미지 환경에서의 안전 비행 운송을 위한 협업제어 및 경로생성 기법

학위논문 (박사)-- 서울대학교 대학원 공과대학 기계항공공학부, 2017. 8. 김현진.Recently, aerial manipulators using unmanned aerial vehicles (UAVs) are receiving attention due to their superior mobility in three-dimensional space. It can be applied to a wide range of applications such as inspection of hard-to-reach structure or aerial transportation. This dissertation presents a viable approach to safe aerial transportation in unknown environments by using multiple aerial manipulators. Unlike existing approaches for cooperative manipulation based on force decomposition or impedance-based control that often requ- ire heavy or expensive force/torque sensors, this dissertation suggests a method without such sensors, by exploiting the decoupled dynamics to develop estimation and control alg- orithms. With the decoupled dynamics and the assumption of rigid grasp, an online estimator is designed initially to estimate the mass and inertial properties of an unknown payload using the states of the aerial manipulator only. Stable adaptive controller based on the online estimated parameter is then designed using Lyapunov methods. Through simulations, the performance of the proposed controller is compared with conventional passivity-based adaptive algorithms. This dissertation also proposes a motion generation algorithm for cooperative manipulators to transport a payload safely. If the payload is excessively heavy in comparison with the transportation ability of an aerial robot, an aerial robot may crash because of actuation limits on the motors. As a first step, the allowable flight envelope is analyzed with respect to the position of the end-effector. In order to keep the end-effector in the allowable fight region, kinematic coordination between a payload and cooperative aerial manipulators is first studied. A two-layer framework, in which the first layer computes the motion reference of the end-effectors and the second layer calculates the joint motion of the corresponding manipulator, is then developed in a task-prioritized fashion. When generating aerial manipulator trajectories, the desired trajectory is calculated to satisfy the unilateral constraints obtained by the allowable flight envelope. This work also considers the obstacle avoidance of cooperative aerial manipulators in unknown environments. Using the relative distance between an aerial robot and an obstacle as measured by an RGB-D camera and point cloud library (PCL), dynamic movement primitives (DMPs) modify the desired trajectory. By having the leader robot detect an obstacle and the follower robots maintain a given relative distance with the leader, improved efficiency of obstacle avoidance for cooperative robots can be achieved. Finally, the proposed synthesis of estimation, control, and planning algorithms are validated with experiments using custom-made aerial manipulators combined with a two-DOF (Degree Of Freedom) robotic arm. The proposed method is validated with trajectory tracking using two types of payloads. Cooperative aerial transportation in unknown environments is also performed with an unknown obstacle. Both experimental results suggest that the proposed approach can be utilized for safe cooperative aerial transportation.1 Introduction 1 1.1 Background and Motivations 1 1.2 Literature Survey 4 1.2.1 Cooperative Manipulation 4 1.2.2 Handling an Unknown Object 7 1.2.3 Obstacle Avoidance for Cooperative Robots 8 1.3 Research Objectives and Contributions 9 1.3.1 Estimation and Control Algorithm 10 1.3.2 Motion Planning within the Allowable Flight Envelope 11 1.3.3 Real-time Obstacle Avoidance using an RGB-D Camera 11 1.4 Thesis Organization 12 2 Background 14 2.1 Dynamics for Cooperative Aerial Manipulator 14 2.1.1 Rigid Body Statics 15 2.1.2 Dynamics for Single Aerial Manipulator 16 2.1.3 Decoupled Dynamics 19 2.2 Task Priority 22 2.3 DMPs 24 3 Estimator and Controller Design 26 3.1 Payload Mass and Inertia Parameter Estimation 28 3.1.1 System Parametrization 28 3.1.2 On-line Parameter Estimator 29 3.1.3 Robust Analysis for Measurement Noise 32 3.2 Controller Design 34 3.3 Simulation Results 40 4 Path Planning 45 4.1 Allowable Payload for Each Aerial Manipulator 45 4.2 Trajectory Generation with Unilateral Constraints 49 4.2.1 End-eector Trajectory Generation 49 4.2.2 Inverse Kinematics with Null Space Approach 49 4.2.3 Task Prioritization with Unilateral Constraints 56 5 Obstacle Avoidance in Unknown Environments 60 5.1 Obstacle Detection 60 5.2 Movement Primitives for Cooperative Aerial Manipulators 64 6 Experimental Validation and Results 71 6.1 Simulation Validation for Moving Obstacle 71 6.2 Experimental Setup 74 6.3 Experiment for Cooperative Aerial Transportation 77 6.3.1 Path Following with Two Types of Payloads 77 6.3.2 Aerial Transportations in Unknown Environments 78 7 Conclusions 93 Abstract (in Korean) 105Docto

