An Aerial Manipulator for Robot-to-Robot Torch-Relay Task: System Design and Control Scheme

With the development of rotor aerial robot, it has been widely used as a stabilized flying platform to achieve observation, communication relay and so on by equipping corresponding equipment, which are always called passive tasks. However, many applications need rotor aerial robots to possess more active capability, such as grasp, carry and assemblage. Thus, the demand for an aerial manipulation system gradually appears, and becomes a hot research issue in recent years. Aerial manipulator system, usually composed of rotor aerial robot and the manipulator, is a new type of robot system with active operating capability. Compared with the mobile manipulator based on the ground and underwater mobile robot which is now widely applied, the aerial manipulation has lager working range and better flexibility obviously. Unfortunately, the new aerial manipulation system also brings new challenges, such as strong dynamics coupling, the modeling and stabilization problem, etc. which may affect its further application. Thus, in our work, an actual physical aerial manipulator system is designed and implemented for its system and application research. Based on the system, the preliminary modeling and control was researched and also an experiment for grasping and carry application is conducted. The conclusions of these researches will help us to realize and improve the system in the future.

A key challenge in the use of drones for an aerial manipulation task such as cutting tree branches is the control problem, especially in the presence of an unpredictable and nonlinear environment. While prior work focused on simplifying the problem by modeling a simple interaction with branches and controlling the system with nonlinear and non-robust control schemes, the current work deals with the problem by designing novel robust nonlinear controllers for aerial manipulation systems that are appropriate for vegetation sampling. In this regard, two different potential control schemes are proposed: nonlinear disturbance observer-based control (NDOBC) and adaptive sliding mode control (ASMC). Each considers the external disturbances and unknown parameters in controller design. The proposed control scheme in both methods employs a decoupled architecture that treats the unmanned aerial vehicle and the manipulator arm of the sampler payload as separate units. In the proposed control structures, controllers are designed after comprehensively investigating the dynamics of both the aerial vehicle and the robotic arm. Each system is then controlled independently in the presence of external disturbances, unknown parameter changes, and the nonlinear coupling between the aerial vehicle and robotic arm. In addition, fully actuated and underactuated aerial platforms are examined, and their stability and controllability are compared so as to choose the most practical framework. Finally, the simulation findings verify and compare the performance and effectiveness of the proposed control strategies for a custom aerial manipulation system that has been designed and developed for field trials.

For aerial manipulators, a steady flight must be guaranteed to perform safe interaction with the surrounding environment. This paper focuses on the development of a position control algorithm for an aerial manipulator system (AMS). The position control algorithm is based on the Immersion and Invariance (I&I) theory. The proposed controller maintains the position of the aerial manipulator at the desired point under external and internal disturbances. The control architecture uses a Visual-SLAM technique using on-board sensors for AMS positioning. A series of outdoor experimental tests are performed to demonstrate the effectiveness of the proposed control strategy.

Contact-based aerial interaction control in unknown environments is a challenging issue. To solve this problem, this paper presents an image-based impedance control scheme for an aerial manipulator. Unlike points and image moments, the line features considered in this paper cannot uniquely determine the pose of the onboard camera. Therefore, a nonlinear observer is proposed to online provide supplementary 3D information of the system. After that, a hierarchical tracking controller, which is equipped with an image-space impedance filter, is designed to implement a trajectory tracking task with tunable compliance, while at the same time achieving a subtask that aims to determine the final pose of the aerial manipulator. By planning task-space trajectories, desired interaction behavior can be specified without relying on the global position of the system. Furthermore, the effectiveness criterion of the observer is derived, and the stability of the system is proven. Several experiments, including a push-and-slide task, robustness analysis, and a comparison with the state of the art have been conducted to demonstrate the feasibility of the method. Note to Practitioners—This article presents a method for controlling an aerial manipulator to interact with unknown environments without measuring the global position of both the environment and the aerial manipulator. Furthermore, unlike the existing methods, the proposed visual servoing method is based on line features, which are generally more robust than point features. Moreover, it would be intuitive for users to specify the approaching path and the interaction behavior of the aerial manipulator by just planning the image feature trajectories and the desired distance between the aerial manipulator and the environment. This distance is online estimated using the visual feedback of a monocular camera, instead of relying on any costly 3D-vision sensors or lidars, making it an economical solution for aerial manipulation in field environments.

