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.

A New Error Compensation Method for Delta Robots Combining Geometric Error Modeling With Spatial Interpolating


Robots are playing an important role in precision manufacturing and automated inspection, which places higher demands on the positioning accuracy. The Delta robot is the most widely used parallel robot with high speed and small cumulative error. In this way, improving the positioning accuracy of the Delta robot can expand its application scenarios. According to the parameter mapping relationship, the position error can be divided into geometric error and non-geometric error. Considering the influence of the orientation errors on the actual position of the robot end, an error model to recognize the geometric error is established, and the parameter identification is performed based on an iterative approach. For the non-geometric error, the 3D annular sector grid division method and the interpolation rule are established based on the error similarity. And then, a new error compensation method for Delta robots is proposed by combining geometric error modeling with spatial interpolating. After compensation, the positioning accuracy of the Delta robot is improved significantly. The maximum absolute positioning error of the robot is reduced by 86.08% from 2.084 mm to 0.290 mm, the average absolute positioning error of the robot is reduced by 81.77% from 0.790 mm to 0.144 mm, and the error trend in the workspace is eliminated, so as to enable the expansion of Delta robot applications.

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