Cable-driven Module Research Articles

The platform for remote driving of a biomimetic propulsor and measurement of longitudinal and lateral forces generated by the propulsor

The performance characterization of a biomimetic propulsor for a swimming or flying robot typically requires measurement of the longitudinal and lateral forces generated by the propulsion of the propulsor. The propulsor can be either a tail (without or with a peduncle) or a morphing fin (wing), with multiple degrees of freedom (DOFs), and ideally the driving motors are designed to mount outside the propulsor to reduce the mass inertia and moment of inertia of the propulsor. In this article, we design and provide a robust and versatile platform that incorporate the mechanical two-DOFs lever unit and the measurement unit, as well as the configurable driving unit. The two-DOFs lever unit enables the freedoms of the longitudinal and lateral movements but are tightly constrained by the measurement unit that is fixed on the platform carriage for measurement of the longitudinal and lateral forces generated by the propulsor. The driving unit has the motors and the cable-driven modules that are configurable for bidirectional remote actuation, which is plug-and-play and flexible for different types and different numbers of motors. An experiment of the peduncle and the tail for propulsion is illustrated with this platform. The design here also serves as a design guidance for a platform for morphing wings.

Design Methodology and Experimental Study of a Lower Extremity Soft Exosuit

Flexibility and light weight have become the development trends in the field of exoskeleton research. With high movement flexibility, low movable inertia and excellent wearable comfort, such a type of system is gradually becoming an exclusive candidate for applications such as military defense, rehabilitation training and industrial production. In this paper, aiming at assisting the walking of human lower limbs, a soft exosuit is investigated and developed based on the considerations of fabric structure, sensing system, cable-driven module, and control strategy, etc. Evaluation experiments are also conducted to verify its effectiveness. A fabric optimization of the flexible suit is performed to realize the tight bond between human and machine. Through the configuration of sensor nodes, the motion intention perception system is constructed for the lower limb exosuit. A flexible actuation unit with a Bowden cable is designed to improve the efficiency of force transmission. In addition, a position control strategy based on division of the gait phase is applied to achieve active assistance during plantar flexion of the ankle joint. Finally, to verify the assistive effectiveness of the proposed lower extremity exosuit, experiments including a physiological metabolic test and a muscle activation test are conducted. The experiment results show that the exosuit proposed in this paper can effectively reduce the metabolic consumption and muscle output of the human body. The design and methodology proposed in this paper can be extended to similar application scenarios.

A Hybrid Arm-Hand Rehabilitation Robot With EMG-Based Admittance Controller.

Reach-and-grasp is one of the most fundamental activities in daily life, while few rehabilitation robots provide integrated and active training of the arm and hand for patients after stroke to improve their mobility. In this study, a novel hybrid arm-hand rehabilitation robot (HAHRR) was built for the reach-and-grasp task. This hybrid structure consisted of a cable-driven module for three-dimensional arm motion and an exoskeleton for hand motion, which enabled assistance of the arm and hand simultaneously. To implement active compliance control, an EMG-based admittance controller was applied to the HAHRR. Experimental results showed that the HAHRR with the EMG-based admittance controller could not only assist the subject in fulfilling the reach-and-grasp task, but also generate smoother trajectories compared with the force-sensing-based admittance controller. These findings also suggested that the proposed approach might be applicable to post-stroke arm-hand rehabilitation training.

Design, stiffness analysis and experimental study of a cable-driven parallel 3D printer

Although additive manufacturing (AM) has been developed rapidly and become an absolutely necessary tool for reducing the cycle and cost of new product development, the mechanical structures of most 3D printers based on Fused Deposition Modeling (FDM) technology are still traditional serial or parallel mechanisms with rigid components. In this paper, a novel cable-driven parallel 3D printer (CDPP) is developed. Compared with the traditional rigid mechanisms, CDPP has the advantages of larger workspace, higher payload-to-weight ratio, easier modularity and reconfigurability. A cable-driven module with three translational degrees of freedom and a follow-up tensioning module with a spring are adopted for positioning. Firstly, the inverse kinematics of the CDPP is derived considering the cable length constraint. The inverse dynamics model of the CDPP is established based on the Newton–Euler equation and the kinematics. Secondly, the system stiffness of the CDPP and stiffness along three coordinate axes are derived, respectively. The system static stiffness with respect to the stiffness constant of the spring and the coordinates of the moving platform are obtained. Finally, the experiments are performed based on numerical simulation. The results of experiments without executing extrusion demonstrate the simulation results about the static stiffness. The feasibility of the CDPP is verified via the experiments while executing extrusion.

An Integrated Two-Level Self-Calibration Method for a Cable-Driven Humanoid Arm

This paper addresses the kinematic calibration issues for a 7-DOF cable-driven humanoid arm in order to improve its motion control accuracy. The proposed 7-DOF humanoid arm has a hybrid parallel-serial kinematic structure, which consists of three serially connected parallel cable-driven modules, i.e., a 3-DOF shoulder module, a 1-DOF elbow module, and a 3-DOF wrist module. Due to the unique arm design features such as hybrid parallel-serial structure, modular configuration, and redundant sensors, an integrated two-level self-calibration method is proposed in this work. The first level of self-calibration, termed as the central linkage mechanism calibration, is to identify the kinematics errors existed in the 7-DOF central linkage mechanism based on its self-motion capability. The second level of calibration, termed as the cable-driven module calibration, is to identify the kinematics errors existed in each of the parallel cable-driven modules based on its sensing redundancy. To simplify the formulation of the calibration algorithms, the error model of the serial central linkage mechanism is derived from its forward kinematics, in which the Products-Of-Exponential (POE) formula is employed, while the error models of the parallel cable-driven modules are derived from their inverse kinematics. The simulation and experimental results have shown that the proposed self-calibration algorithms can effectively improve the accuracy of the 7-DOF cable-driven humanoid arm.