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

Geometric Tracking Control of a Multi-rotor UAV for Partially Known Trajectories

This paper presents a trajectory-tracking controller for multi-rotor unmanned aerial vehicles (UAVs) in scenarios where only the desired position and heading are known without the higher-order derivatives. The proposed solution modifies the state-of-the-art geometric controller, effectively addressing challenges related to the non-existence of the desired attitude and ensuring positive total thrust input for all time. We tackle the additional challenge of the non-availability of the higher derivatives of the trajectory by introducing novel nonlinear filter structures. We formalize theoretically the effect of these filter structures on the system error dynamics. Subsequently, through a rigorous theoretical analysis, we demonstrate that the proposed controller leads to uniformly ultimately bounded system error dynamics

Unifying Foundation Models with Quadrotor Control for Visual Tracking Beyond Object Categories

Visual control enables quadrotors to adaptively navigate using real-time sensory data, bridging perception with action. Yet, challenges persist, including generalization across scenarios, maintaining reliability, and ensuring real-time responsiveness. This paper introduces a perception framework grounded in foundation models for universal object detection and tracking, moving beyond specific training categories. Integral to our approach is a multi-layered tracker integrated with the foundation detector, ensuring continuous target visibility, even when faced with motion blur, abrupt light shifts, and occlusions. Complementing this, we introduce a model-free controller tailored for resilient quadrotor visual tracking. Our system operates efficiently on limited hardware, relying solely on an onboard camera and an inertial measurement unit. Through extensive validation in diverse challenging indoor and outdoor environments, we demonstrate our system's effectiveness and adaptability. In conclusion, our research represents a step forward in quadrotor visual tracking, moving from task-specific methods to more versatile and adaptable operations

Nonlinear adaptive control of an aerial manipulation system

This paper presents the nonlinear adaptive control of a quadrotor endowed with a 2 degrees of freedom (DOF) manipulator. By considering the quadrotor and the robot arm as a combined system, complete modeling of the aerial manipulation system (AMS) has been presented using the Euler-Lagrange method. A hierarchical nonlinear control scheme 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 uncertainties and reaction forces coming from the manipulator. For the inner loop, the attitude dynamics of the quadrotor and the 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 and the masses have been tackled along with the reaction forces acting on the attitude part of the AMS. The proposed technique has been validated through simulations in two different scenarios

Uncalibrated image-based visual servoing

This paper develops a new method for uncalibrated image-based visual servoing. In contrast to traditional image-based visual servo, the proposed solution does not require a known value of camera focal length for the computation of the image Jacobian. Instead, it is estimated at run time from the observation of the tracked target. The technique is shown to outperform classical visual servoing schemes in situations with noisy calibration parameters and for unexpected changes in the camera zoom. The method’s performance is demonstrated both in simulation experiments and in a ROS implementation of a quadrotor servoing task. The developed solution is tightly integrated with ROS and is made available as part of the IRI ROS stack.Peer ReviewedPostprint (author draft version

Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle

This paper proposes an image-based visual servo (IBVS) controller for the 3D translational motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to provide asymptotic stability for vision-based tracking control of the quadrotor in the presence of uncertainty in the dynamic model of the system. The aim of the paper also includes the use of ow of image features as the velocity information to compensate for the unreliable linear velocity data measured by accelerometers. For this purpose, the mathematical model of the quadrotor is presented based on the optic ow of image features which provides the possibility of designing a velocity-free IBVS controller with considering the dynamics of the robot. The image features are de ned from a suitable combination of perspective image moments without using the model of the object. This property allows the application of the proposed controller in unknown places. The controller is robust with respect to the uncertainties in the transla- tional dynamics of the system associated with the target motion, image depth and external disturbances. Simulation results and a comparison study are presented which demonstrate the e ectiveness of the proposed approach

Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle

This paper proposes an image-based visual servo (IBVS) controller for the 3D translational motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to provide asymptotic stability for vision-based tracking control of the quadrotor in the presence of uncertainty in the dynamic model of the system. The aim of the paper also includes the use of ow of image features as the velocity information to compensate for the unreliable linear velocity data measured by accelerometers. For this purpose, the mathematical model of the quadrotor is presented based on the optic ow of image features which provides the possibility of designing a velocity-free IBVS controller with considering the dynamics of the robot. The image features are de ned from a suitable combination of perspective image moments without using the model of the object. This property allows the application of the proposed controller in unknown places. The controller is robust with respect to the uncertainties in the transla- tional dynamics of the system associated with the target motion, image depth and external disturbances. Simulation results and a comparison study are presented which demonstrate the e ectiveness of the proposed approach

Hybrid Modeling of Deformable Linear Objects for Their Cooperative Transportation by Teams of Quadrotors

his paper deals with the control of a team of unmanned air vehicles (UAVs), specifically quadrotors, for which their mission is the transportation of a deformable linear object (DLO), i.e., a cable, hose or similar object in quasi-stationary state, while cruising towards destination. Such missions have strong industrial applications in the transportation of hoses or power cables to specific locations, such as the emergency power or water supply in hazard situations such as fires or earthquake damaged structures. This control must be robust to withstand strong and sudden wind disturbances and remain stable after aggressive maneuvers, i.e., sharp changes of direction or acceleration. To cope with these, we have previously developed the online adaptation of the proportional derivative (PD) controllers of the quadrotors thrusters, implemented by a fuzzy logic rule system that experienced adaptation by a stochastic gradient rule. However, sagging conditions appearing when the transporting drones are too close or too far away induce singularities in the DLO catenary models, breaking apart the control system. The paper’s main contribution is the formulation of the hybrid selective model of the DLO sections as either catenaries or parabolas, which allows us to overcome these sagging conditions. We provide the specific decision rule to shift between DLO models. Simulation results demonstrate the performance of the proposed approach under stringent conditions.This work has been partially supported by spanish MICIN project PID2020-116346GB-I00, and project KK-2021/00070 of the Elkartek 2021 funding program of the Basque Government. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 777720

Grasping, Perching, And Visual Servoing For Micro Aerial Vehicles

Micro Aerial Vehicles (MAVs) have seen a dramatic growth in the consumer market because of their ability to provide new vantage points for aerial photography and videography. However, there is little consideration for physical interaction with the environment surrounding them. Onboard manipulators are absent, and onboard perception, if existent, is used to avoid obstacles and maintain a minimum distance from them. There are many applications, however, which would benefit greatly from aerial manipulation or flight in close proximity to structures. This work is focused on facilitating these types of close interactions between quadrotors and surrounding objects. We first explore high-speed grasping, enabling a quadrotor to quickly grasp an object while moving at a high relative velocity. Next, we discuss planning and control strategies, empowering a quadrotor to perch on vertical surfaces using a downward-facing gripper. Then, we demonstrate that such interactions can be achieved using only onboard sensors by incorporating vision-based control and vision-based planning. In particular, we show how a quadrotor can use a single camera and an Inertial Measurement Unit (IMU) to perch on a cylinder. Finally, we generalize our approach to consider objects in motion, and we present relative pose estimation and planning, enabling tracking of a moving sphere using only an onboard camera and IMU