Cable-driven Robot Research Articles

A novel pyramidal cable-driven robot for exercising and rehabilitation of writing tasks

AbstractThis paper presents a novel cable-driven parallel robot with the aim of rehabilitating/exercising young and disabled children in drawing and writing tasks. The pyramidal topology was identified as providing the required three active translational Degrees of Freedom with a redundant set of five cables in a compact portable shape. In addition, this robot was designed with new features, as it is inexpensive, easy to control, easy to move to any place at home or school as it is fitting a home desk or classroom table. In this paper, we present the main steps for designing the proposed cable-driven pyramidal parallel robot. Specific attention is addressed to the design of the structure and the end effector as well as to establishing proper simulation models. Several simulations are proposed by implementing both kinematic and dynamic models to demonstrate the feasibility of multiple writing/drawing tasks. A specific user interface is proposed allowing both continuous and intermittent trajectories. A sliding mode control is implemented to achieve suitable tracking accuracy on a desired path. Finally, an experimental validation is successfully carried out by considering multiple trajectories for demonstrating the engineering feasibility and effectiveness of the proposed design and simulation models.

A New Practical Robust Adaptive Control of Cable-driven Robots

A New Practical Robust Adaptive Control of Cable-driven Robots

Energy efficient robots based on structures with tensegrity features and cable-driven mechanisms

The paper presents concept of energy efficient motion control of robots and other machines based on structures with tensegrity features and/or cable-driven mechanisms. The essence of concept is generalization of so called eigenmotion idea for these multi-DOF complex mechanisms. The term eigenmotion here refers to a motion of a mechanism in which the constant sum of kinetic and potential energy is maximally preserved. The operation of the drives is ideally used only to eliminate passive resistances and to minimize deviations of motion from the required trajectory. The main advantage of mechanisms with tensegrity features and cable-driven ones is a relatively high number of elements such as springs, active cables or variable bodies, whose energy absorbing properties can be suitably adjusted during design and some also continuously during operation. The variability of attainable eigenmotion trajectories of these types of mechanisms can be further extended thanks to number of drives higher than number of end-effector degrees of freedom. The concept is demonstrated on two planar systems, one structure with tensegrity features and one serial–parallel cable-driven robot. The examples show the optimization of the parameters to achieve the eigenmotion properties on the given trajectories, as well as the change of the eigenmotion trajectory by changing the adjustable parameters. The final control of mechanical models along energy efficient trajectories is realized by computed torque control method.

Design and Implementation of a Synergy-Based Cable-Driven Humanoid Arm With Variable Stiffness

Abstract Cable-driven arms have the advantages of light weight, large workspace, good compliance, high-speed, and acceleration. This paper proposes a cable-driven variable stiffness humanoid arm that can reproduce typical daily postures of the upper limb with a few actuators via kinematic synergy. A kinematic model of the arm is established to obtain the design parameters corresponding to different postures. The dimension reduction of the actuation is realized through a synergy analysis of the driving cables. A coupling actuation mechanism is designed to reduce the number of actuators required to generate specific postures of the arm via cables. Optimization of the geometric parameters of the joints is conducted to improve posture reproduction accuracy. The stiffness of the arm could be regulated by adjusting the cable tension. Stiffness modeling of the joint is performed to evaluate the influence of cable tension. A prototype of the arm is designed. The workspace is analyzed under the actuation of the designed coupling mechanism. The transformation among the targeted postures is simulated to validate the feasibility of the actuation dimension reduction design of the arm. Robustness analysis is conducted which indicates the use of synergic actuation weakens the arm's robustness. With the proposed dimension reduction method, the actuation dimensions are reduced from 9 to 4, which leads to the diminution of the reachable workspace and manipulability. The reproduction accuracy of the targeted postures is 84.3%. The proposed method can be applied to the dimension reduction designs of other cable-driven robots.

Automating Surgical Peg Transfer: Calibration With Deep Learning Can Exceed Speed, Accuracy, and Consistency of Humans

