Exoskeletons are always presented in a repetitive steady-state environment, such as walking, running, sorting, or stacking. But how do they perform in a one-off activity, such as jumping? Can you even jump in a powered exoskeleton that was designed for walking? Will the device’s weight hold you down, or can the wearable robot compensate for the mass of the batteries, controller, straps, and motors? Emily Bywater from the Neurobionics Lab in the University of Michigan Robotics Department took the Dephy powered ankle exoskeleton and went to answer all these questions and more. Her findings were then presented in a two-part video prepared by the University of Michigan:
With some help from Professor Elliott Rouse and other lab mates, Emily Bywater designed and developed the control algorithms for jumping and tested it against 19 participants who jumped with the powered exo, without it, and with the device turned off from a shallow and deep squat. The results? The Dephy ExoBoot could compensate for its weight of 5.5 kg (12 lbs.) and add an additional inch of height compared to jumping without an exoskeleton condition. The entire experiment is elegantly summarized in 10 minutes (see the video below), and the presentation also provides insight into the inner workings of the Dephy ExoBoot.
The panel goes through early examples of real-life exoskeletons, starting with early-stage US military investments. The discussion then touches upon shifting the focus away from building an exoskeleton for the sake of making one to building an exoskeleton for a specific purpose or task. The discussion quickly jumps to other topics like safety, getting from research to users (getting out of the lab, finding the right metrics, discovering what “comfort” means for each user, how to seamlessly transition from one task to another), what are the limits of the technology, and more. The panel moves quickly and cannot dig deep into the topics, but at least it touches on many current issues surrounding wearable technology.
The next frontier in building motorized exoskeletons will be learning to control them best. This can include mode switching, individual user customization, or getting the timing and torque right to execute a jump.
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