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.

Self-Adaptive Obstacle Crossing of an AntiBot From Reconfiguration Control and Mechanical Adaptation


One drawback of wheeled robots is their inferiority to conquer large obstacles and perform well on complicated terrains, which limits their application in rescue missions. To provide a solution to this issue, an ant-like six-wheeled reconfigurable robot, called AntiBot, is proposed in this paper. The AntiBot has a Sarrus reconfiguration body, a three-rocker-leg passive suspension, and mechanical adaptable obstacle-climbing wheeled legs. In this paper, we demonstrate through simulations and experiments that this robot can change the position of its center of mass actively to improve its obstacle-crossing capability. The geometric and static stability conditions for obstacle crossing of the robot are derived and formulated, and numerical simulations are conducted to find the feasible region of the robot’s configuration in obstacle crossing. In addition, a self-adaptive obstacle-crossing algorithm is proposed to improve the robot’s obstacle-crossing performance. A physical prototype is developed, and using it, a series of experiments are carried out to verify the effectiveness of the proposed self-adaptive obstacle-crossing algorithm.

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