Optimal Joint Space Control of a Cable-Driven Aerial Manipulator

This article proposes a novel method for maintaining the trajectory of an aerial manipulator by utilizing a fast nonsingular terminal sliding mode(FNTSM)manifold and a linear extended state observer(LESO).The developed controlmethod applies an FNTSMto ensure the tracking performance’s control accuracy,and an LESO to estimate the system’s unmodeled dynamics and external disturbances.Additionally,an improved salp swarm algorithm(ISSA)is employed to parameter tune the suggested controller by integrating the salp swarmtechnique with a cloud model.This approach also uses a model-free scheme to reduce the complexity of controller design without relying on complex and precise dynamics models.The simulation results show that the proposed controller outperforms linear active rejection disturbance control and PID controllers in terms of transient performance and resilience against lumped disturbances,and the ISSA can help the proposed controller find optimal control parameters.

Observer-Based Control for a Cable-Driven Aerial Manipulator under Lumped Disturbances

With the increasing demand for interactive aerial operations,the application of aerial manipulators is becoming more promising.However,there are a few critical problems on how to improve the energetic efficiency and pose control of the aerialmanipulator forpractical application.In this paper,a novel cable-drivenaerialmanipulatorused for remote water sampling is proposed and then its rigid-flexible coupling dynamics model is constructed which takes joint flexibility into account.To achieve high precision joint position tracking under lumped disturbances,a newly controller,which consists of three parts:linear extended state observer,adaptive super-twisting strategy,and fractional-order nonsingular terminal sliding mode control,is proposed.The linear extended state observer is adopted to approximate unmeasured states and unknown lumped disturbances and achieve model-free control structure.The adaptive super-twisting strategy and fractional-order nonsingular terminal sliding mode control are combined together to achieve good control performance and counteract chattering problem.The Lyapunovmethod is utilized to prove the overall stability and convergence of the system.Lastly,various visualization simulations and ground experiments are conducted,verifying the effectiveness of our strategy,and all outcomes demonstrate its superiorities over the existing control strategies.

Active fault-tolerant control scheme of aerial manipulators with actuator faults

In this paper,an active fault-tolerant control(FTC)strategy of aerial manipulators based on non-singular terminal sliding mode(NTSM)and extended state observer(ESO)is proposed.Firstly,back-stepping technology is adopted as the control framework to ensure the global asymptotic stability of the closed-loop system.Next,the NTSM with estimated parameters of actuator faults is used as main robustness controller to deal with actuator faults.Then,the ESO is utilized to estimate and compensate the complex coupling effects and external disturbances.The Lyapunov stability theory can guarantee the asymptotic stability of aerial manipulators system with actuator faults and external disturbances.The proposed FTC scheme considers both actuator fault and modelling errors,combined with the adaptive law of actuator fault,which has better performance than traditional FTC scheme,such as NTSM.Finally,several comparative simulations are conducted to illustrate the effectiveness of the proposed FTC scheme.

Group Coevolution and Immigration Pigeon-Inspired Optimized Dual-layer Controller for Aerial Manipulator Trajectory Tracking

The aerial manipulator expands the scope of unmanned aerial vehicle(UAV)'s application as well as increases the di±culties in the design of the controller.To better control the aerial manipulator for di®erent trajectories tracking under di®erent conditions,a new dual-layer controller is designed in this paper.The integral backstepping sliding mode controller(IBSMC)is applied to the outer-loop controller and backstepping controller(BC)is applied to the innerloop controller.To improve the performance of the system,an improved pigeon-inspired optimization(PIO)algorithm called group coevolution and immigration pigeon-inspired optimization(GCIPIO)algorithm is proposed to optimize the controller parameters of IBSMC.GCIPIO algorithm utilizes the group coevolution and immigration mechanisms.A series of simulations are conducted to show the advantage of the proposed method.The results illustrate that the proposed method ensures the closed-loop system has less end-e®ector tracking error.

