Although recent years have seen significant progress of humanoid robots in walking and running, the frequent foot strikes with ground during these locomotion gaits inevitably generate high instantaneous impact forces, which leads to exacerbated joint wear and poor energy utilization. Roller skating, as a sport with substantial biomechanical value, can achieve fast and continuous sliding through rational utilization of body inertia, featuring minimal kinetic energy loss. Therefore, this study proposes a novel humanoid robot with each foot equipped with a row of four passive wheels for roller skating. A deep reinforcement learning control framework is also developed for the swizzle gait with the reward function design based on the intrinsic characteristics of roller skating. The learned policy is first analyzed in simulation and then deployed on the physical robot to demonstrate the smoothness and efficiency of the swizzle gait over traditional bipedal walking gait in terms of Impact Intensity and Cost of Transport during locomotion. A reduction of $75.86\%$ and $63.34\%$ of these two metrics indicate roller skating as a superior locomotion mode for enhanced energy efficiency and joint longevity.

翻译：尽管近年来人形机器人在行走与奔跑方面取得了显著进展，但这些步态中足部与地面的频繁撞击不可避免地会产生高瞬时冲击力，导致关节磨损加剧与能量利用效率低下。轮滑作为一项具有重要生物力学价值的运动，能够通过合理利用身体惯性实现快速连续的滑行，其动能损失极小。因此，本研究提出一种新型人形机器人，其每只足部配备一排四个被动轮用于轮滑运动。同时，针对轮滑八字步态开发了一套深度强化学习控制框架，其奖励函数设计基于轮滑运动的内在特性。首先在仿真环境中对学习得到的策略进行分析，随后部署至实体机器人上，通过运动过程中的冲击强度与运输成本两项指标，验证了八字步态相较于传统双足行走步态在平滑性与效率上的优势。两项指标分别降低$75.86\%$与$63.34\%$，表明轮滑是一种能够提升能量效率与延长关节寿命的优越移动模式。