<p>Traditional aerial manipulation systems were usually composed of rigid-link manipulators attached to an aerial platform, arising several rigidity-related issues such as difficulties of reach, compliant motion, adaptability to object’s shape and pose uncertainties, and safety of human-manipulator interactions, especially in unstructured and confined environments. To address these issues, partially compliant manipulators, composed of rigid links and compliant/flexible joints, were proposed; however, they still suffer from insufficient dexterity and maneuverability. In this article, a new set of compliant aerial manipulators is suggested. For this purpose, the concept of aerial continuum manipulation system (ACMS) is introduced, several conceptual configurations are proposed, and the functionalities of ACMSs for different applications are discussed. Then, the performances of proposed aerial manipulators are compared with conventional aerial manipulators by implementing available benchmarks in the literature. To enhance the comparison, new features with related benchmarks are presented and used for evaluation purposes. In this study, the advantages of ACMSs over their rigid-link counterparts are illustrated and the potential applications of ACMSs are suggested. The open problems such as those related to dynamic coupling and control of ACMSs are also highlighted.</p>

Control of an aerial manipulator is challenging due to the decentralized dynamics of the aerial vehicle and the robotic arm. It is generally complex to adjust the controller of the aerial manipulator when replacing a different robotic arm. This paper presents a flexible control scheme for a quadrotor-based aerial manipulator equipped with a replaceable robotic arm. To analyze the dynamic characteristics during grasping, the model of the aerial manipulator is decentralized including the models of a quadrotor and the centroid of an n-DOF robotic arm. The interaction effect of a moving robotic arm on the quadrotor is considered by analyzing the varying centroid of the robotic arm. Based on the modeling of the aerial manipulator, a control scheme integrating a linear model predictive control (LMPC) and a feedforward controller is presented to accurately control the motion of the aerial platform. The LMPC controls the aerial vehicle to follow the desired trajectory, and a feedforward controller keeps the aerial platform hovering stably during grasping. Practical experiments with two different robotic arms are performed. Experimental results show that the proposed modeling and control scheme provides a flexible and effective approach for an aerial manipulator with a replaceable robotic arm.

Design of a class of generalized parallel mechanisms for adaptive landing and aerial manipulation

Aerial manipulation devices have been increasingly tailored to use at the limit of unmanned aerial vehicle (UAV) technology. The utility value of affordable off-the shelf UAVs for aerial manipulation is relatively unexplored as they often do not meet the performance requirements of coupled manipulator design systems. This paper presents the design and validation of a balanced pantograph manipulator prototype for decoupled use, evaluated with bench tests and and flight tests on a quadrotor UAV. The design exhibits two degrees of freedom (DOF) with a larger range of motion than most preceding decoupled manipulators. The paper also discusses an analytical model which maps the centre of gravity (CG) of all the links of the device in its operational range, allowing fine-tuning of a compact counter mass assembly which operates mechanically to achieve a net-zero stability impact on the UAV. This primary function is ideal for close quarters inspection and contact sensing tasks which engage passively with the environment. Results show that the decoupled pantograph manipulator has no measurable stability impact on the UAV, is appropriate for the use cases described and shows promise for development into a coupled design platform.

This article presents the problem of autonomous control of an unmanned aerial manipulator (UAM) developed for operation with unknown disturbances, wherein the disturbances from the coupling effect between the UAM and the external environment need to be considered. Regarding the coupling force as a disturbance to the entire UAM system, an adaptive prescribed performance control (APPC) scheme utilizing the knowledge of prescribed performance is proposed to guarantee the transient and steady-state performance responses. Also, an adaptive law is designed to estimate the upper boundary parameters of the UAM system uncertainties and disturbances, wherein the restrictive constant boundary assumptions and the prior information of the upper bound are not required in the controller design. Furthermore, to enable safe manipulation in a realistic situation, an end-effector trajectory generation method is presented satisfying the joint angle limitation. For the validation of the proposed method, the simulation results of numerical simulation comparisons are shown. Moreover, experimental scenarios including stable flight and simulated co-work with humans in complex environments are designed to verify the proposed method. <i>Note to Practitioners</i>&#x2014;This article is motivated by the problem of aerial manipulation under unknown disturbances, which may be caused by the wide movement of the manipulator and the sudden loading or unloading of an object. Existing approaches for aerial manipulation often require the assumption of a constant or slowly varying external disturbance. However, a priori bounded disturbance might impose a priori bound on the system state before obtaining closed-loop stability. In this article, the proposed controller with an adaptive law is designed to estimate the upper boundary parameters of the overall disturbances and ensure the predefined performance, so that the prior information of the upper bound of disturbances is not required. The performance of the proposed control strategy is demonstrated via numerical simulation comparisons and experiments, including stale flight and simulated co-work with humans in a complex environment.

This paper proposes a novel aerial manipulator with front cutting effector (AMFCE) to address the aerial physical interaction (APhI) problem. First, the system uncertainty and external disturbance during the system movement and contact operation are estimated by modeling the entire robot and contact position. Next, based on the established model, the nonlinear disturbance observer (NDO) is used to estimate and compensate the unknown external disturbance of the system and the uncertainty of the model parameters in real time. Then, the nonsingular terminal synovial membrane control method is used to suppress the part that is difficult to estimate. Finally, a controller which is suitable for the movement and operation of the entire system is designed. The controller’s performance is verified through experiments, and the results show that the design, modeling, and control of the entire system can achieve the APhI.

Expanding an unmanned aerial vehicle (UAV) with an equipped robotic arm increases the ability of the UAV to actively interact with the environment. During the process of active tasks, precise motion control under model uncertainties and external disturbances is a challenging issue. To solve this issue, an active modeling based control scheme is proposed in this paper. In this scheme, the aerial manipulator system (AMS) is modeled with consideration of various uncertainties represented by the model error and the process noise. The model error caused by the gravity and movement of the manipulator is estimated by the unscented kalman filter (UKF). The estimation is further integrated into a nominal controller to achieve high-precision motion control. Detailed experimental results on the self-bulit testbed illustrate the effectiveness and good performance of the proposed method.

