arXiv 2604.213552026-07-01cs.RO

RPG: 为人类oid战斗中平滑多技能过渡的鲁棒策略门控

RPG: Robust Policy Gating for Smooth Multi-Skill Transitions in Humanoid Fighting

Center for Artificial Intelligence and Robotics, Shenzhen International Graduate School, Tsinghua University（人工智能与机器人中心，深圳国际研究生院，清华大学）；Shanghai AI Laboratory（上海人工智能实验室）；Northwestern Polytechnical University（西北工业大学）；Shanghai Jiao Tong University（上海交通大学）

Yucheng Xin, Jiacheng Bao, Yubo Dong, Xueqian Wang, Bin Zhao, Xuelong Li, Junbo Tan, Dong Wang

阅读 PDF

arXiv 页面 ↗HTML 原文 ↗

AI总结：

本文提出RPG框架，通过动作过渡随机化和时间随机化训练统一策略，实现人类oid多技能平滑稳定过渡，并设计控制管道整合步行/跑步与战斗技能，实验证明其有效性与鲁棒性。

摘要：

人类oid机器人在广泛任务中展示了出色的运动技能，但人形长时间动态战斗的全身控制尤为困难，因要求敏捷性和稳定性严格。尽管模仿学习使机器人能执行人类战斗技能，但现有方法常依赖多个单技能策略切换或使用通用策略模仿输入参考动作。这些策略在技能过渡时不稳定，因技能或参考动作初始与终端状态不匹配导致域外干扰，产生不平滑或不稳定行为。本文提出RPG，一种混合专家策略框架，用于平滑稳定的多技能过渡。我们的方法结合动作过渡随机化和时间随机化，训练统一策略生成敏捷战斗动作，在技能过渡时具有稳定性和平滑性。此外，我们设计了整合步行/跑步运动与战斗技能的控制管道，允许人类样长时间任意持续时间的战斗，可无缝中断或过渡动作策略。大量模拟实验验证了所提框架的有效性，实际部署在Unitree G1人形机器人上进一步验证了其鲁棒性和适用性。

英文摘要：

Humanoid robots have demonstrated impressive motor skills in a wide range of tasks, yet whole-body control for humanlike long-time, dynamic fighting remains particularly challenging due to the stringent requirements on agility and stability. While imitation learning enables robots to execute human-like fighting skills, existing approaches often rely on switching among multiple single-skill policies or employing a general policy to imitate input reference motions. These strategies suffer from instability when transitioning between skills, as the mismatch of initial and terminal states across skills or reference motions introduces out-of-domain disturbances, resulting in unsmooth or unstable behaviors. In this work, we propose RPG, a hybrid expert policy framework, for smooth and stable humanoid multi-skills transition. Our approach incorporates motion transition randomization and temporal randomization to train a unified policy that generates agile fighting actions with stability and smoothness during skill transitions. Furthermore, we design a control pipeline that integrates walking/running locomotion with fighting skills, allowing humanlike long-time combat of arbitrary duration that can be seamlessly interrupted or transit action policies at any time. Extensive experiments in simulation demonstrate the effectiveness of the proposed framework, and real-world deployment on the Unitree G1 humanoid robot further validates its robustness and applicability.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。