All the other technologies are increasing extremely rapidly but battery technology isn't.
We are at a point where a breakthrough in batteries would have an incredible effect across a huge number of fields.
[EDIT] - My point here is that even if improvements to battery technology remain slow or constant, with sufficient innovation in energy efficiency and algorithms, we could still have robots with usable to good running times. Just figuring out a reliable walking gait and building materials for passive dynamic walking can significantly reduce the power requirements.[3]
[1] - http://hypertextbook.com/facts/2001/JacquelineLing.shtml [2] - http://www.chem.hawaii.edu/uham/bat.html [3] - https://en.wikipedia.org/wiki/Passive_dynamics
The energy to raise a fixed mass a certain height isn't going to change.
Not to mention an electric car with a thousand mile range would be huge.
An average American man needs about 3400 Calories each day which corresponds to about 1 kg of oxygen consumed[1]. Similarly the average American woman uses 2550 Calories and .75 kg of oxygen.
[1] Design Rules for Life Support Systems http://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/2004001... [2] http://www.livescience.com/49157-how-fat-is-lost-body.html
The human brain uses the incredible 20 Watts to achieve things that modern megawatt supercomputers aren't capable of.
This is much more than the problem of not having good sensors, not having powerful enough actuators, or solving models. Without understanding the fundamental principles we may not even get the hardware right. Recall early attempts at heavier than air flight that attempted to copy and scale up a bird rather than understand the principles behind how wings worked.
1. The sensors?
2. The actuators?
3. Coming up with accurate dynamical models?
4. Solving the models accurately?
5. Solving the models efficiently?
6. Making the models robust to inaccuracy/noise?
Yes, I realize all of these are probably hard. What I'm trying to understand is whether the biggest challenge is coming up with e.g. an accurate (possibly nonlinear) dynamical model, or with solving the model (efficiency/accuracy), or with making existing models that are otherwise already completely accurate robust to outside noise, or with the manufacturing aspect (precision), or whatever.