  We designed a modular robotic control stack that provides a customizable and
accessible interface to the Franka Emika Panda Research robot. This framework
abstracts high-level robot control commands as skills, which are decomposed
into combinations of trajectory generators, feedback controllers, and
termination handlers. Low-level control is implemented in C++ and runs at
$1$kHz, and high-level commands are exposed in Python. In addition, external
sensor feedback, like estimated object poses, can be streamed to the low-level
controllers in real time. This modular approach allows us to quickly prototype
new control methods, which is essential for research applications. We have
applied this framework across a variety of real-world robot tasks in more than
$5$ published research papers. The framework is currently shared internally
with other robotics labs at Carnegie Mellon University, and we plan for a
public release in the near future.
