Underactuated Manipulator Research Articles

Comprehensive Stable Control Strategy for a Typical Underactuated Manipulator Considering Several Uncertainties

This article proposes a comprehensive stable control strategy for the planar multi-link underactuated manipulator (PMLUM), considering several uncertainties. According to the nilpotent approximation property, the control procedure is split into two stages. In the first stage of control, we postulate the idea of model degradation, reducing the PMLUM to a planar virtual Pendubot (PVP). This occurs by controlling the active link (AL) to a specific desired position and the passive link (PL) moves along with it. When the AL moves to the desired position, the second phase of control is entered. Meanwhile, all ALs are regarded as a whole, so the PMLUM can be regarded as a mechanical arm with 2-DOF. In the second stage of control, due to the nilpotent approximation feature of the PVP, the PVP is guided to the desired angle using the iterative steering technique. Simulation experiments are carried out on active–active–passive (AAP) and active–active–active–passive (AAAP) systems under major uncertainties, which contain initial velocity and torque disturbances. The final results validate the effectiveness of the method proposed.

Adaptive total energy shaping of a class of manipulators

AbstractPoint‐to‐point control of underactuated mechanical systems is a challenging problem, especially if some of the system's parameters are uncertain. A popular method to stabilize underactuated manipulators is total energy shaping, in which a new Hamiltonian function is assigned to the closed‐loop system while a set of partial differential equations (PDEs) should be solved. In this study, an adaptive total energy shaping controller based on the approach called interconnection and damping assignment passivity‐based control (IDA‐PBC) for some underactuated robots is designed. The proposed method can overcome uncertainties in the dynamical parameters and also the parameters of the input mapping matrix under the satisfaction of the PDEs. The stability of the desired pose is ensured by the Lyapunov approach via suitable design of adaptation laws without the requirement for the persistence of excitation condition or other similar conditions. The results are applied to a 3‐DOF underactuated manipulator and verified by simulations.

Interacting with Obstacles Using a Bio-Inspired, Flexible, Underactuated Multilink Manipulator.

With the increasing demand for robotic manipulators to operate in complex environments, it is important to develop designs that work in obstacle-rich environments and can navigate around obstacles. This paper aims to demonstrate the capabilities of a bio-inspired, underactuated multilink manipulator in environments with fixed and/or movable obstacles. To simplify the system design, a single rotational actuator is used at the base of the manipulator. We present a modeling method for flexible, multilink underactuated manipulators, including their interaction with obstacles. We also demonstrate how to plan a trajectory for the manipulator in environments with fixed obstacles. The robustness of the manipulator is examined by analyzing the effects of uncertainty in its initial state and the position of obstacles. Next, we demonstrate the performance of the manipulator in environments with movable obstacles and show the advantages of controlling the obstacles' radii and positions. Lastly, we showcase the process of picking up an object in workspaces with obstacles. All the findings are supported by simulations as well as hardware experiments.

Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator.

A high degree of freedom (DOF) benefits manipulators by presenting various postures when reaching a target. Using a tendon-driven system with an underactuated structure can provide flexibility and weight reduction to such manipulators. The design and control of such a composite system are challenging owing to its complicated architecture and modeling difficulties. In our previous study, we developed a tendon-driven, high-DOF underactuated manipulator inspired from an ostrich neck referred to as the Robostrich arm. This study particularly focused on the control problems and simulation development of such a tendon-driven high-DOF underactuated manipulator. We proposed a curriculum-based reinforcement-learning approach. Inspired by human learning, progressing from simple to complex tasks, the Robostrich arm can obtain manipulation abilities by step-by-step reinforcement learning ranging from simple position control tasks to practical application tasks. In addition, an approach was developed to simulate tendon-driven manipulation with a complicated structure. The results show that the Robostrich arm can continuously reach various targets and simultaneously maintain its tip at the desired orientation while mounted on a mobile platform in the presence of perturbation. These results show that our system can achieve flexible manipulation ability even if vibrations are presented by locomotion.

