous. Specifically the problem of rendezvous when there is no communication link, limited visibility and no agreed rendezvous point. Using Taranenko’s direct method multiple vehicle rendezvous is simulated.EThOS - Electronic Theses Online ServiceGBUnited Kingdo