When sharpening knives, with practice you can tell when you are done by sliding your fingertips along (not across) the sharpened bevel. It's possible to feel imperfections measured in micrometers this way.
Not advanced maths per se; neural networks are amazing! Fuzzy matching based on experience - taken to an incredible level. And, tuneable by internal simulation (imagination).
The second thing about microslippage is why I, even though I would say I'm transhumanist, would only ever go full cyborg if the robot parts had a sense of touch.
I don't wanna pet my dog and not only not feel their fur, but also end up crushing them with my super strength.
If you're about to walk into a bar with you head, or like the top of a doorpost or smt. You'll instinctively pull back and avoid the obstacle, inches before it hurts, because your brain notice the hairs on your head moved. That's why men who have recently gone bald, often have bumps and bruises on their head. My bald colleague told me that for him, that was the hardest thing about going bald.
Throwing and catching always amaze me. And it's not something that everyone is always great at, for sure, but anyone can try to toss a wad of paper into the waste basket. Whether or not you make it, the calculations under the hood, happening so quickly, always astound me to think about.
I always imagine it more like neural networks. simply based on a lot of training and experience. As an example think of times when you step onto a non moving escalator. Your mind definitely knows its not moving but you still can't defeat the trained expectation of jerk.
Most people who've been juggling for awhile don't need too much additional practice to be able to do at least a few blindfolded catches just because of how consistent your throws get after awhile.
The other thing that's interesting is how pattern recognition in flying things people aren't generally used to seeing develops. I used to play ultimate, and when people start learning how a frisbee flies they might be susceptible to chasing it down by following along the path of the disc rather than moving directly to where it's going to end up. This is sometimes called dogging the disc because (many) dogs do the same thing. But then you learn to "read" the disc and you can tell by the flight path and angle of the disc where it's going to land.
I always thought about how interesting it is that handing things to people is so reliable. We just kind of know exactly when the other person has grabbed something enough for us to let go.
A lot of it is the difference between learning practically and learning theoretically. You don't have to understand the underlying mechanics in practice to know how to keep getting the same result. Your brain doesn't have to be doing any math, it just has to have shaken a bottle enough times to have a good comparative basis formed.
Learning to calculate the current remaining volume in a container when observing someone else shake it.... that would use all that theoretical knowledge and math.
It's like knowing how hard you have to throw an egg at a wall for it to break instead of bounce off. You do it 100 times, you just get a good feel for it. Doing all the math, and then trying to learn it practically is barely gonna affect how quickly you learn it in practice. But if you wanted to make a robot that throws it exactly hard enough without wasting any energy, practical knowledge will have almost no value, and theory and math will be incredibly valuable.
This is coming from someone who does indeed have the whole "passive trajectory analysis of every moving object around me" thing. I can't do crowds or drive at busy times. But, for moving through a minor crowd while reading a book, or pulling into a tight parking space while other cars are moving around near me, it's very helpful. I have good spatial awareness in general, like parking in my garage with only an inch of clearance on the far side of my car has never been an issue in 14 years so far. Or when doing it with someone else's borrowed car every now and then too. When I shrug off the difficulty of doing something like that, people seem to be amazed. Otherwise, I would have assumed it was normal, feels normal to me.
The overwhelming majority of all neurons in our body are just for controlling movement. Ironically, things like language or creativity require very little of our computing power and might be replicated by machine learning and a sufficiently beefy computer. But complex motor tasks? We're way ahead of our current tech on that.