Effective Control Method Based on Trajectory Optimization for Three-Link Vertical Underactuated Manipulators With Only One Active Joint.

For a three-link vertical underactuated manipulator (TVUM) with only one active joint, the control target is to swing up its endpoint from the straight-down equilibrium point (SDEP) and to stabilize the endpoint at the straight-up equilibrium point (SUEP) eventually. Up to now, there are few effective control strategies to achieve the above control target. In this article, we propose an effective control method based on the trajectory optimization to realize the system control target, and the main steps of this article are: 1) a continuous trajectory that consists of two segments with design parameters is planned for the actuated link, along which the actuated link can be swung up from the initial states to the final states; 2) the design parameters are optimized by using the intelligent optimization algorithm to guarantee that the states of the underactuated links are continuous at the junction. In this way, the underactuated links are also moved to their final states with the actuated link simultaneously; 3) a tracking controller is designed by using the sliding-mode method to track the trajectory with optimized design parameters, so the endpoint is swung up from the SDEP to the SUEP directly; and 4) a stabilizing controller is further devised through the LQR method to keep the endpoint being stable at the SUEP. Finally, simulation results show that the proposed control method achieves the swing-up and stable control target of the system, and the control performance of the proposed method is superior than that of the existing control methods through the comparisons.

A General Stable Control Method for R-Type Underactuated Robot with Three Different Initial Situations

In this paper, we propose a general control method via the intelligent algorithm for a planar R-type underactuated robot. This control method solves the unified control problem of R-type underactuated manipulator. Meanwhile, the proposed method is also applicable to cases of nonzero initial velocity and interference rejection. Our total control program includes two stages. In the first stage, we design the trajectory based on the states of the actuated link, and then the controller is designed to track the planned trajectory to realize the objective of the actuated link. In the second stage, the trajectory with adjustable parameters is planned for the actuated link. Then, the adjustable parameters are calculated by the intelligent algorithm based on the underactuated constraints. Subsequently, the controller is designed to track the second trajectory to realize the objective of the actuated manipulator and the underactuated manipulator. Finally, the performance of the proposed method is verified through simulations.

Design and Experiment of an Underactuated Broccoli-Picking Manipulator

Mature broccoli has large flower balls and thick stems. Therefore, manual broccoli picking is laborious and energy-consuming. However, the big spheroid vegetable-picking manipulator has a complex structure and poor enveloping effect and easily causes mechanical damage. Therefore, a broccoli flower ball-picking manipulator with a compact structure and simple control system was designed. The manipulator was smart in structure and stable in configuration when enveloped in flower balls. First, a physical damage test was carried out on broccoli according to the underactuated manipulator’s design scheme. The maximum surface pressure of the flower ball was 30 N, and the maximum cutting force of the stem was 35 N. Then, kinematic analysis was completed, and the statical model of the underactuated mechanism was established. The dimension of the underactuated mechanism for each connecting rod was determined based on the damage test results and design requirements. The sizes of each connecting rod were 50 cm, 90 cm, 50 cm, 90 cm, 50 cm, 60 cm, and 65 cm. The statical model calculated the required thrust of the underactuated mechanism as 598.66–702.88 N. Then, the manipulator was simulated to verify its reliability of the manipulator. Finally, the manipulator’s motion track, speed, and motor speed were determined in advance in the laboratory environment. One-hundred picking tests were carried out on mature broccoli with a 135–185 mm diameter. Results showed that the manipulator had an 84% success rate in picking and a 100% lossless rate. The fastest single harvest time in the test stand was 11.37 s when the speed of the robot arm was 3.4 m/s, and the speed of the stepper motor was 60 r/min.

Distributed Formation Control of End-Effector of Mixed Planar Fully- and Under-Actuated Manipulators

Distributed Formation Control of End-Effector of Mixed Planar Fully- and Under-Actuated Manipulators

A Novel Exploration-Exploitation-Based Adaptive Law for Intelligent Model-Free Control Approaches.

