[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-92523":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":9,"language":10,"languages":9,"totalLinesOfCode":9,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":15,"stars7d":15,"stars30d":16,"stars90d":15,"forks30d":15,"starsTrendScore":15,"compositeScore":17,"rankGlobal":9,"rankLanguage":9,"license":18,"archived":19,"fork":19,"defaultBranch":20,"hasWiki":19,"hasPages":19,"topics":21,"createdAt":9,"pushedAt":9,"updatedAt":22,"readmeContent":23,"aiSummary":24,"trendingCount":15,"starSnapshotCount":15,"syncStatus":25,"lastSyncTime":26,"discoverSource":27},92523,"RoboDojo","RoboDojo-Benchmark\u002FRoboDojo","RoboDojo-Benchmark","Official Repo of RoboDojo",null,"Python",197,11,54,3,0,122,53.24,"MIT License",false,"main",[],"2026-07-22 04:02:06","\u003Cdiv align=\"center\">\n\n\u003Cimg src=\"https:\u002F\u002Fmedia.luminis-sim.com\u002Fmedia\u002Fchallenge\u002Fposters\u002Frobodojo_logo.png\">\u003C\u002Fimg>\n\n\u003Ch2 align=\"center\">RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies\u003C\u002Fh2>\n\n\u003Ch2 align=\"center\">\u003Ca href=\"https:\u002F\u002Frobodojo-benchmark.com\u002F\">Webpage\u003C\u002Fa> | \u003Ca href=\"https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002F\">Document\u003C\u002Fa> | \u003Ca href=\"https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.04434\">Paper\u003C\u002Fa> | \u003Ca href=\"https:\u002F\u002Frobodojo-benchmark.com\u002Fcommunity\">Community\u003C\u002Fa> | \u003Ca href=\"https:\u002F\u002Frobodojo-benchmark.com\u002Fleaderboard\">Leaderboard\u003C\u002Fa>\u003C\u002Fh2>\n\n\u003C\u002Fdiv>\n\nhttps:\u002F\u002Fprivate-user-images.githubusercontent.com\u002F88101805\u002F619409345-cc074c5d-4567-4418-8a29-1385aaba9d5b.mp4\n\n## ✨ Highlights\n\n\u003Cp align=\"center\">\n  \u003Cimg src=\"https:\u002F\u002Fmedia.luminis-sim.com\u002Fmedia\u002Fhome\u002Fteaser.png\" width=\"70%\">\u003C\u002Fimg>\n\u003C\u002Fp>\n\n\u003Cp align=\"center\">\u003Cem>Overview of RoboDojo. RoboDojo unifies efficient simulation evaluation and reproducible real-world testing for generalist robot manipulation, covering 42 simulation tasks, 18 real-world tasks, heterogeneous parallel simulation, RoboDojo-RealEval, XPolicyLab, and a continuously updated leaderboard.\u003C\u002Fem>\u003C\u002Fp>\n\n> RoboDojo is **eval-only** in this release: it provides the simulator client, benchmark tasks, asset\u002Fconfig validation, and result artifacts. Policy integration and policy servers are owned by [XPolicyLab](https:\u002F\u002Fgithub.com\u002FXPolicyLab\u002FXPolicyLab\u002Fblob\u002Fmain\u002FREADME.md).\n\n- 🌐 **Unified sim-and-real benchmark** — 42 simulation tasks and 18 real-world tasks across 3 robot embodiments for generalist robot manipulation.\n- 🧭 **Five capability dimensions** — Generalization, Memory, Precision, Long-Horizon, and Open, designed to probe different skills rather than simple object or layout reskins.\n- 🧗 **Challenging by design** — intentionally hard, diverse, long-horizon tasks that expose failures hidden by simpler benchmarks.\n- ⚡ **Heterogeneous parallel simulation** — runs different tasks, scenes, and processes concurrently on Isaac Sim for fast, scalable feedback.\n- 🧱 **Physically grounded assets** — rigid, articulated, and deformable objects in a single configuration-driven scene.\n- 🤖 **Integrate once, evaluate everywhere** — [XPolicyLab](https:\u002F\u002Fgithub.com\u002FXPolicyLab\u002FXPolicyLab\u002Fblob\u002Fmain\u002FREADME.md) unifies 40+ policies behind one interface for both simulation and real-world runs.\n- 📊 **Reproducible & leaderboard-ready** — seed-controlled layouts and one-command `summarize` aggregation into a leaderboard table.