모션 프리머티브를 이용한 복잡한 로봇 임무 학습 및 일반화 기법

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 항공우주공학과, 2020. 8. 김현진.Learning from demonstrations (LfD) is a promising approach that enables robots to perform a specific movement. As robotic manipulations are substituting a variety of tasks, LfD algorithms are widely used and studied for specifying the robot configurations for the various types of movements. This dissertation presents an approach based on parametric dynamic movement primitives (PDMP) as a motion representation algorithm which is one of relevant LfD techniques. Unlike existing motion representation algorithms, this work not only represents a prescribed motion but also computes the new behavior through a generalization of multiple demonstrations in the actual environment. The generalization process uses Gaussian process regression (GPR) by representing the nonlinear relationship between the PDMP parameters that determine motion and the corresponding environmental variables. The proposed algorithm shows that it serves as a powerful optimal and real-time motion planner among the existing planning algorithms when optimal demonstrations are provided as dataset. In this dissertation, the safety of motion is also considered. Here, safety refers to keeping the system away from certain configurations that are unsafe. The safety criterion of the PDMP internal parameters are computed to check the safety. This safety criterion reflects the new behavior computed through the generalization process, as well as the individual motion safety of the demonstration set. The demonstrations causing unsafe movement are identified and removed. Also, the demolished demonstrations are replaced by proven demonstrations upon this criterion. This work also presents an extension approach reducing the number of required demonstrations for the PDMP framework. This approach is effective where a single mission consists of multiple sub-tasks and requires numerous demonstrations in generalizing them. The whole trajectories in provided demonstrations are segmented into multiple sub-tasks representing unit motions. Then, multiple PDMPs are formed independently for correlated-segments. The phase-decision process determines which sub-task and associated PDMPs to be executed online, allowing multiple PDMPs to be autonomously configured within an integrated framework. GPR formulations are applied to obtain execution time and regional goal configuration for each sub-task. Finally, the proposed approach and its extension are validated with the actual experiments of mobile manipulators. The first two scenarios regarding cooperative aerial transportation demonstrate the excellence of the proposed technique in terms of quick computation, generation of efficient movement, and safety assurance. The last scenario deals with two mobile manipulations using ground vehicles and shows the effectiveness of the proposed extension in executing complex missions.시연 학습 기법(Learning from demonstrations, LfD)은 로봇이 특정 동작을 수행할 수 있도록 하는 유망한 동작 생성 기법이다. 로봇 조작기가 인간 사회에서 다양한 업무를 대체해 감에 따라, 다양한 임무를 수행하는 로봇의 동작을 생성하기 위해 LfD 알고리즘들은 널리 연구되고, 사용되고 있다. 본 논문은 LfD 기법 중 모션 프리머티브 기반의 동작 재생성 알고리즘인 Parametric dynamic movement primitives(PDMP)에 기초한 알고리즘을 제시하며, 이를 통해 다양한 임무를 수행하는 모바일 조작기의 궤적을 생성한다. 