An aerial manipulator system consisting of a quadrotor UAV and a one-DOF manipulator is introduced for contacting operations in the air. As the system is interacting with external environment to do some operations, there will exist contact force. According to the practical aerial contact manipulation features, it is known that an aerial manipulator usually performs operations as the UAV platform is in hover flight or nearby. To realize controlling the force, the hovering UAV acting as a spring-mass-damper system is firstly proved. Then, based on the derived model and the impedance control algorithm, a contact force control method is presented. That is, the position error is controlled in order to control the contact force ultimately. The actual flight experiments show that the developed system is enable to realize the contact force control without a force sensor.

In recent years, tracking of articulated objects at high speed with monocular cameras has been gaining attention. This study presents a novel method for high-frame-rate articulated object tracking with a monocular camera. The method is an extended version of our previous research on high-speed monocular rigid object tracking. In this study, to realize tracking of an articulated object, we integrate dual-quaternion kinematics with our previous fast pixel-wise-posteriors (fast-PWP3D) tracking framework, and propose an auto-regressive (AR) process to encode the dynamic propagation of the estimated state vectors. We give a full three-dimensional derivation of the mathematical formulation of our method and show that our method is capable of tracking an articulated object having a large number of degrees of freedom with only a monocular camera, and is robust against dynamic environmental changes (e.g., illumination/partial occlusion). Moreover, we show an efficient implementation strategy of our method. The results of real-time experiments show that we achieved nearly 350 Hz performance when tracking a four degrees-of-freedom (4-DOF) articulated object with a monocular camera.

This paper focuses on the real-time kinematics solution of an aerial manipulator mounted on an aerial vehicle, the vehicle’s motion isn’t considered in this study. Robot kinematics using Denavit-Hartenberg model was presented. The fundamental scope of this paper is to obtain a global online solution of design configurations with a weighted specific objective function and imposed constraints are fulfilled. Acknowledging the forward kinematics equations of the manipulator; the trajectory planning issue is consequently assigned to on an optimization issue. Several types of computing methods are documented in the literature and are well-known for solving complicated nonlinear functions. Accordingly, this study suggests two kinds of artificial intelligent techniques which are regarded as search methods; they are differential evolution (DE) method and modified shuffled frog-leaping algorithm (MSFLA). These algorithms are constrained metaheuristic and population-based approaches. moreover, they are able to solve the inverse kinematics problem taking into account the mobile platform additionally avoiding singularities since it doesn’t demand the inversion of a Jacobian matrix. Simulation results are carried out for trajectory planning of 6 degree-of-freedom (DOF) kinematically aerial manipulator and confirmed the feasibility and effectiveness of the supposed methods.

Manipulating objects using arms mounted to unmanned aerial vehicles (UAVs) is attractive because UAVs may access many locations that are otherwise inaccessible to traditional mobile manipulation platforms such as ground vehicles. Historically, UAVs have been employed in ways that avoid interaction with the environment at all costs. The recent trend of increasing small UAV lift capacity and the reduction of the weight of manipulator components make the realization of mobile manipulating UAVs imminent. Despite recent work, several major challenges remain to be overcome before it will be common practice to manipulate objects from UAVs. Among these challenges, the constantly moving UAV platform and compliance of manipulator arms make it difficult to position the UAV and end-effector relative to an object of interest precisely enough for reliable manipulation. Solving this challenge will bring UAVs one step closer to being able to perform meaningful tasks such as infrastructure repair, disaster response, law enforcement, and personal assistance. Toward a solution to this challenge, this thesis describes a way forward that uses the UAV as a means to crudely position a manipulator within reach of the end-effector's goal position in the world. The manipulator then performs the fine positioning of the end-effector, rejecting position perturbations caused by UAV motions. An algorithm to coordinate the redundant degrees of freedom of an aerial manipulation system is described that allows the motions of the manipulator to serve as inputs to the UAV's position controller. To demonstrate this algorithm, the manipulator's six degrees of freedom are servoed using visual sensing to drive an eye-in-hand camera to a specified pose relative to a target while treating motions of the host platform as perturbations. Simultaneously, the host platform's degrees of freedom are regulated using kinematic information from the manipulator. This ultimately drives the UAV to a position that allows the manipulator to assume a pose relative to the UAV that maximizes reachability, thus facilitating the arm's ability to compensate for undesired UAV motions. Maintaining this loose kinematic coupling between the redundant degrees of freedom of the host UAV and manipulator allows this type of controller to be applied to a wide variety of platforms, including manned aircraft, rather than a single instance of a purpose-built system. As a result of this loose coupling, careful consideration must be given to the manipulator design so that it can achieve useful poses while minimally influencing the stability of the host UAV. Accordingly, the novel application of a parallel manipulator mechanism is described.