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Imagine getting by with a little help from your wearable robot friend. Nitin Sharma’s research group is doing just that in their latest research about to be published in the journal Automatica.  Here is their synopsis of the reported work:

Wearable robotic systems are increasingly being used for human augmentation in industrial and military applications and as assistive devices during rehabilitation. Current control strategies for wearable robots primarily use actuation from electric motors. In contrast, in this paper, we developed “a muscle first strategy” control that enables a human user to maximize skeletal muscle use or harness muscle’s inherent metabolic energy, via functional electrical stimulation (FES), and still use a rigid wearable robot. The strategy is potentially beneficial from both rehabilitation and augmentation aspects. A shared workload between externally stimulated muscles and a powered exoskeleton can improve lost muscle function, reduce actuator and power consumption, and thus make the overall system less bulky.

The paper presents a generalized theoretical result that uses two control modes: muscle mode and exoskeleton mode. Think of this control strategy as similar to a hybrid car (Toyota Prius), where one can switch between gasoline engine or electrical engine or a combination of both. We thought about conditions when it would be appropriate to switch from the muscle mode to the exoskeleton mode and vice versa (for example, when the muscle fatigues or when the muscle recovers from the fatigue). The derivation of these conditions is not straightforward because one has to consider modeling and performance issues related to the distinct actuation characteristics of a skeletal muscle vs. exoskeleton. We used a multiple Lyapunov functional analysis to derive state-dependent constraints on the switch criteria to ensure stable and smooth use of this hybrid muscle-exoskeleton system. We successfully demonstrated feasibility when human participants wearing a hybrid exoskeleton (developed in the Sharma Lab) performed a sit-to-stand task. This work was funded by the National Science Foundation, Award # 1646009.

Sheng, Z. Sun, V. Molazadeh et al., Switched control of an N-degree-of-freedom input delayed wearable robotic system. Automatica (2021) 109455,