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    Home»Artificial Intelligence»This design software reimagines everyday objects as self-aware devices | MIT News
    Artificial Intelligence

    This design software reimagines everyday objects as self-aware devices | MIT News

    InfoForTechBy InfoForTechOctober 23, 2026No Comments4 Mins Read
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    This design software reimagines everyday objects as self-aware devices | MIT News
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    Jiaji Li and lead author Xiang Chang, a TJU PhD student and visiting researcher at CSAIL, used X-Hinges to create many clever devices. For example, they made a glove that can teach a robot how to grasp blocks. It adjusts to the size of a user’s hands, then records how the joints in their fingers bend via sensors before rapidly relaying that information to a humanoid hand to mimic it. The glove could be useful in factories or homes, where a robot often needs to learn new interactions quickly.

    The researchers also produced a small, origami-style lamp using X-Hinges. It senses when a human pinches it closed and adjusts its brightness accordingly. When you turn on this adaptive, portable light source (sort of like a reading light), it looks like a piece of folded-up paper that sprouts into a lamp.

    X-Hinges can even assemble devices that identify which objects have been placed on it. You could put a banana on top, for instance, and it’ll recognize the fruit almost immediately based on the tactile data it’s recorded using its sensors. This advanced physical awareness could be integrated into detection systems in places such as airports and grocery stores. 

    Behind each of the scientists’ creations is an easy-to-use interface that helps you design interactive objects from scratch. Users can choose how each part of their design looks and moves, just as the researchers did when making a video game controller that resembles a cartoon shark.

    X-Hinges gives you four shapes to choose from: a custom option, cylinder, rectangle, and thin outline. To recreate the unique look of a shark’s tail, the researchers designed their own shape. They then chose how the toy bent, opting for its tail to move up and down, sort of like a joystick. Finally, the program embedded the sensors, and the scientists 3D-printed their device.

    The researchers say that X-Hinges’ diverse motions are a novel feature compared to past attempts to 3D-print responsive everyday objects. “Most methods only allow for one axis of motion, often due to signal interference. X-Hinges enables your 3D-printed item to move from three angles,” says Chang. “Ultimately, you get a design with the intended movement you want. It also records motion data in each of those areas at the same time, making the device responsive to different kinds of interactions.”

    The tool could help realize the untapped potential of the seemingly mundane. Objects we use every day for a specific purpose, like a water bottle for drinking or a lamp for lighting, could become interactive gadgets. Much like how a chatbot uses a sort of digital intelligence to answer your prompts, an object could leverage a kind of physical intelligence to execute a physical task when users interact with it.

    For now, though, X-Hinges faces a calibration bottleneck. Each time an item is 3D-printed, its layout of electrical elements varies slightly, so two devices that appear identical from the outside may not make the same sensor readings. This is crucial if you’re building a deformable fitness glove, for instance, for two separate users. To fix this, Chang and Li built a computer vision system that can recalibrate outputs to align, ensuring data is accurate across two of the same items, although they hope to develop a built-in signal recalibration mechanism in the future.

    That ambition traces back to the throughline in Jiaji Li’s own research: letting actuation and sensing “grow” directly inside a 3D-printed object, instead of adding them on afterward. He previously built printed tendon-driven mechanisms that gave objects the ability to move; X-Hinges is how he’s now building on the ability to sense. The next step, he says, is combining the two in a single print — it’s actuation and sensing born together in the same fabrication process, opening the door to new physical platforms for embodied intelligence and AI agents.

    Chang and Li wrote the paper with MIT associate professor of EECS and CSAIL principal investigator Stefanie Mueller and recent TJU graduate Haiyang Yan. Their work was supported, in part, by a postdoctoral research fellowship from Zhejiang University and the MIT-GIST Program.

    The researchers will present their work at the ACM Symposium on User Interface Software and Technology in early November.

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