Generating dynamic jumping motions on legged robots remains a challenging control problem as the full flight phase and large landing impact are expected. Compared to quadrupedal robots or other multi-legged robots, bipedal robots place higher requirements for the control strategy given a much smaller footprint. To solve this problem, a novel heuristic landing planner is proposed in this paper. With the momentum feedback during the flight phase, landing locations can be updated to minimize the influence of uncertainties from tracking errors or external disturbances when landing. To the best of our knowledge, this is the first approach to take advantage of the flight phase to reduce the impact of the jump landing which is implemented in the actual robot. By integrating it with a modified kino-dynamics motion planner with centroidal momentum and a low-level controller which explores the whole-body dynamics to hierarchically handle multiple tasks, a complete and versatile jumping control framework is designed in this paper. Extensive results of simulation and hardware jumping experiments on a miniature bipedal robot with proprioceptive actuation are provided to demonstrate that the proposed framework is able to achieve human-like efficient and robust jumping tasks, including directional jump, twisting jump, step jump, and somersaults.

翻译：在足式机器人上生成动态跳跃运动仍是一项具有挑战性的控制问题，因为这涉及完整的腾空阶段和巨大的落地冲击。与四足机器人或其他多足机器人相比，双足机器人由于占地面积更小，对控制策略提出了更高要求。为解决这一问题，本文提出了一种新颖的启发式落地规划器。通过利用腾空阶段的动量反馈，可实时更新落地位置，以最小化跟踪误差或外部干扰等不确定性对落地的影响。据我们所知，这是首次在实际机器人上利用腾空阶段减少跳跃落地冲击的方法。通过将该规划器与改进的基于质心动量的运动学-动力学运动规划器以及利用全身动力学分层处理多项任务的底层控制器相结合，本文设计了一个完整且通用的跳跃控制框架。通过在具有本体感知驱动的微型双足机器人上进行的仿真和硬件跳跃实验的广泛结果，证明了该框架能够实现类人高效且鲁棒的跳跃任务，包括定向跳、扭身跳、台阶跳和空翻。