\n\n## 📚 Documentation\n\nThe [RoboDojo documentation](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002F) is the canonical reference. Key sections:\n\n| Section | Description |\n| :-- | :-- |\n| [Usage Overview](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Fusage\u002F) | End-to-end walkthrough of the evaluation workflow. |\n| [Installation & Downloading (Assets and Data)](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Fusage\u002Finstall-and-download\u002F) | Environment setup and downloading robot\u002Fobject\u002Flayout assets\u002Ftraining data. |\n| [Quick Evaluation](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Fusage\u002Fevaluation\u002F) | Quickly dispatch XPolicyLab to run a policy for testing. |\n| [XPolicyLab](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Fusage\u002FXPolicyLab\u002F) | Integrates a large collection of policies and defines how to integrate new ones. |\n| [Simulation Tasks Details](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Ftasks\u002F) | The 42 Isaac Sim tasks across five capability dimensions. |\n| [Real Robot Tasks Details](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Freal-tasks\u002F) | The 18 real-world tasks on Piper X, Piper, and ARX X5. |\n| [Configurations](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Fusage\u002Fconfigurations\u002F) | Simulator, scene, robot, and camera configuration options. |\n| [Common Issues](https:\u002F\u002Frobodojo-benchmark.com\u002Fdoc\u002Fcommon-issue\u002F) | Troubleshooting for installation, assets, GPU memory, and evaluation. |\n\n## 🗂️ Repository Structure\n\n```text\nenv\u002F                   simulator backbone and managers\nenv_cfg\u002F               simulator, scene, robot, and camera configs\ntask\u002FRoboDojo\u002F         task logic and task YAML configs\nscripts\u002Frobodojo.sh    public RoboDojo-side eval entry\nscripts\u002Feval_policy.sh simulator client launched by XPolicyLab eval.sh\nXPolicyLab\u002F            policy server and policy integrations\nAssets\u002F                downloaded robot, object, material, and layout assets\n```\n\n## 🔌 Policy Integration\n\nPolicies live in [XPolicyLab](https:\u002F\u002Fgithub.com\u002FXPolicyLab\u002FXPolicyLab\u002Fblob\u002Fmain\u002FREADME.md), which owns policy structure, dependencies, checkpoint layout, and server behavior. RoboDojo only assumes a policy directory provides:\n\n```text\nXPolicyLab\u002Fpolicy\u002F\u003CPOLICY_NAME>\u002Feval.sh\nXPolicyLab\u002Fpolicy\u002F\u003CPOLICY_NAME>\u002Fdeploy.yml\n```\n\n`eval.sh` starts the policy server and calls back into RoboDojo through `scripts\u002Feval_policy.sh`; `deploy.yml` declares the server host, port, action mode, and policy-specific runtime settings.\n\n## 🏆 Leaderboard\n\nView live rankings on the [RoboDojo Leaderboard](https:\u002F\u002Frobodojo-benchmark.com\u002Fleaderboard).\n\n**Simulation.** The full evaluation stack is open source, so you can debug locally and iterate on scores. Official RoboDojo-endorsed listings are submitted through the cloud evaluation pipeline with anti-cheating verification.\n\n**Real world.** Real-robot leaderboard entries are accepted through the same cloud evaluation process; see the public documentation for protocol, rules, and submission details.\n\n## 📝 Citation\n\n**RoboDojo**\n\n```bibtex\n@misc{chen2026robodojounifiedsimandrealbenchmark,\n      title={RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies}, \n      author={Tianxing Chen and Yue Chen and Zixuan Li and Junyuan Tang and Kailun Su and Haoran Lu and Weijie Wan and Baijun Chen and Songling Liu and Haowen Yan and Honghao Su and Zhiyang Dou and Kaixuan Wang and Dandan Zhang and Yunze Liu and Yan Qin and Qiwei Liang and Qiwei Wu and Zijian Lin and Wenwei Lin and Yuran Wang and Minghua He and Tianshu Wu and Ruihai Wu and Jingquan Zhou and Kai-Chong Lei and Haibao Yu and Yuanfeng Ji and Weiyang Jin and Guanyu Lin and Xiaofan Li and Qi Xiong and Renjing Xu and Zhongyu Li and Wenhao Chai and Enze Xie and Ziwei Wang and Yao Mu and Hao Dong and Wojciech Matusik and Mingyu Ding and Wenbo Ding and Ping Luo and Masayoshi Tomizuka},\n      year={2026},\n      eprint={2607.04434},\n      archivePrefix={arXiv},\n      primaryClass={cs.RO},\n      