Latest Papers

ASME Journal of Mechanisms and Robotics

  • Stable Inverse Dynamics for Feedforward Control of Nonminimum-Phase Underactuated Systems
    on January 25, 2023 at 12:00 am

    AbstractAn enhanced inverse dynamics approach is here presented for feedforward control of underactuated multibody systems, such as mechanisms or robots where the number of independent actuators is smaller than the number of degrees of freedom. The method exploits the concept of partitioning the independent coordinates into actuated and unactuated ones (through a QR-decomposition) and of linearly combined output, to obtain the internal dynamics of the nonminimum-phase system and then to stabilize it through proper output redefinition. Then, the exact algebraic model of the actuated sub-system is inverted, leading to the desired control forces with just minor approximations and no need for pre-actuation. The effectiveness of the proposed approach is assessed by three numerical test cases, by comparing it with some meaningful benchmarks taken from the literature. Finally, experimental verification through an underactuated robotic arm with two degrees of freedom is performed.

Supernumerary Robotic Limbs to Assist Human Walking With Load Carriage


Walking with load carriage is a common requirement for individuals in many situations. Legged exoskeletons can transfer the load weight to the ground with rigid-leg structures, thus reducing the load weight borne by the human user. However, the inertia of paralleled structures and the mechanical joint tend to disturb natural motions of human limbs, leading to high-energy consumption. Different from exoskeletons, Supernumerary Robotic Limbs (SuperLimbs) are kinematically independent of the human limbs, thus avoiding the physical interference with the human limbs. In this paper, a SuperLimb system is proposed to assist the human walking with load carriage. The system has two rigid robotic limbs, and each robotic limb has four degrees-of-freedom (DOFs). The SuperLimbs can transfer the load weight to the ground through the rigid structures, thus reducing the weight borne by the human user. A hybrid control strategy is presented to assist the human as well as avoid disturbing user’s natural motions. Motions of the SuperLimb system are generated autonomously to follow the gait of the human user. The gait synchronization is controlled by a finite state machine, which uses inertial sensors to detect the human gait. Human walking experiments are conducted to verify this concept. Experiments indicate that the SuperLimbs can follow the human gait as well as distribute the load weight. Results show that our SuperLimb system can reduce 85.7% of load weight borne by the human when both robotic limbs support and 55.8% load weight on average. This study may inspire the design of other wearable robots and may provide efficient solutions for human loaded walking.
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