Model-free control approaches require advanced exploration-exploitation policies to achieve practical tasks such as learning to bipedal robot walk in unstructured environments. In this article, we first construct a comprehensive exploration-exploitation policy that carries quality knowledge about the long-term predictor and the control policy, and the control signal of the model-free algorithms. Therefore, the developed model-free algorithm continues exploration by adjusting its unknown parameters until the desired learning and control are accomplished. Second, we provide an utterly model-free adaptive law enriched with the exploration-exploitation policy and derived step-by-step using the exact analogy of the model-based solution. The obtained adaptive control law considers the control signal saturation and the control signal (input) delay. Performed Lyapunov stability analysis ensures the convergence of the adaptive law that can also be used for intelligent control approaches. Third, we implement the adaptive algorithm in real time on a challenging benchmark system: a fourth-order, coupled dynamics, input saturated, and time-delayed underactuated manipulator. The results show that the proposed adaptive algorithm explores larger state-action spaces and treats the vanishing gradient problem in both learning and control. Also, we notice from the results that the learning and control properties of the adaptive algorithm are optimized as required.

Position-posture Control Strategy for Planar Underactuated Manipulators with Second-order Nonholonomic Constraint

Position-posture Control Strategy for Planar Underactuated Manipulators with Second-order Nonholonomic Constraint

Cascade control of underactuated manipulator based on reinforcement learning framework

In this article, we propose a cascade control framework to attenuate the residual vibration of the underactuated manipulator. The control framework is divided into two phases. In the first phase, a path generator trained by the reinforcement learning produces the leading signal for the tracking controller. In the second phase, the leading signal stabilizes the underactuated manipulator, and the adaptive proportional derivative controller is implemented to reduce the vibration. In the process, a novel path planning method is proposed to improve exploration efficiency, and a negative reward is introduced to avoid unsafe strategies and simulation instability. The effectiveness of the proposed control scheme is verified in the simulations of the double pendulum crane and the two-link flexible manipulator.

Learning to Cooperate: A Hierarchical Cooperative Dual Robot Arm Approach for Underactuated Pick-and-Placing

Cooperative multiagent manipulation systems allow to extend on the manipulative limitations of individual agents, increasing the complexity of the manipulation tasks the ensemble can handle. Controlling such a system requires meticulous planning of subsequent subtasks, queried to the individual agents, in order to execute the master task successfully. Real-time (re)planning is essential to ensure the task can still be achieved when subtasks execution suffers from uncertainty or when the master task changes intermittently requiring real-time reconfiguration of the plan. In this article, we develop a supervisory control architecture tailored to the cooperation of two robotic manipulators equipped with standard pick-and-place facilities in the plane. We control the planar position and orientation of an object using two underactuated manipulators so that only the position of the object can be controlled directly. The desired orientation follows from the accumulation of alternating relative angles. A time-invariant policy function is trained using deep reinforcement learning, which can determine a finite sequence of pick-and-place maneuvers to manipulate the object to a desired configuration. Two policy architectures are compared. The first uses the kinematic model to determine the final step, whilst the second policy makes this decision itself. The more information is given to the policy, the easier it trains. In return, it becomes less adaptable and loses some of its generalizability.

Tip Position Control and Vibration Suppression of a Planar Two-Link Rigid-Flexible Underactuated Manipulator.

When a flexible link manipulator lacks a joint motor, how to use the remaining motors to achieve the control objective is a challenge, and the research in this direction is limited. This article presents a tip position control and vibration suppression approach for a planar two-link rigid-flexible (TLRF) underactuated manipulator with a passive first joint. First, we establish a dynamic model of the system by using the assumed mode method (AMM) and the Lagrangian modeling method. Then, we obtain the dynamic coupling relationship of the two links based on the dynamic model. According to this dynamic coupling relationship, we find that the passive rigid link can be controlled indirectly by controlling the active flexible link. Thus, we calculate the target angles of the two links by using the inverse kinematic method and design a controller for the active flexible link to stabilize it at its target angle and to suppress its vibration. Next, we optimize the parameters of this controller by using the genetic algorithm (GA). GA helps us simultaneously stabilize the passive rigid link at its target angle while realizing the control objective of the active flexible link. The simulation results demonstrate the effectiveness of the proposed control approach.

