A Modular Robotic Arm Control Stack for Research: Franka-Interface and FrankaPy
Kevin Zhang, Mohit Sharma, Jacky Liang, and Oliver Kroemer

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 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 published research papers. The framework is currently shared internally with other robotics labs at Carnegie Mellon University, and…
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Taxonomy
TopicsRobot Manipulation and Learning · Modular Robots and Swarm Intelligence · Reinforcement Learning in Robotics
