AI-driven exoskeleton lightens your load and elevates performance

A groundbreaking AI-powered exoskeleton developed by researchers at North Carolina State University and the University of North Carolina at Chapel Hill promises to be a game-changer for individuals with mobility issues.

I showed off a similar technology and got a mountain of messages asking if there was an application for disabled folks.  This new exoskeleton could very well be that help.

The wearable technology provides unprecedented energy savings during human movement, making users feel as if they’re carrying 26 pounds less. This results in significant improvements in athletic performance and daily life activities.

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Credit: NCSU

The power of digital twin simulations

The secret behind this revolutionary exoskeleton lies in sophisticated digital twin simulations, where humans and machines coexist, learning and adapting through millions of iterations to perfect physical assistance. The exoskeleton’s AI algorithm, still in development, goes beyond traditional machine learning focused on simulations and games, venturing into a new frontier where technology directly enhances human capabilities.

Credit: NCSU

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Data-driven and physics-informed reinforcement learning

The researchers have embraced data-driven and physics-informed reinforcement learning, an approach that ensures their wearable robots are not just smart but also intuitive, aligning with their mission to improve human mobility and health. This cutting-edge technology maps sensor inputs from the robot to assistive torque without any intermediate steps, enabling end-to-end control.

Credit: NCSU

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Versatile assistance across multiple activities

One of the most remarkable features of this exoskeleton is its ability to generate synergistic assistance across various activities, including walking, running, and stair climbing. The learned controller automatically adapts to each user’s different kinematic patterns, accommodating transitions between activities seamlessly without the need for handcrafted control.

Credit: NCSU

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Unprecedented metabolic cost reduction

The experimental results are nothing short of impressive. Among state-of-the-art portable exoskeletons, the exoskeleton achieved the greatest metabolic cost reduction for walking (24.3%), running (13.1%), and stair climbing (15.4%). This remarkable achievement stems from the experiment-free and versatile control approach, which eliminates the need for lengthy human tests and handcrafted rules.

Credit: NCSU

How much will the exoskeleton cost?

We spoke to Hao Su, Ph.D., Associate Professor at North Carolina State University and the University of North Carolina at Chapel Hill. He is also the Director of Biomechatronics and Intelligent Robotics Lab(BIRO), and he told us,

While the exoskeleton price is about $50,000 to $120,000 due to research and development costs and actuators, our approach can significantly reduce the R&D cost by leveraging our efficient learning-in-simulation framework, which allows for rapid design and testing in computer simulations rather than intensive testing on humans and physical robots. Looking forward, we plan to make our robots truly affordable and accessible through innovative hardware design, namely low-ratio gears and cost-effective but high-torque electric motors. In about one year, we aim to make our exoskeletons for sale at a price range of $1,500 to $4,000, depending on specific features and manufacturing scale.

Kurt’s key takeaways

This AI-powered exoskeleton marks a major advancement in wearable robotics. It offers the rapid development and widespread adoption of assistive robots for both able-bodied and mobility-impaired individuals. This technology has the potential to revolutionize the field of exoskeletons, paving the way for a future where mobility is no longer a barrier and eliminates the hurdles of movement limitations.

What activities or tasks do you struggle with currently that this type of wearable robotic assistance could help make easier or more accessible? Let us know in the comments below.

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