A survey of single and multi-UAV aerial manipulation

Aerial manipulation has direct application prospects in environment, construction, forestry, agriculture, search, and rescue. It can be used to pick and place objects and hence can be used for transportation of goods. Aerial manipulation can be used to perform operations in environments inaccessible or unsafe for human workers. This paper is a survey of recent research in aerial manipulation. The aerial manipulation research has diverse aspects, which include the designing of aerial manipulation platforms, manipulators, grippers, the control of aerial platform and manipulators, the interaction of aerial manipulator with the environment, through forces and torque. In particular, the review paper presents the survey of the airborne platforms that can be used for aerial manipulation including the new aerial platforms with aerial manipulation capability. We also classified the aerial grippers and aerial manipulators based on their designs and characteristics. The recent contributions regarding the control of the aerial manipulator platform is also discussed. The environment interaction of aerial manipulators is also surveyed which includes, different strategies used for end-effectors interaction with the environment, application of force, application of torque and visual servoing. A recent and growing interest of researchers about the multi-UAV collaborative aerial manipulation was also noticed and hence different strategies for collaborative aerial manipulation are also surveyed, discussed and critically analyzed. Some key challenges regarding outdoor aerial manipulation and energy constraints in aerial manipulation are also discussed

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

Experiments on coordinated motion of aerial robotic manipulators

In this paper a three layer control architecture for multiple aerial robotic manipulators is presented. The top layer, on the basis of the desired mission, determines the end-effector desired trajectory for each manipulator, while the middle layer is in charge of computing the motion references in order to track such end-effectors trajectories coming from the upper layer. Finally the bottom layer is a low level motion controller, which tracks the motion references. The overall mission is decomposed in a set of elementary behaviors which are combined together, through the Null Space-based Behavioral (NSB) approach, into more complex compounds behaviors. The proposed framework has been tested conducting an experimental campaign