RoboChallenge：大规模真机器人评估具身策略
机器人学
2025-10-22 v1
摘要
在机器人控制算法中，测试真实机器人是不可或缺的。对于基于学习的算法，尤其是 VLA 模型，大规模评估的需求日益紧迫，即在大量任务上测试大量模型。然而，尽管如此，一旦考虑到可扩展性和可重复性，实际操作却极其不容易。 In this report, we describe our methodology for constructing RoboChallenge, an online evaluation system to test robotic control algorithms, and our survey of recent state-of-the-art VLA models using our initial benchmark Table30. 我们描述了构建 RoboChallenge 的方法论，这是一个用于测试机器人控制算法的在线评估系统，并介绍了我们使用初始基准 Table30 对最近最先进 VLA 模型的调查。
引用
@article{arxiv.2510.17950,
title = {RoboChallenge: Large-scale Real-robot Evaluation of Embodied Policies},
author = {Adina Yakefu and Bin Xie and Chongyang Xu and Enwen Zhang and Erjin Zhou and Fan Jia and Haitao Yang and Haoqiang Fan and Haowei Zhang and Hongyang Peng and Jing Tan and Junwen Huang and Kai Liu and Kaixin Liu and Kefan Gu and Qinglun Zhang and Ruitao Zhang and Saike Huang and Shen Cheng and Shuaicheng Liu and Tiancai Wang and Tiezhen Wang and Wei Sun and Wenbin Tang and Yajun Wei and Yang Chen and Youqiang Gui and Yucheng Zhao and Yunchao Ma and Yunfei Wei and Yunhuan Yang and Yutong Guo and Ze Chen and Zhengyuan Du and Ziheng Zhang and Ziming Liu and Ziwei Yan},
journal= {arXiv preprint arXiv:2510.17950},
year = {2025}
}
备注
Authors are listed in alphabetical order. The official website is located at https://robochallenge.ai