A Modular Robotic Arm Control Stack for Research: Franka-Interface and FrankaPy

TL;DR

This paper presents a modular control framework for the Franka Emika Panda robot, enabling rapid prototyping of control methods through high-level Python interfaces and real-time low-level C++ control, supporting diverse research tasks.

Contribution

The authors introduce a flexible, modular control stack with a Python interface and real-time low-level control, facilitating research and rapid development of new control algorithms.

Findings

Applied across multiple real-world robot tasks

Used in over 5 published research papers

Supports real-time sensor feedback integration

Abstract

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.