Trajectory Optimization

This is not really intended as "ready to accept," but I wanted to start the conversation on trajectory optimization. I added (what I hope is) a pretty flexible framework for direct methods for traj opt, along with some implementations for some first-order integration schemes and direct collocation. The code is far from being speed-optimized, and I think one of the important discussions should be on how to prevent repeated, unnecessary calculations, similar to what Hongkai has with kinsol for inverse kinematics. 

I also added a ConstraintManager class, which is just intended to be a general interface for combining multiple constraints into one. I think this would be a good approach to describe more complex constraints, like support polygons and complementarity constraints.
Shockingly much faster to compute. I did a number of tests yesterday on various ways to pass these function handles in. It turns out that doing something like ```NLP.addDataFunction(@obj.dynamics) ;
   ...
   NLP.data_function(args{:});
```
is REALLY slow, whereas
```
 NLP.addDataFunction(FunctionWrapper(@obj.dynamics));
...
NLP.data_function.eval(args{:});
```
Is not. For the Acrobot Dircol case, the overhead increased runtime from 8 seconds to over 60. There are other 'fast' ways to do this, but after trying a whole bunch of options, this seemed the cleanest, not that I like it.