研究16种快跑步态，发现无腾空步态适合低速，双腾空步态更节能于高速。
16 Ways to Gallop: Energetics and Body Dynamics of High-Speed Quadrupedal Gaits
- 基于飞行相数与前后腿相位关系分类步态，用轨迹优化最小化能耗。
- 无飞行相步态在低速时最省力，双飞行相步态在高速时能耗最低。
- 适用于机器人自适应步态切换设计，尤其关注能效优化场景。
奔跑是动物和四足机器人常见的高速步态，但其能量特性仍不明确。本研究基于Hildebrand的不对称步态框架，按每步中飞行相数量及前后腿相位关系，系统分析了多种可能的奔跑步态。使用Unitree的A1四足机器人，将奔跑动力学建模为混合动力系统，并通过轨迹优化（TO）在不同速度下最小化运输成本（CoT）。结果表明：旋转式与横向奔跑步态在能量上无本质差异，尽管存在身体偏航和滚动运动差异；飞行相数量显著影响能效：无飞行相步态在低速时最优，而双飞行相步态在高速时能耗最低。通过之前开发的基于二次规划（QP）的控制器，在Gazebo仿真中验证了结论。这些发现深化了对四足运动能量特性的理解，可为未来具自适应、高能效步态切换能力的腿式机器人设计提供指导。
原文摘要 · Abstract (English)
Galloping is a common high-speed gait in both animals and quadrupedal robots, yet its energetic characteristics remain insufficiently explored. This study systematically analyzes a large number of possible galloping gaits by categorizing them based on the number of flight phases per stride and the phase relationships between the front and rear legs, following Hildebrand's framework for asymmetrical gaits. Using the A1 quadrupedal robot from Unitree, we model galloping dynamics as a hybrid dynamical system and employ trajectory optimization (TO) to minimize the cost of transport (CoT) across a range of speeds. Our results reveal that rotary and transverse gallop footfall sequences exhibit no fundamental energetic difference, despite variations in body yaw and roll motion. However, the number of flight phases significantly impacts energy efficiency: galloping with no flight phases is optimal at lower speeds, whereas galloping with two flight phases minimizes energy consumption at higher speeds. We validate these findings using a quadratic programming (QP)-based controller, developed in our previous work, in Gazebo simulations. These insights advance the understanding of quadrupedal locomotion energetics and may inform future legged robot designs for adaptive, energy-efficient gait transitions.
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