Making encoders is a bitch, and dc motors are cheaper without them.
So it would be cool if u could get a robot to work without them.
Its a seemingly impossible thing, cause a legged robot cant even have a centre point for its motors to even just stand still! If you put mechanical end stops, then you can at least know the end point positions, that could help.
If you dont have positional information, the trick is maybe u could correllate it from accellerometre information over time, so you exchange the positional information for so many accellerometre samples and maybe its equivilent information!
So u just need to correllate it, with machine learning.
Its actually a little of a long story to explain it, but I think its possible! U just need to get in the right semantical/generation space to make it happen.
So if you take it from the position of searching inside of a physics engine (as the generation space), you predict the next accellerometre accelleration, from a chain of accellerometre data, and u step it each new frame, and the chain of accellerometre data is replacing the lack of angular position information, but it should be equivilent.
Then that should build the virtual copy of the physics, which lets u then brute force the robots motor commands to get the robot in action, WITHOUT encoders!