Peg transfer is a well-known surgical training task in the Fundamentals of Laparoscopic Surgery (FLS). While human surgeons teleoperate robots such as the da Vinci to perform this task with high speed and accuracy, it is challenging to automate. This paper presents a novel system and control method using a da Vinci Research Kit (dVRK) surgical robot and a Zivid depth sensor, and a human subjects study comparing performance on three variants of the peg-transfer task: unilateral, bilateral without handovers, and bilateral with handovers. The system combines 3D printing, depth sensing, and deep learning for calibration with a new analytic inverse kinematics model and time-minimized motion controller. In a controlled study of 3384 peg transfer trials performed by the system, an expert surgical resident, and 9 volunteers, results suggest that the system achieves accuracy on par with the experienced surgical resident and is significantly faster and more consistent than the surgical resident and volunteers. The system also exhibits the highest consistency and lowest collision rate. To our knowledge, this is the first autonomous system to achieve “superhuman” performance on a standardized surgical task. All data is available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://sites.google.com/view/surgicalpegtransfer</uri> Note to Practitioners—This paper presents a new approach to calibrating cable-driven robots based on a combination of 3D printing, depth sensing, inverse kinematics, convex optimization, and deep learning. The approach is applied to calibrating the da Vinci, commercial surgical-assist robot, to automate a standard “pick and place” task. Experiments suggest that the resulting system matches human surgical expert performance in speed and accuracy and significantly outperforms humans in terms of consistency. All details on the system including CAD models, code, and user study data are available online.

Comparison of theoretical and experimental models for knee flexion/extension using a cable-driven robot

AbstractTo support and facilitate the rehabilitation of patients with physical limitations and aid the therapist, several robotic structures are being studied. Among the structures, the cable-driven robots stand out. The cable-driven robots are structures actuated by cables and have the advantages of being flexible and reconfigurable for each patient. The objective of this paper is to develop a theoretical model for knee flexion/extension force and moment using a cable-driven robot. The proposed model is necessary for elaborating a referential to which diagnosis can be made and the improvement of the patient evaluated. The presented theoretical model was validated through experiments with twelve sedentary and healthy volunteers. The first procedure tested ten subjects in three thigh angles for knee flexion motion; the second procedure tested two subjects in flexion and extension for the same thigh angle. The results show the validity of the model for 88.58% of the tests in an ANOVA analysis with a 99% confidence interval. The similarity of data for different gender, ages, and intrinsic factors was noted, implying that the model is representative and independent of the subject’s individuality. Differences between flexion and extension values were observed, which need to be studied in the future.

Real-Time Tension Distribution Design for Cable-Driven Parallel Robot

In this study, we investigated dynamic control strategies for over-constrained cable-driven robots. In order to control a cable-driven robot, it is essential to address issues that arise from the restriction of cable tension, as well as to the redundancy issues that arise from an over-constrained cable-driven system. In contrast to previous research that required consideration of the relationship between tension constraints and computed control wrench in tension distribution problems, we developed a tension function that incorporates the hyperbolic tangent function, which allows tension to always satisfy tension constraints and eliminates the consideration of constraints at each step. The gradient descent method was applied to this tension function to determine an appropriate distribution of tension for the computed wrench. In order to manage tension distribution optimization for achieving objectives such as energy conservation, we provide a practical method to simultaneously realize the necessary wrench and the appropriate tension distribution. Compared with studies that focus on the complex analysis of the structure matrix to solve the tension distribution problem, the tension distribution issue is handled in a straightforward manner in our method, providing the solutions to other problems, such as discontinuity in the calculated wrench, and requirements of changing the cable’s force level during movement. The simulation results and results of comparison with other methods show the effectiveness of the method.

Preface

The 4th International Symposium on Robotics and Intelligent Manufacturing Technology (ISRIMT 2022) was successfully held on September 23-25, 2022 in Changzhou, China (virtual conference). ISRIMT 2022 provided a platform for scientific research achievements and cutting-edge technologies sharing, and for all the participants to understand the academic development trends in related fields, promoting cooperation in the industrialization of academic achievements.We had the honor of having invited Prof. Dequn Li from Huazhong University of Science and Technology, China to serve as our Honorary Chairman. The conference covered keynote speeches, oral presentations, and online Q&A discussion, attracting 90 individuals. Firstly, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers selected were presented by their authors by turns.During the conference, twelve distinguished professors were invited to address their keynote speeches. Among them, Prof. Yu Tian from Tsinghua University, China addressed a thought-provoking speech Bio-inspired Adhesion: From Interfacial Mechanism to Robotic Applications. In this presentation, he introduced the research progress of his group in the field of bio-inspired adhesion, focusing on the design strategy from the understanding of interfacial mechanics to the applications of grasping robotics. And then, Prof. Giuseppe Carbone from University of Calabria, Italy made a speech on the Examples of Innovative Robot Designs with Embodied Intelligence. Illustrative examples were outlined to show the feasibility and practical usefulness of this approach as referring to recent designs such as parallel/hybrid manipulators, humanoid robots, cable-driven robots for conventional or non-conventional applications including healthcare, agriculture, cultural heritage/space exploration. Last but not the least, Prof. Dunbing Tang from Nanjing University of Aeronautics and Astronautics, China delivered a presentation on Multi-agent Reinforcement Learning for Online Scheduling in Smart Factories. This paper presented new cyber-physical integration in smart factories for online scheduling of low-volume-highmix orders. Their dramatic speeches had triggered heated discussion in the conference. And every participant praised this conference for disseminating useful and insightful knowledge.The proceedings of ISRIMT 2022 are a compilation of the accepted papers and represent an interesting outcome of the conference. These papers feature but are not limited to the following topics: Artificial Intelligence, Cloud Manufacturing, Distributed Robot Systems, Intelligent Optimization Method, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.We would like to express our sincere gratitude to all the keynote speakers, peer reviewers, and all the participants who supported ISRIMT 2022. Particularly, our special thanks go to the Journal of Physics: Conference Series, for all the efforts of its colleague in publishing this paper volume. We firmly believe that ISRIMT 2022 have contributed to not only scientific and engineering progress but also other new products and processes.The Committee of ISRIMT 2022List of Committee member, Honorary Chairman are available in this Pdf.