url={https:\u002F\u002Farxiv.org\u002Fabs\u002F2607.04434}, \n}\n```\n\n**RoboTwin 2.0**\n\n```bibtex\n@article{chen2025robotwin,\n  title={Robotwin 2.0: A scalable data generator and benchmark with strong domain randomization for robust bimanual robotic manipulation},\n  author={Chen, Tianxing and Chen, Zanxin and Chen, Baijun and Cai, Zijian and Liu, Yibin and Li, Zixuan and Liang, Qiwei and Lin, Xianliang and Ge, Yiheng and Gu, Zhenyu and others},\n  journal={arXiv preprint arXiv:2506.18088},\n  year={2025}\n}\n```\n\n**MagicSim**\n\n```bibtex\n@misc{lu2026magicsimunifiedinfrastructureexecutable,\n      title={MagicSim: A Unified Infrastructure for Executable Embodied Interaction}, \n      author={Haoran Lu and Songling Liu and Yue Chen and Guo Ye and Mutian Shen and Shuyang Yu and Yu Xiao and Jihai Zhao and Shang Wu and Jianshu Zhang and Xiangtian Gui and Chuye Hong and Yuran Wang and Maojiang Su and Jiayi Wang and Ruihai Wu and Zhaoran Wang and Han Liu},\n      year={2026},\n      eprint={2606.17511},\n      archivePrefix={arXiv},\n      primaryClass={cs.RO},\n      url={https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.17511}, \n}\n```\n\n## 🙏 Acknowledgements\n\nRoboDojo builds on [Isaac Sim](https:\u002F\u002Fdeveloper.nvidia.com\u002Fisaac\u002Fsim), [IsaacLab](https:\u002F\u002Fgithub.com\u002Fisaac-sim\u002FIsaacLab), [IsaacLab-Arena](https:\u002F\u002Fgithub.com\u002Fisaac-sim\u002FIsaacLab-Arena), [RoboTwin 2.0](https:\u002F\u002Fgithub.com\u002Frobotwin-Platform\u002Frobotwin), [XPolicyLab](https:\u002F\u002Fgithub.com\u002FXPolicyLab\u002FXPolicyLab), and [MagicSim](https:\u002F\u002Farxiv.org\u002Fabs\u002F2606.17511). We thank the authors and maintainers for their open-source contributions to the robotics community.\n\nContact [Tianxing Chen](https:\u002F\u002Ftianxingchen.github.io\u002F) or [Yue Chen](https:\u002F\u002Fyuechen0614.github.io\u002F) if you have questions or suggestions.\n\n## 🏫 Affiliations\n\nRoboDojo is operated by **AI MMLab Club**, a non-profit, vendor-neutral organization, and is jointly maintained and supported by a global consortium of academic institutional partners. To preserve the fairness, neutrality, and independence of the official evaluation, RoboDojo does not involve commercial companies in its governance, operation, funding, sponsorship, compute, hardware, or other forms of project support. For inquiries from academic or non-profit partners regarding project collaboration or resource support, please contact [RoboDojoCommittee@gmail.com](mailto:RoboDojoCommittee@gmail.com).\n\n\u003Cimg src=\"https:\u002F\u002Fmedia.luminis-sim.com\u002Fmedia\u002Fhome\u002Fpartners\u002Faffiliations.png\">\u003C\u002Fimg>\n\n## ⚖️ License\n\nReleased under the [RoboDojo Non-Commercial Research License](LICENSE). RoboDojo is available for non-commercial research, education, and evaluation only. Commercial use requires prior written permission from the maintainers.\n\n\n\u003Cp align=\"center\">\n  \u003Cimg alt=\"Python 3.11\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPython-3.11-475569?style=flat-square&logo=python&logoColor=white&labelColor=64748b\" height=\"22\"\u002F> \n  \u003Cimg alt=\"Isaac Sim 5.1\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIsaac_Sim-5.1-475569?style=flat-square&logo=nvidia&logoColor=76B900&labelColor=64748b\" height=\"22\"\u002F> \n  \u003Cimg alt=\"Isaac Lab 2.3\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FIsaac_Lab-2.3-475569?style=flat-square&logo=nvidia&logoColor=76B900&labelColor=64748b\" height=\"22\"\u002F> \n  \u003Cimg alt=\"License Non-Commercial\" src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-Non--Commercial-475569?style=flat-square&labelColor=64748b\" height=\"22\"\u002F>\n\u003C\u002Fp>\n","RoboDojo 是一个面向通用机器人操作策略的统一仿真与真实世界联合评测基准。它提供42个仿真任务和18个真实世界任务，覆盖3种机器人本体，从泛化性、记忆性、精度、长视野和开放性五个维度系统评估策略能力；支持基于Isaac Sim的异构并行仿真、物理一致的刚体\u002F关节\u002F可变形物体建模，并通过标准化接口与XPolicyLab策略库对接，实现一键结果汇总与 leaderboard 提交。适用于机器人学习、具身智能、操作策略研发等需跨仿真-现实验证的研究与工程场景。",2,"2026-07-09 02:30:14","CREATED_QUERY"]