Latest Papers

ASME Journal of Mechanisms and Robotics

  • Dynamic Modeling and Simulation of a Hybrid Robot
    by Shen N, Yuan H, Li J, et al. on May 12, 2022 at 12:00 am

    AbstractThe unique structure of hybrid robot makes its dynamic characteristic different from that of the traditional machine tools. Therefore, the dynamic model is crucial to both designing and application of hybrid robot. In this paper, a new type of five-degrees-of-freedom (5DoF) hybrid robot is introduced, and its dynamic model is established. First, the kinematic formulas are derived for all the component, and then, the inertia forces or moments are calculated. Second, the active forces or moments in the joints are assumed as variables and the number of variables is reduced by analyzing joint types. Then, an equation set of 36 equilibrium equations with 38 variables is obtained using D'Alembert's principle. Based on the spatial deformation compatibility analysis of two branches, two supplementary equations are derived to determine the solution of dynamic model of the hybrid robot with redundant constraints in its parallel mechanism. Several cases are studied by comparing with ADAMS simulation. The result shows the good accuracy of the proposed dynamic model, which provides a practical method to calculate the reaction force or moment in any joint at any instant for the hybrid robot and thus facilitates dimensional synthesis, trajectory optimization, and smoothing control.

  • Feasibility Design and Control of a Lower Leg Gait Emulator Utilizing a Mobile 3-Revolute, Prismatic, Revolute Parallel Manipulator
    by Soliman A, Ribeiro GA, Gan D, et al. on May 12, 2022 at 12:00 am

    AbstractDesign and control of lower extremity robotic prostheses are iterative tasks that would greatly benefit from testing platforms that would autonomously replicate realistic gait conditions. This paper presents the design of a novel mobile 3-degree-of-freedom (DOF) parallel manipulator integrated with a mobile base to emulate human gait for lower limb prosthesis evaluation in the sagittal plane. The integrated mobile base provides a wider workspace range of motion along the gait direction and reduces the requirement of the parallel manipulator’s actuators and links. The parallel manipulator design is optimal to generate the defined gait trajectories with both motion and force requirements using commercially available linear actuators. An integrated active force control with proportional integral derivative (PID) control provided more desirable control compared to traditional PID control in terms of error reduction. The novelty of the work includes the methodology of human data-oriented optimal mechanism design and the concept of a mobile parallel robot to extend the translational workspace of the parallel manipulator with substantially reduced actuator requirements, allowing the evaluation of prostheses in instrumented walkways or integrated with instrumented treadmills.

  • Announcing the 2021 Best Paper Award and Honorable Mention
    by Krovi V. on May 12, 2022 at 12:00 am

    Together with the Editorial Board of the Journal of Mechanisms and Robotics (JMR), I am pleased to announce the winner of the journal's 2021 Best Paper Award:P. Reinier Kuppens, Miguel A. Bessa, Just L. Herder, and Jonathan B. Hopkins, 2021, “Compliant Mechanisms That Use Static Balancing to Achieve Dramatically Different States of Stiffness,” ASME J. Mech. Robot., 13(2), p. 021010. https://doi.org/10.1115/1.4049438

Design Framework and Clinical Evaluation of a Passive Hydraulic Patient Simulator for Biceps Spasticity Assessment Training

Abstract

This article presents the framework for developing a passive (unpowered) mechanical training simulator for replication of biceps spasticity to complement current clinical assessment training. The passive training simulator was developed to mimic three main behavioral features of spasticity, i.e., abnormal muscle tone, catch-release behavior, and range of motion (ROM) reduction. The simulator can replicate varied levels of spasticity (Modified Ashworth Scale (MAS) levels 0–4) using a combination of three adjustable mechanical design features, i.e., resistance level, catch angle, and ROM selectors. Bench-top evaluation examined the performance of individual mechanical design features, as well as their combined performance. Spastic muscle resistance profiles generated by the simulator qualitatively agreed with the clinical descriptions of spasticity in the MAS. Mean peak simulated resistive torque fell within the clinical measures from actual spasticity patients for MAS 1–4, but was lower for MAS 0 (0.9, 3.5, 4.2, 6.9, 9.8 Nm for MAS 0–4, respectively). Seven clinicians were invited to validate the simulator performance. They were asked to identify the simulated MAS level during a blinded assessment and to score the realism of each simulation feature using a five-point scale, where 3 was “about right,” during a disclosed assessment. The mean percent agreement of clinicians’ judgments was 76 ± 12%. The mean realism score throughout MAS 0–4 were 2.82 ± 0.15. Preliminary results suggested good potential for this simulator in helping future healthcare practitioners learn and practice the basics of spasticity assessment.
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