Vibration-based tension estimation of short helically multi-stranded wires under low axial tension

When cables are used to support systems, accurate tension monitoring is critical. However, almost all existing tension estimation models are inaccurate for short cable under low tension. Short helically stranded wire cables under low axial tension are widely used especially in cable-driven robots (CDRs). A vibration-based equation accurately to evaluate applied tensions for short helically stranded wires under low axial tension was developed. We employed two kinds of short cables with diameters of 2.4 and 3.2 mm under tensions of approximately 20 to 110 N. There were no known tension estimates for these conditions up to now. We used a best-fit numerical approach (employing the measured first frequencies and C/f1 values) to derive an accurate equation. The helically stranded wire theory was also used to validate the feature. Finally, we verified experimentally the derived equation using different material and different diameters and the estimates agreed with the experimental data well.

Control-Based Tension Distribution Scheme for Fully Constrained Cable-Driven Robots

Control inputs of fully constrained cable-driven parallel robots (CDPRs) are constrained by the positiveness of the cables tension, as cables merely apply tensile forces. The positive tension distribution (PTD) in CDPRs is usually guaranteed with iterative optimization techniques, utilizing the redundant actuation of the CDPR. The iterative nature of the conventional PTD limits their real-time application since the worst-case computation time of the iterative methods is not predictable. In addition, optimization methods are prone to model uncertainties. This article addresses the PTD problem in the fully constrained CDPRs with a control viewpoint. In the proposed approach, the PTD algorithm is an integral part of the controller, which explicitly generates positive values for the cables tension. To this aim, a saturation-type function is coupled with the controller, and its effect is compensated using a nonlinear disturbance observer. The stability of the proposed control scheme is also investigated in detail through Lyapunov’s second method, considering a nonsingular terminal sliding mode controller. Furthermore, the performance of the proposed methodology is compared with the conventional method for a six-degrees-of-freedom CDPR, in the presence of uncertainties. Finally, the effectiveness of the proposed control scheme is investigated through experiments.

Consistent Solution Strategy for Static Equilibrium Workspace and Trajectory Planning of Under-Constrained Cable-Driven Parallel and Planar Hybrid Robots

This paper presents a consistent solution strategy for static equilibrium workspaces of different types of under-constrained robots. Considering the constraint conditions of cable force and taking the least squares error of the static equilibrium equation as the objective, the convex optimization solution is carried out, and the static equilibrium working space of the under-constrained system is obtained. A consistent solution strategy is applied to solve the static equilibrium workspaces of the cable-driven parallel and planar hybrid robots. The dynamic models are presented and introducing parameters that are applied to make the system stable for point-to-point movements. Based on this model, the traditional polynomial-based point-to-point trajectory planning algorithm is improved by adding unconstrained parameters to the kinematic law function. The constraints of the dynamics model are incorporated into the trajectory planning process to achieve point-to-point trajectory planning for the under-constrained cable-driven robots. Finally, under-constrained cable-driven parallel robots with three cables and planar hybrid robot with two cables are taken as examples to carry out numerical simulation. The final results show that the point-to-point trajectory planning algorithm introducing parameters is effective and feasible and can provide theoretical guidance for the design of subsequent under-constrained robots.

