Latest Papers

ASME Journal of Mechanisms and Robotics

  • Mechanical Characterization of Supernumerary Robotic Tails for Human Balance Augmentation
    on August 31, 2023 at 12:00 am

    AbstractHumans are intrinsically unstable in quiet stance from a rigid body system viewpoint; however, they maintain balance, thanks to neuro-muscular sensory control properties. With increasing levels of balance related incidents in industrial and ageing populations globally each year, the development of assistive mechanisms to augment human balance is paramount. This work investigates the mechanical characteristics of kinematically dissimilar one and two degrees-of-freedom (DoF) supernumerary robotic tails for balance augmentation. Through dynamic simulations and manipulability assessments, the importance of variable coupling inertia in creating a sufficient reaction torque is highlighted. It is shown that two-DoF tails with solely revolute joints are best suited to address the balance augmentation issue. Within the two-DoF options, the characteristics of open versus closed loop tails are investigated, with the ultimate design selection requiring trade-offs between environmental workspace, biomechanical factors, and manufacturing ease to be made.

Approach for Identifying Cartesian Stiffness of a 5-Degree-of-Freedom Hybrid Robot for Machining


This article presents a systematic approach for identifying the Cartesian stiffness of a 5-degree-of-freedom (DOF) hybrid robot for machining that includes a parallel mechanism and an A/C wrist. The novelty of this approach is that the elasticities of both links and joints in the parallel mechanism are integrated into the compliance (inverse of stiffness) parameters at the limb level. By identifying the compliance parameters at the limb level rather than at the joint/link level, the number of parameters to be identified is significantly reduced and the complexity of the identification problem is decreased. Based on screw theory, the Cartesian stiffness model of this hybrid robot is established first. Then, by reconstructing this stiffness model, a linear regression model suitable for estimating the compliance parameter is derived. In addition, a two-step systematic procedure for parameter estimation is introduced, including the reconstruction of the design matrix and robust ridge estimation. Finally, both computer simulations and experiments are carried out to demonstrate the validity of the proposed approach. The simulation results show that the predictive deviations of the end-effector deflections identified by ridge estimation are less than those estimated by linear least squares, confirming its greater robustness. The experimental results indicate that the developed method has potential in industrial settings.

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