Adaptive Sliding-Mode Disturbance Observer-Based Nonlinear Control for Unmanned Dual-Arm Aerial Manipulator Subject to State Constraints

The unmanned dual-arm aerial manipulator system is composed of a multirotor unmanned aerial vehicle(UAV)and two manipulators.Compared to a single manipulator,dual-arm always provides greater°exibility and versatility in both goods delivery and complex task execution.However,the practical application of the system is limited due to nonlinearities and complex dynamic coupling behavior between the multirotor and the manipulator,as well as the one between the inner and outer loop of the multirotor.In this paper,a holistic model of the dual-arm aerial manipulator system is¯rst derived with complete model information.Subsequently,an adaptive sliding-mode disturbance observer(ASMDO)is proposed to handle external disturbances and unmeasurable disturbances caught by unmeasurable angular velocity and acceleration of the manipulators.Moreover,for safety concerns and transient performance requirements,the state constraints should be guaranteed.To this end,an auxiliary term composed of constrained variable signals is introduced.Then,the performance of the designed method is proven by rigorous analysis.Finally,the proposed method is validated through two sets of simulation tests.

Grasp Planning and Visual Servoing for an Outdoors Aerial Dual Manipulator

This paper describes a system for grasping known objects with unmanned aerial vehicles (UAVs) provided with dual manipulators using an RGB-D camera. Aerial manipulation remains a very challenging task. This paper covers three principal aspects for this task: object detection and pose estimation, grasp planning, and in-flight grasp execution. First, an artificial neural network (ANN) is used to obtain clues regarding the object’s position. Next, an alignment algorithm is used to obtain the object’s sixdimensional (6D) pose, which is filtered with an extended Kalman filter. A three-dimensional (3D) model of the object is then used to estimate an arranged list of good grasps for the aerial manipulator. The results from the detection algorithm—that is, the object’s pose—are used to update the trajectories of the arms toward the object. If the target poses are not reachable due to the UAV’s oscillations, the algorithm switches to the next feasible grasp. This paper introduces the overall methodology, and provides the experimental results of both simulation and real experiments for each module, in addition to a video showing the results.

Rotorcraft with a 3DOF Rigid Manipulator:Quaternion-based Modeling and Real-time Control Tolerant to Multi-body Couplings

This paper proposes a simple solution for the stabilization of a mini-quadcopter carrying a 3DoF（degrees of freedom） manipulator robot in order to enhance its achievable workspace and application profile. Since the motion of the arm induces torques which degrade the stability of the system, in the present work, we consider the stabilization of both subsystems： the quadcopter and the robotic arm. The mathematical model of the system is based on quaternions. Likewise, an attitude control law consisting of a bounded quaternion-based feedback stabilizes the quadcopter to a desired attitude while the arm is evolving. The next stage is the translational dynamics which is simplified for control（nonlinear） design purposes. The aforementioned controllers are based on saturation functions whose stability is explicitly proved in the Lyapunov sense. Finally, experimental results and a statistical study validate the proposed control strategy.

A Review on Cooperative Robotic Arms with Mobile or Drones Bases

This review paper focuses on cooperative robotic arms with mobile or drone bases performing cooperative tasks. This is because cooperative robots are often used as risk-reduction tools to human life. For example, they are used to explore dangerous places such as minefields and disarm explosives. Drones can be used to perform tasks such as aerial photography, military and defense missions,agricultural surveys, etc. The bases of the cooperative robotic arms can be stationary, mobile(ground), or drones. Cooperative manipulators allow faster performance of assigned tasks because of the available "extra hand". Furthermore, a mobile base increases the reachable ground workspace of cooperative manipulators while a drone base drastically increases this workspace to include the aerial space.The papers in this review are chosen to extensively cover a wide variety of cooperative manipulation tasks and industries that use them.In cooperative manipulation, avoiding self-collision is one of the most important tasks to be performed. In addition, path planning and formation control can be challenging because of the increased number of components to be coordinated.