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.

Visual-Biased Observability Index for Camera-Based Robot Calibration


Efficient robot integration can be realized by matching real and virtual robots, and accurate robot models can be generated by kinematic parameter calibration. End-effector pose selection for pose measurement to discover the positioning errors is critical in kinematic parameter calibration. Ideal pose selection maximizes calibration accuracy for a defined measurement uncertainty and optimizes measurement cost and utility. In the design of the pose selection process, observability indices are widely accepted criteria for effective pose selection to evaluate calibration performance. Observability indices represent the effect of uncertainty in the measured end-effector poses on the calibrated parameters. However, unlike expensive direct measurement using laser, low-cost camera-based kinematic calibration estimates the end-effector poses from the marker points in the captured image. The variance of the detected marker positions biases the end-effector poses and, eventually, the calibrated parameters. Therefore, this study proposes extended observability indices for pose selection based on this bias to realize accurate calibration with a low-cost camera. The target observability index is O1, a scale-free, reliable index used in kinematic calibration. Considering the visual bias, we extended it as Ov1. This study evaluated Ov1 by comparing the positioning accuracies calibrated on poses selected by maximizing it, original O1, O3 known as the best criterion to restrain the end-effector positioning uncertainty, and Ov3, which is the extended O3 for consistency. A ball-bar test showed that the poses selected by the index Ov1 exhibited higher positioning accuracy than the other indices.

Read More

Journal of Mechanisms and Robotics Open Issues