Drake: Model-based design in the age of robotics and machine learning

When I joined Toyota Research Institute (TRI) more than five years ago, I believed that an industrial research lab like TRI could make fundamental contributions to robotics that would be hard to make in an academic lab or a startup. And I joined with a commitment that we would share our best tools and results with the world through open-source software. Just before joining TRI, I competed in the DARPA Robotics Challenge to program a humanoid robot for nearly-autonomous operation in a disaster response scenario. This experience gave me a deep appreciation for the value of software engineering and helped me realize the world has never seen truly mature implementations of the best ideas from control theory, machine learning, mathematical optimization, and verification applied to robots at scale. The introduction of scale and real-world testing poses a host of basic research challenges that simply aren't visible in simpler prototypes.