方舟：一個基於Python的開源機器人學習框架

Ark: An Open-source Python-based Framework for Robot Learning

June 24, 2025

作者: Magnus Dierking, Christopher E. Mower, Sarthak Das, Huang Helong, Jiacheng Qiu, Cody Reading, Wei Chen, Huidong Liang, Huang Guowei, Jan Peters, Quan Xingyue, Jun Wang, Haitham Bou-Ammar

cs.AI

摘要

機器人學在硬件方面取得了顯著進展——從DARPA的城市與機器人挑戰賽到首屆人形機器人踢拳錦標賽——然而，商業自動化仍落後於機器學習的發展。一個主要瓶頸在於軟件：當前的機器人技術棧要求陡峭的學習曲線、低層次的C/C++專業知識、分散的工具集以及複雜的硬件集成，這與推動現代人工智能發展的以Python為中心、文檔完善的生態系統形成鮮明對比。我們推出了ARK，這是一個開源的、以Python為先的機器人框架，旨在彌合這一差距。ARK提供了一個Gym風格的環境接口，允許用戶收集數據、進行預處理，並使用最先進的模仿學習算法（如ACT、擴散策略）訓練策略，同時在高保真模擬與物理機器人之間無縫切換。輕量級的客戶端-服務器架構提供了網絡化的發布-訂閱通信，而可選的C/C++綁定確保了在需要時的實時性能。ARK附帶了可重用的模塊，用於控制、SLAM、運動規劃、系統識別和可視化，並具有原生ROS互操作性。全面的文檔和案例研究——從操作到移動導航——展示了快速原型設計、輕鬆的硬件更換以及與主流機器學習工作流程相媲美的端到端管道。通過在一個共同的Python框架下統一機器人學與人工智能實踐，ARK降低了入門門檻，並加速了自主機器人的研究與商業部署。

English

Robotics has made remarkable hardware strides-from DARPA's Urban and Robotics Challenges to the first humanoid-robot kickboxing tournament-yet commercial autonomy still lags behind progress in machine learning. A major bottleneck is software: current robot stacks demand steep learning curves, low-level C/C++ expertise, fragmented tooling, and intricate hardware integration, in stark contrast to the Python-centric, well-documented ecosystems that propelled modern AI. We introduce ARK, an open-source, Python-first robotics framework designed to close that gap. ARK presents a Gym-style environment interface that allows users to collect data, preprocess it, and train policies using state-of-the-art imitation-learning algorithms (e.g., ACT, Diffusion Policy) while seamlessly toggling between high-fidelity simulation and physical robots. A lightweight client-server architecture provides networked publisher-subscriber communication, and optional C/C++ bindings ensure real-time performance when needed. ARK ships with reusable modules for control, SLAM, motion planning, system identification, and visualization, along with native ROS interoperability. Comprehensive documentation and case studies-from manipulation to mobile navigation-demonstrate rapid prototyping, effortless hardware swapping, and end-to-end pipelines that rival the convenience of mainstream machine-learning workflows. By unifying robotics and AI practices under a common Python umbrella, ARK lowers entry barriers and accelerates research and commercial deployment of autonomous robots.