This study explores the dynamics of asymmetrical bounding gaits in quadrupedal robots, focusing on the integration of torso pitching and hip motion to enhance speed and stability. Traditional control strategies often enforce a fixed posture, minimizing natural body movements to simplify the control problem. However, this approach may overlook the inherent dynamical advantages found in natural locomotion. By considering the robot as two interconnected segments, we concentrate on stance leg motion while allowing passive torso oscillation, drawing inspiration from natural dynamics and underactuated robotics principles. Our control scheme employs Linear Inverted Pendulum (LIP) and Spring-Loaded Inverted Pendulum (SLIP) models to govern front and rear leg movements independently. This approach has been validated through extensive simulations and hardware experiments, demonstrating successful high-speed locomotion with top speeds nearing 4 m/s and reduced ground reaction forces, indicating a more efficient gait. Furthermore, unlike conventional methods, our strategy leverages natural torso oscillations to aid leg circulation and stride length, aligning robot dynamics more closely with biological counterparts. Our findings suggest that embracing the natural dynamics of quadrupedal movement, particularly in asymmetrical gaits like bounding, can lead to more stable, efficient, and high-speed robotic locomotion. This investigation lays the groundwork for future studies on versatile and dynamic quadrupedal gaits and their potential applications in scenarios demanding rapid and effective locomotion.

翻译：本研究探讨了四足机器人非对称跳跃步态的动力学特性，重点关注通过整合躯干俯仰与髋部运动来提升速度与稳定性。传统控制策略通常强制保持固定姿态，通过最小化自然身体运动来简化控制问题。然而，这种方法可能忽略了自然运动中所固有的动力学优势。通过将机器人视为两个相互连接的节段，我们专注于支撑腿的运动，同时允许躯干被动振荡，其灵感来源于自然动力学原理及欠驱动机器人学理论。我们的控制方案采用线性倒立摆（LIP）和弹簧负载倒立摆（SLIP）模型来分别控制前腿和后腿的运动。该方法已通过大量仿真和硬件实验得到验证，成功实现了高速运动，最高速度接近4米/秒，并降低了地面反作用力，表明步态效率更高。此外，与传统方法不同，我们的策略利用自然的躯干振荡来辅助腿部循环和步幅，使机器人动力学更接近生物运动特性。我们的研究结果表明，接纳四足运动的自然动力学特性，特别是在跳跃等非对称步态中，可以实现更稳定、高效和高速的机器人运动。此项研究为未来研究多功能、动态的四足步态及其在需要快速有效运动场景中的潜在应用奠定了基础。