Error Compensation in Position and Orientation of Mobile Platform of Cable-Driven Robots via Tensile Forces Measurement

The paper deals with a problem of position and orientation errors of mobile platform of large-sized parallel cabledriven robots. The advantages of parallel cable-driven robots are simplicity of structure and scalability. At the same time, parallel cable-driven robots are difficult to design due to the specific problems such as collision of cables, geometric and structural nonlinearity in the mathematical models of the main elements of the robot. In this paper, we consider the problem of eliminating the uncertainty associated with deformations of the elements of the robot structure. Such a configuration of the cable system is selected, in which the proximal anchor points of some cables can be considered without errors relatively to given positions. The cable system of a large-sized robot is mounted on the towers. The errors in the proximal anchor points relatively to given positions become significant due to the significant deformations of upper sections of the towers. The deformations of the towers in lower sections can be considered insignificant, and the proximal anchor points have to be located no higher than the middle of the tower to be considered corresponding to a given position. The aim is to compensate the position and orientation errors of the mobile platform of large-sized parallel cable-driven robot due to deformations of the cables and towers. The task suppose uncertainty about the coordinates of the proximal anchor points of the upper cables. Cable deformations are determined from Hooke’s law using tensile forces measurement in cables. The problem of compensations is solved in two stages. At the first stage, the approximate bias of the center of mass of the mobile platform along the vertical coordinate is found. It is defined as the height of the truncated pyramid, the edges of which are formed by stretched lower cables. At the second stage, rotation angles of the mobile platform are determined. Using the rotation matrix, biases in the heights of each distal anchor points are found in the tool coordinate system. In the studied cases PID regulation is used, however, more advanced techniques of automatic regulation, for example, optimal control, can provide better results. The tasks are applied to the model of large-sized symmetric parallel eight-cable-driven robot.

Effectiveness of Bio Inspired Robotics in Studying Biological Systems, and Looking for the Mechanisms that May Solve a Problem in the Engineering Field

Bio-inspired robots have been developed for creating natural things insight robots. These kinds of robots have the capability to interact with human easily. Nowadays, many scientists are trying to make an advanced bio-inspired robot that also makes able to have an impact on society or helps individuals. These kinds of development generally use for logistics, manufacturing, surgery, supply, and car driving. Bio-inspired robot use high-capacity sensors, high-resolution cameras, chips, and other major kinds of essential technologies. This study has also focused on the importance of bioinspired robots that plays a significant role in assembling, carrying, sawing, and other essential curriculum. Interaction between robots and human increase the advantages and strength of the activities and it can provide the desired benefits to individuals. Accordingly, this paper also tries to find the impact of the biological system and its significance in the development of bio-inspired robots. Interaction between human and robots make a huge and effective impact on society and people get inspired to adopt technological facilities in their daily life. In a biological system, bio-robotics also help to develop the growth of technological transformation. Biological studies get inspiration to create designs of advanced and intelligent robotics for conducting diverse human-like activities such as swimming, terrestrial movements, and flying. That also helps to understand the evolution of biological organisms within an advanced dynamic environment. Keywords : Bio-inspired robots, bio-inspired robotic platforms, Robotics Traction Unit (RTU), AI Farming, AI Technology, Magnet-polymer, hybrid continuum cable-driven robot (HCDR), Deep learning models, acrylonitrile-butadiene-styrene, PDMS, ABC, ACO, PSO.

Kinematic Modelling for Hyper-Redundant Robots—A Structured Guide

Obtaining mathematical equations to model the kinematics of a hyper-redundant robot is not intuitive and of greater difficulty than for traditional robots. Depending on the characteristics of the robot, the most appropriate methodology to approach the modelling may be one or another. This article provides a general overview of the different approaches there are when modelling a hyper-redundant cable-driven robot, while proposing a guide to help the novel researcher that approaches this field decide which methodology to apply when modelling a robot. After providing some definitions, a simple framework to understand all the underlying models is presented. Afterwards, the mathematical equations for the most important methods of modelling are developed. Finally, the proposal for a step-by-step tutorial is included, and it is exemplified by applying it to three real robots.

Workspace-Based Model Predictive Control for Cable-Driven Robots

The control of cable-driven robots is challenging due to the system’s nonlinearity, actuation redundancy, and the unilaterally bounded actuation constraints. To solve this problem, a workspace-based model predictive control (W-MPC) scheme is proposed, which combines the online model predictive control with offline workspace analysis. Using the workspace, a set of convex constraints can be generated for a given reference trajectory. This can then be used to formulate a convex optimization problem for the online W-MPC. Meanwhile, strict recursive feasibility and stability are obtained by taking advantage of the predictive feature of MPC. To demonstrate the effectiveness of the proposed W-MPC, simulation was performed on a 2-link planar cable-driven robot and a spatial cable-driven parallel robot for both nominal and non-nominal scenarios. Hardware experiment was also carried out using a 3 degree-of-freedom planar cable robot. The results show that the controller is efficient and effective to perform motion tracking with the cable force constraints satisfied despite the existence of various model uncertainties.

