Popular culture has usually depicted robots as chilly, metallic, and menacing, constructed for domination, not compassion. However at Georgia Tech, the way forward for robotics is softer, smarter, and designed to assist.
“When folks consider robots, they normally think about one thing like The Terminator or RoboCop: large, inflexible, and manufactured from metallic,” mentioned Hong Yeo, the G.P. “Bud” Peterson and Valerie H. Peterson Professor on the George W. Woodruff College of Mechanical Engineering. “However what we’re creating is the alternative. These synthetic muscle groups are comfortable, versatile, and responsive—extra like human tissue than machine.”
Yeo’s newest examine, printed in Supplies Horizons, explores AI-powered muscle groups constructed from lifelike supplies paired with clever management techniques. The know-how learns from the physique and adapts in actual time, creating movement that feels pure, responsive, and protected sufficient to assist restoration.
Muscle tissue that assume, supplies that really feel
Conventional robotics depends on metal, wires, and motors, however hardly ever captures the nuances of human movement. Yeo’s analysis takes a special method. He makes use of hierarchically structured fibers, that are versatile supplies inbuilt layers, very like muscle and tendon. They’ll sense, adapt, and even “keep in mind” how they’ve moved earlier than.
Yeo trains machine studying algorithms to regulate these pliable supplies in actual time with the correct amount of power or flexibility for every activity.
“These muscle groups do not solely reply to instructions,” Yeo mentioned. “They be taught from expertise. They’ll adapt and self-correct, which makes movement smoother and extra pure.”
The results of that analysis is deeply human. For somebody recovering from a stroke or limb loss, every deliberate motion rebuilds not simply energy—it rebuilds confidence, independence, and a way of self.
A glove that provides freedom again
One of many first real-world purposes is a prosthetic glove powered by synthetic muscle groups (printed in ACS Nano), a tool that behaves extra like a serving to hand than a mechanical software. Conventional prosthetics depend on inflexible motors and preset motions, however Yeo’s design mirrors the pure give-and-take of actual muscle.
Contained in the glove, skinny layers of stretchable fibers and sensors contract, twist, and flex in sync with the wearer’s intent. The glove can fine-tune grip energy, scale back tremors, and reply immediately to the person’s actions, bringing dexterity again to on a regular basis life.
That sort of precision issues most within the smallest duties: fastening a button, lifting a glass, holding a baby’s hand.
“These aren’t simply actions,” Yeo mentioned. “They’re freedoms.”
For Yeo, the thought of restoring freedom by motion has pushed his analysis from the very starting.
A mission rooted in loss
Yeo’s work is deeply private. His path to biomedical engineering started with loss—the sudden demise of his father whereas Yeo was nonetheless in school. That second reshaped his sense of objective, redirecting his focus from machines that transfer to applied sciences that heal.
“Initially, I used to be excited about designing vehicles,” he mentioned. “However after my father’s demise, I sort of awoke. Perhaps I may do one thing that helps save somebody’s life.”
That objective continues to information his lab’s work immediately, constructing applied sciences that assist folks get well what they’ve misplaced.
Attaining that imaginative and prescient, nonetheless, means tackling a few of engineering’s hardest challenges.
Gentle machines, arduous issues
Creating lifelike muscle groups is not simple. They have to be comfortable however sturdy, responsive however protected. They usually should keep away from triggering the physique’s immune system. Which means constructing supplies that may survive contained in the physique—and be taught to belong there.
“We all the time take into consideration not solely operate, however adaptability,” Yeo mentioned. “If it’ll be a part of somebody’s physique, it has to work with them, not in opposition to them.”
His group calibrates these artificial fibers like precision devices—examined, adjusted, and re-tuned till they function in sync with the physique’s pure actions. Over time, they develop a sort of “muscle reminiscence,” adapting fluidly to altering circumstances. That dynamic adaptability, Yeo defined, is what separates a machine from a prosthetic that actually feels alive.
From collaboration to innovation
Fixing issues this advanced requires multiple self-discipline. It takes a complete ecosystem of collaboration. Yeo’s lab brings collectively consultants in mechanical engineering, supplies science, drugs, and pc science to design smarter, safer gadgets.
“You possibly can’t resolve this type of downside in isolation,” he mentioned. “We’d like all of it—polymers, synthetic intelligence, biomechanics—working collectively.”
His group now works intently with well being care suppliers and business companions to deliver these gadgets out of the lab and into sufferers’ lives.
The longer term you possibly can really feel
The way forward for robotics, in accordance with Yeo, will not be outlined by energy or complexity however by really feel.
“If it feels overseas, folks will not use it,” he mentioned. “But when it looks like a part of you, that is when it could possibly actually change lives.”
It is the alternative of The Terminator, the place machines substitute us. Yeo is designing these machines to assist us reclaim ourselves.
Extra info:
Saewoong Oh et al, Empowering synthetic muscle groups with intelligence: latest developments in supplies, designs, and manufacturing, Supplies Horizons (2025). DOI: 10.1039/d5mh00236b
Tae Woog Kang et al, Gentle Nanomembrane Sensor-Enabled Wearable Multimodal Sensing and Suggestions System for Higher-Limb Sensory Impairment Help, ACS Nano (2025). DOI: 10.1021/acsnano.4c15530
Georgia Institute of Expertise
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Human-centric comfortable robotics flip the script on ‘The Terminator’ (2025, October 30)
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