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ASME Journal of Mechanisms and Robotics

  • Special Issue: Selected Papers From IDETC-CIE 2020
    by Ben-Tzvi P, Notash L, Voglewede P. on May 3, 2021 at 12:00 am

    This special issue of the ASME Journal of Mechanisms and Robotics is a compendium of 25 of the best papers submitted and presented at the 44th ASME Mechanisms and Robotics Conference during the 2020 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE 2020).

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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