Having taken Tedrake's underactuated robotics class which uses Drake's python bindings, it is an amazing collection of tools and examples of algorithms. Really great for learning.

I would say is very focused on research and quick prototyping, however.

MIT Driverless experimented with using Drake in 2018-19 race car, but we found that just implementing everything in eigen was more flexible, removed a dependency, and more transparent for tinkering.

Not if the smalltalkers get there first

Not if CPU's are fast enough to do it in Julia :-)

Ah, Julia shares my goals, but I really don't like it's methods.

To be we absolutely need static types and super high level stuff to both:

- keep the code closer to it's purpose

(e.g. do linear algebra and proof of why this program does the stats you want it to together)

- be super architecture agnostic

(With lambda generalized to arbitrary categorizes we can just elaborate to Vect and fuse functional pipelines with matrix multiplication).

(https://ncatlab.org/nlab/show/Vect)

"Model-based design and verification for robotics."

>Drake (“dragon” in Middle English) is a C++ toolbox started by the Robot Locomotion Group at the MIT Computer Science and Artificial Intelligence Lab (CSAIL).

I thought this was going to be https://www.factual.com/blog/introducing-drake-a-kind-of-mak...

Cmake project that depends on a specific distribution to be built _from source_? I know, it's 2020, we have Docker and things, but but but that's not how it works folks!