기존의 동작 재생성 알고리즘과 달리, 이 연구는 제공된 시연에서 표현된 동작을 단순히 재생성하는 것에 그치지 않고, 새로운 환경에 맞게 일반화 하는 과정을 포함한다. 이 논문에서 제시하는 일반화 과정은 PDMPs의 내부 파라미터 값인 스타일 파라미터와 환경 변수 사이의 비선형 관계를 가우스 회귀 기법 (Gaussian process regression, GPR)을 이용하여 수식적으로 표현한다. 제안된 기법은 또한 최적 시연를 학습하는 방식을 통해 강력한 최적 실시간 경로 계획 기법으로도 응용될 수 있다. 본 논문에서는 또한 로봇의 구동 안전성도 고려한다. 기존 연구들에서 다루어진 시연 관리 기술이 로봇의 구동 효율성을 개선하는 방향으로 제시된 것과 달리, 이 연구는 강한 구속조건으로 로봇의 구동 안전성을 확보하는 시연 관리 기술을 통해 안정성을 고려하는 새로운 방식을 제시한다. 제안된 방식은 스타일 파라미터 값 상에서 안전성 기준을 계산하며, 이 안전 기준을 통해 시연을 제거하는 일련의 작업을 수행한다. 또한, 제거된 시위를 안전 기준에 따라 입증된 시위로 대체하여 일반화 성능을 저하시키지 않도록 시위를 관리한다. 이를 통해 다수의 시연 각각 개별 동작 안전성 뿐 아니라 온라인 동작의 안전성까지 고려할 수 있으며, 실시간 로봇 조작기 운용시 안전성이 확보될 수 있다. 제안된 안정성을 고려한 시연 관리 기술은 또한 환경의 정적 설정이 변경되어 모든 시연을 교체해야 할 수 있는 상황에서 사용할 수 있는 시연들을 판별하고, 효율적으로 재사용하는 데 응용할 수 있다. 또한 본 논문은 복잡한 임무에서 적용될 수 있는 PDMPs의 확장 기법인 seg-PDMPs를 제시한다. 이 접근방식은 복잡한 임무가 일반적으로 복수개의 간단한 하위 작업으로 구성된다고 가정한다. 기존 PDMPs와 달리 seg-PDMPs는 전체 궤적을 하위 작업을 나타내는 여러 개의 단위 동작으로 분할하고, 각 단위동작에 대해 여러개의 PDMPs를 구성한다. 각 단위 동작 별로 생성된 PDMPs는 통합된 프레임워크내에서 단계 결정 프로세스를 통해 자동적으로 호출된다. 각 단계 별로 단위 동작을 수행하기 위한 시간 및 하위 목표점은 가우스 공정 회귀(GPR)를 이용한 환경변수와의의 관계식을 통해 얻는다. 결과적으로, 이 연구는 전체적으로 요구되는 시연의 수를 효과적으로 줄일 뿐 아니라, 각 단위동작의 표현 성능을 개선한다. 제안된 알고리즘은 협동 모바일 로봇 조작기 실험을 통하여 검증된다. 세 가지의 시나리오가 본 논문에서 다루어지며, 항공 운송과 관련된 첫 두 가지 시나리오는 PDMPs 기법이 로봇 조작기에서 빠른 적응성, 임무 효율성과 안전성 모두 만족하는 것을 입증한다. 마지막 시나리오는 지상 차량을 이용한 두 개의 로봇 조작기에 대한 실험으로 복잡한 임무 수행을 하기 위해 확장된 기법인 seg-PDMPs가 효과적으로 변화하는 환경에서 일반화된 동작을 생성함을 검증한다.1 Introduction 1 1.1 Motivations 1 1.2 Literature Survey 3 1.2.1 Conventional Motion Planning in Mobile Manipulations 3 1.2.2 Motion Representation Algorithms 5 1.2.3 Safety-guaranteed Motion Representation Algorithms 7 1.3 Research Objectives and Contributions 7 1.3.1 Motion Generalization in Motion Representation Algorithm 9 1.3.2 Motion Generalization with Safety Guarantee 9 1.3.3 Motion Generalization for Complex Missions 10 1.4 Thesis Organization 11 2 Background 12 2.1 DMPs 12 2.2 Mobile Manipulation Systems 13 2.2.1 Single Mobile Manipulation 14 2.2.2 Cooperative Mobile Manipulations 14 2.3 Experimental Setup 17 2.3.1 Test-beds for Aerial Manipulators 17 2.3.2 Test-beds for Robot Manipulators with Ground Vehicles 17 3 Motion Generalization in Motion Representation Algorithm 22 3.1 Parametric Dynamic Movement Primitives 22 3.2 Generalization Process in PDMPs 26 3.2.1 Environmental Parameters 26 3.2.2 Mapping Function 26 3.3 Simulation Results 29 3.3.1 Two-dimensional Hurdling Motion 29 3.3.2 Cooperative Aerial Transportation 30 4 Motion Generalization with Safety Guarantee 36 4.1 Safety Criterion in Style Parameter 36 4.2 Demonstration Management 39 4.3 Simulation Validation 42 4.3.1 Two-dimensional Hurdling Motion 46 4.3.2 Cooperative Aerial Transportation 47 5 Motion Generalization for Complex Missions 51 5.1 Overall Structure of Seg-PDMPs 51 5.2 Motion Segments 53 5.3 Phase-decision Process 54 5.4 Seg-PDMPs for Single Phase 54 5.5 Simulation Results 55 5.5.1 Initial/terminal Offsets 56 5.5.2 Style Generalization 59 5.5.3 Recombination 61 6 Experimental Validation and Results 63 6.1 Cooperative Aerial Transportation 63 6.2 Cooperative Mobile Hang-dry Mission 70 6.2.1 Demonstrations 70 6.2.2 Simulation Validation 72 6.2.3 Experimental Results 78 7 Conclusions 82 Abstract (in Korean) 93Docto

