Sensors are a huge challenge for robotics. We have very precise force-feedback on our joints, pressure and heat (temperature gradient) sensors all over our body, and our hands have a sensor density that allows us to count needle heads and detect the exact grip strength needed by feeling the micro-slippage of objects in our hands. Robots don't have that.

You can do backflips with pretty much just visual sensors for your environment, a good IMU for your spatial orientation, and some feedback on the position of a small number of really beefy joints and the force exerted on them. Folding laundry and opening doors is much more difficult, and trying to compensate with mostly vision requires going slow enough that things have time to move over appreciable distances before you take the next adjustment

> We have very precise force-feedback on our joints, pressure and heat (temperature gradient) sensors all over our body

You can do all the same with robots. Current advantage of human that on top of imperfect sensor data we have hyper-efficient brain connecting all dots and making calculations and approximations, and this gap looks very closeable today.

Side note but I'm convinced that people wanting to improve touch sensitivity in robots need to look at frequency detail of tactile data, not spatial detail. Try this: Put your finger on a bumpy wall without moving it at all and see what you feel. Not much. Now move your finger across the wall. All sorts of detail jumps out. I think the human tactile system is reading changing pressure in the time domain and translating that into the spatial domain as the finger scans across the surface.