> This means the sensor can tell you where you bent it, with a predefined (and coarse) resolution.

> OptiGap’s application is mainly within the realm of soft robotics, which typically involves compliant (or ‘squishy’) systems, where the use of traditional sensors is often not practical.

This explanation is already quite clear. If I understood correctly, by "predefined resolution" you mean that it detects which silicone sleeve was bent on a tube with a series of them, correct?

Can you provide more concrete examples for how you envision it being used? The first application that comes to mind is sensing how fingers bend in a glove controller.

The finger bending example is certainly a classic for something like this but I think it truly shines in soft robot examples like flapping wing robots or swimming finned robot, where it's critical for sensors to be mechanically transparent so as to not impact the usually delicate dynamics. The "soft" robotic arm in my earlier paper is another good example https://ieeexplore.ieee.org/document/9763962

Also; if you can please include examples of practical use cases. I am sure there are tons, but I always love discovering complexity in hidden places

Yeah. I guess in layman's terms it's a long squishy cable that knows where it's being bent.

Have a quick recording that shows an outcome or effect that is a core part of the research.

Having just read the piece for the first time after you added the "bent rope" explanation: YOU NAILED IT. I literally had the reaction of thinking, "Wow, there's a super simple explanation early on! I trust this writer much more now."