Redundancy Resolution and Disturbance Rejection via Torque Optimization in Hybrid Cable-Driven Robots

This article presents redundancy resolution and disturbance rejection via torque optimization in hybrid cable-driven robots (HCDRs). To begin with, we present a redundant HCDR for nonlinear whole-body system modeling and model reduction. Based on the reduced dynamic model, two new methods are proposed to solve the redundancy resolution problem: 1) joint-space torque optimization for actuated joints (TOAJ) and 2) joint-space torque optimization for actuated and unactuated joints (TOAUJ), and they can be extended to other HCDRs. Compared to the existing approaches, this article provides the first solution (TOAUJ-based method) for HCDRs that can solve the redundancy resolution problem as well as disturbance rejection. Additionally, this article develops detailed algorithms targeting TOAJ and TOAUJ implementation. A simple yet effective controller is designed for analysis and validation. Case studies are conducted to evaluate the performance of TOAJ and TOAUJ. The results show the effectiveness of the aforementioned approaches.

Operational Space Iterative Learning Control of Coupled Active/Passive Multilink Cable-Driven Hyper-Redundant Robots

Abstract The operational space control (OSC) of multilink cable-driven hyper-redundant robots (MCDHRs) is required to perform tasks in many applications. As a new coupled active-passive (CAP) MCDHR system, due to the multiple couplings between the active cables, the passive cables, the joints, and the end-effector, the OSC becomes more and more complicated. However, there is currently no robust and effective control method to solve the OSC problem of such types MCDHRs. In this paper, an OSC framework of CAP-MCDHRs using a dynamics-based iterative-learning-control (ILC) method is proposed, considering multivariate optimization. First, the multi-coupling kinematics and the series-parallel coupling dynamics equation (i.e., cable-joint-end) of the CAP-MCDHR are derived. Then, a dynamics-based trajectory tracking framework was constructed. Moreover, an OSC accuracy evaluation model based on a high-precision laser tracker was also designed. The framework allows the tracking of operational space trajectories (OSTs) online with the feasible cable tension and the joint angle. It is also shown that the tracking performance can be improved through the ILC when the desired trajectory is repeatedly performed. Finally, a simulation and an experimental hardware system are built. The results show that the proposed control framework can be easily and effectively applied to the CAP-MCDHR used in real-time.

Practical adaptive position feedback regulator for parallel robots with bounded inputs

This paper addresses the regulation problem of parallel robots by a proportional derivative plus desired gravity compensator (PD-DGC) controller. Due to inaccurate measurements, unmodeled dynamics, and vibrations specially in cable-driven robots and external disturbance in practice, the model of the robot is often plagued with kinematic and dynamic uncertainties. In this paper, two new generations of PD-DGC controller, namely adaptive with respect to the parameters in gravity term, and time-varying PD-DGC in the presence of bounded disturbance, are proposed. Toward not requiring accurate velocity measurement, PD-DGC with merely position feedback in complement to the time-varying controller is designed in the presence of bounded control efforts. Incorporating both methods to establish a simple but strong robust adaptive controller is also investigated by adding an extra assumption on adapted parameters. The asymptotic stability of the closed-loop system is analyzed by the Lyapunov direct method. Experimental results on 2-DOF eye surgery and 3-DOF flexible link ARAS cable-driven robot demonstrate the effectiveness of the proposed approaches in practice.

Motion modeling of cable-driven continuum robots using vector form intrinsic finite element method

ABSTRACT This paper presents the motion modeling of a cable-driven, single backbone continuum robot via the vector form intrinsic finite element (VFIFE) method. The VFIFE method is a solution framework based on vector mechanics. The algorithm describes a continuous body by using a finite number of particles instead of a mathematical function. We first approached the model by defining path elements and allocating particles (mass nodes) for the structure. We then established constitutive conditions as the generalized forces derived from both the external environment and internal deformed structural elements. We found that the dynamic equation of particles can be governed by Newton’s law of motion and solved by a general explicit time integration technique. Furthermore, we performed static modeling of the system by employing a dynamic relaxation algorithm with kinetic damping in the dynamic equations. Finally, from experiments, we validated the simulated static model of a single backbone continuum robot. It is shown that this method is capable of describing a continuum robot’s motion by solving for frame structures that undergo large deformation.

Nonlinear dynamic modeling of a mobile spatial cable-driven robot with flexible cables

Nonlinear dynamic modeling of a mobile spatial cable-driven robot with flexible cables