# Taming the Panda with Python: A Powerful Duo for Seamless Robotics Programming and Integration

arXiv: https://arxiv.org/abs/2307.07633 · HTML: https://mlsanity.com/paper/2307.07633/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jul 2023.

## Built on by (most cited first, 10 of 10)

- [MALMM: Multi-Agent Large Language Models for Zero-Shot Robotics Manipulation](https://mlsanity.com/paper/2411.17636/) (2024)
- [Robot Control Stack: A Lean Ecosystem for Robot Learning at Scale](https://mlsanity.com/paper/2509.14932/) (2025)
- [Toward Artificial Palpation: Representation Learning of Touch on Soft Bodies](https://mlsanity.com/paper/2511.16596/) (2025)
- [CoBOS: Constraint-Based Online Scheduler for Human-Robot Collaboration](https://mlsanity.com/paper/2403.18459/) (2024)
- [Robot Policy Transfer with Online Demonstrations: An Active Reinforcement Learning Approach](https://mlsanity.com/paper/2503.12993/) (2025)
- [What Do You Need for Compositional Generalization in Diffusion Planning?](https://mlsanity.com/paper/2505.18083/) (2025)
- [DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation](https://mlsanity.com/paper/2509.04970/) (2025)
- [BLAZER: Bootstrapping LLM-based Manipulation Agents with Zero-Shot Data Generation](https://mlsanity.com/paper/2510.08572/) (2025)
- [Minimal Embodiment Enables Efficient Learning of Number Concepts in Robot](https://mlsanity.com/paper/2604.11373/) (2026)
- [More with LESS -- Local Scene Representations for Tactile Imaging](https://mlsanity.com/paper/2606.14344/) (2026)

## Abstract (arXiv)

Franka Emika robots have gained significant popularity in research and education due to their exceptional versatility and advanced capabilities. This work introduces panda-py - a Python interface and framework designed to empower Franka Emika robotics with accessible and efficient programming. The panda-py interface enhances the usability of Franka Emika robots, enabling researchers and educators to interact with them more effectively. By leveraging Python's simplicity and readability, users can quickly grasp the necessary programming concepts for robot control and manipulation. Moreover, integrating panda-py with other widely used Python packages in domains such as computer vision and machine learning amplifies the robot's capabilities. Researchers can seamlessly leverage the vast ecosystem of Python libraries, thereby enabling advanced perception, decision-making, and control functionalities. This compatibility facilitates the efficient development of sophisticated robotic applications, integrating state-of-the-art techniques from diverse domains without the added complexity of ROS.