Design and Research of an Underactuated Manipulator Based on the Metamorphic Mechanism

Robot hands play an important role in the interaction between robots and the environment, and the precision and complexity of their tasks in work production are becoming higher and higher. However, because the traditional manipulator has too many driving components, complex control, and a lack of versatility, it is difficult to solve the contradiction between the degrees of freedom, weight, flexibility, and grasping ability. The existing manipulator has difficulty meeting the diversified requirements of a simple structure, a large grasping force, and the ability to automatically adapt to shape when grasping an object. To solve this problem, we designed a kind of underactuated manipulator with a simple structure and strong generality based on the metamorphic mechanism principle. First, the mechanism of the manipulator was designed on the basis of the metamorphic mechanism principle, and a kinematics analysis was carried out. Then, the genetic algorithm was used to optimize the size parameters of the manipulator finger structure. Finally, for different shapes of objects, the design of the control circuit binding force feedback control was carried out with a grasping experiment. The experimental results show that the manipulator has simple control and can grasp objects of different sizes, positions, and shapes.

A Control Strategy Based on Trajectory Planning and Optimization for Two-Link Underactuated Manipulators in Vertical Plane

The control objective of the vertical plane underactuated manipulator (VPUM) is generally to swing up the end point (EP) from the vertical down equilibrium point (VDEP) to the vertical up equilibrium point (VUEP), and finally, to stabilize it at the VUEP. The zone control methods are usually used to achieve this control objective, but the problem of these methods is that they cannot find a unified zone range, and it is easy to appear singularity in the motion process. In this article, for two-link VPUMs, we propose a control strategy based on trajectory planning and optimization, which does not need to divide the zone range, avoids the singularity problem, and can achieve the control objective quickly and smoothly. We design the trajectory by using the time scale method for the active link according to the initial and target states. Then, we obtain the trajectory parameters by employing differential evolution algorithm to ensure that the passive link can also move from the initial states to the target states simultaneously. We design a sliding mode tracking controller to make the active link move along the designed trajectory, so the EP is moved to VUEP. Meantime, we design a sliding mode stabilization controller to ensure that the system is stable at VUEP. Finally, the universality and robustness of the proposed method are proved by simulations.

Stabilization Control of Underactuated Spring-Coupled Three-Link Horizontal Manipulator Based on Energy Absorption Idea

A spring-coupled three-link horizontal manipulator (STHM) is an underactuated mechanical system that possesses two control inputs and three degrees of freedom (DOF). This paper discusses the stabilization control problem for this multi-DOF underactuated system. By using an energy-absorbing idea, we design two types of virtual friction controllers: PsD controller and PD controller. Additionally, the stability of the control system is analyzed based on Lyapunov theory and LaSalle’s invariance principle. The design of the stabilizing controller in this paper makes good use of the physical characteristics of the STHM system. The design process of the whole control system is simple. Numerical examples demonstrate the validity and superiority of our developed control strategy.

Design and implementation of fault-tolerant control strategies for a real underactuated manipulator robot

This paper presents the design and implementation of four control strategies applied to a real underactuated manipulator robot with 3-DOF (Degrees of Freedom). Additionally, an original methodology for controlled oscillatory compensations is designed and implemented to mitigate the effect of a passive joint on the overall performance of this manipulator robot. The objective of this methodology is to create controlled oscillations that allow the faulty link and its (passive) joint to physically align with their adjacent previous link. The implemented control techniques are sinh–cosh, neural compensation, gain scheduling PID, and gain scheduling sinh–cosh. The real robot in which these four control strategies and oscillatory compensation methodology are implemented is a SCARA (Selective Compliant Assembly Robot Arm) robot. To assess controller performance—once the 3-DOF underactuated manipulator robot starts its trajectory—after t = 4.5 s, a fault is activated in its joint No. 2, converting it into a passive joint. The performance indicators IA (index of agreement), RMS (Root Mean Square), and RSD (Residual Standard Deviation) are used to analyze, compare, and evaluate the behavior of the four control strategies and the compensation methodology.