Closed-Loop Behavior of an Autonomous Helicopter Equipped with a Robotic Arm for Aerial Manipulation Tasks

This paper is devoted to the control of aerial robots interacting physically with objects in the environment and with other aerial robots. The paper presents a controller for the particular case of a small‐scaled autonomous helicopter equipped with a robotic arm for aerial manipulation. Two types of influences are imposed on the helicopter from a manipulator: coherent and non ‐ coherent influence. In the former case, the forces and torques imposed on the helicopter by the manipulator change with frequencies close to those of the helicopter movement. The paper shows that even small interaction forces imposed on the fuselage periodically in proper phase could yield to low frequency instabilities and oscillations, so called phase circle

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

An Omnidirectional Aerial Platform for Multi-Robot Manipulation

The objectives of this work were the modeling, control and prototyping of a new fully-actuated aerial platform. Commonly, the multirotor aerial platforms are under-actuated vehicles, since the total propellers thrust can not be directed in every direction without inferring a vehicle body rotation. The most common fully-actuated aerial platforms have tilted or tilting rotors that amplify the aerodynamic perturbations between the propellers, reducing the efficiency and the provided thrust. In order to overcome this limitation a novel platform, the ODQuad (OmniDirectional Quadrotor), has been proposed, which is composed by three main parts, the platform, the mobile and rotor frames, that are linked by means of two rotational joints, namely the roll and pitch joints. The ODQuad is able to orient the total thrust by moving only the propellers frame by means of the roll and pitch joints. Kinematic and dynamic models of the proposed multirotor have been derived using the Euler- Lagrange approach and a model-based controller has been designed. The latter is based on two control loops: an outer loop for vehicle position control and an inner one for vehicle orientation and roll-pitch joint control. The effectiveness of the controller has been tested by means of numerical simulations in the MATLAB c SimMechanics environment. In particular, tests in free motion and in object transportation tasks have been carried out. In the transportation task simulation, a momentum based observer is used to estimate the wrenches exchanged between the vehicle and the transported object. The ODQuad concept has been tested also in cooperative manipulation tasks. To this aim, a simulation model was considered, in which multiple ODQuads perform the manipulation of a bulky object with unknown inertial parameters which are identified in the first phase of the simulation. In order to reduce the mechanical stresses due to the manipulation and enhance the system robustness to the environment interactions, two admittance filters have been implemented: an external filter on the object motion and an internal one local for each multirotor. Finally, the prototyping process has been illustrated step by step. In particular, three CAD models have been designed. The ODQuad.01 has been used in the simulations and in a preliminary static analysis that investigated the torque values for a rough sizing of the roll-pitch joint actuators. Since in the ODQuad.01 the components specifications and the related manufacturing techniques have not been taken into account, a successive model, the ODQuad.02, has been designed. The ODQuad.02 design can be developed with aluminum or carbon fiber profiles and 3D printed parts, but each component must be custom manufactured. Finally, in order to shorten the prototype development time, the ODQuad.03 has been created, which includes some components of the off-the-shelf quadrotor Holybro X500 into a novel custom-built mechanical frame