A review on structural development and recognition–localization methods for end-effector of fruit–vegetable picking robots

The excellent performance of fruit and vegetable picking robots is usually contributed by the reasonable structure of end-effector and recognition–localization methods with high accuracy. As a result, efforts are focused on two aspects, and diverse structures of end-effector, target recognition methods as well as their combinations are yielded continuously. A good understanding for the working principle, advantages, limitations, and the adaptability in respective fields is helpful to design picking robots. Therefore, depending on different grasping ways, separating methods, structures, materials, and driving modes, main characteristics existing in traditional schemes will be depicted firstly. According to technical routes, advantages, potential applications, and challenges, underactuated manipulators and soft manipulators representing future development are then summarized systematically. Secondly, partial recognition and localization methods are also demonstrated. Specifically, current recognition manners adopting the single-feature, multi-feature fusion and deep learning are explained in view of their advantages, limitations, and successful instances. In the field of 3D localization, active vision based on the structured light, laser scanning, time of flight, and radar is reflected through the respective applications. Also, another 3D localization method called passive vision is also evaluated by advantages, limitations, the degree of automation, reconstruction effects, and the application scenario, such as monocular vision, binocular vision, and multiocular vision. Finally portrayed from structural development, recognition, and localization methods, it is possible to develop future end-effectors for fruit and vegetable picking robots with superior characteristics containing the less driving element, rigid–flexible–bionic coupling soft manipulators, simple control program, high efficiency, low damage, low cost, high versatility, and high recognition accuracy in all-season picking tasks.

Robostrich Arm: Wire-Driven High-DOF Underactuated Manipulator

We propose a wire-driven robotic arm inspired by the ostrich neck. It can pick up a small piece of feed from the ground while colliding with it. This arm is named robostrich arm (shortened form of robotic ostrich arm). It consists of a serial chain of 18 rigid bodies connected by free rotational joints that are designed to have angle limitations similar to the bones of a real ostrich. It moves in a vertical plane and is driven by two DC motors through antagonistic wires. The task considered in this study was to lift the arm tip (the “head” of the robostrich arm). The experimental results indicate that the tensioner balance and timing between the two wires are important for achieving the head-up task. This paper indicates the contribution of antagonist muscles to the performance of head-up tasks by high-degree-of-freedom underactuated manipulators in robotics and ostrich necks in biological studies.

PSO-based nonlinear model predictive planning and discrete-time sliding tracking control for uncertain planar underactuated manipulators

Control of planar underactuated manipulators (PUM) with unknown parameter perturbations and external disturbances is still a challenging task due to their complex and peculiar characteristics. The research on it is significant in the view of wide applications in practice. In this paper, taking an uncertain 3-degree of freedom PUM with a free first joint as a benchmark example, we discuss its position control issue. Specifically, an integrated control method is developed, including the nonlinear model prediction control (NMPC) based on an improved particle swarm optimisation (PSO) algorithm and the discrete-time fast terminal sliding mode (FTSM) control. The PSO-based NMPC is proposed for planning discrete trajectories of the active joint angles in real time, along which the manipulator end-point can reach the desired position. Then the discrete-time FTSM controllers are designed to keep the active joints tracking the discrete trajectories, where the uncertainties related to the active links/joints are estimated by time delay estimation method. Besides, the influence of the uncertainties related to the free link/joint on the system can be made up by the NMPC in real time. It is confirmed via simulations that the above method can achieve the accurate positioning of such an uncertain manipulator.