Robotic jumping research advances engineering and biomimicry frontiers, prioritizing range, precision, and predictability to navigate unstructured environments. Earth’s gravity necessitates powerful actuators and lightweight bodies in robotic designs for maximal jump height. While many robots excel in statical environments, precise, predictable jumps in dynamic settings remain challenging. We realized this with a bipedal robot leveraging thrust-induced hypogravity, alongside dual regulation of aerial attitude and parabolic trajectory via thrust vectoring. Hypogravity multiplies leap range (max: 6.9 m) despite leg force saturation, enabling the robot to clear multi-level stairs, a 2.35-m-high wall, and 3-m-wide stream. Parabolic trajectory regulation allows leap distance precision/consistency surpassing existing thrust-assisted hybrids and leg-only jumpers. It enables pre-jump prediction of aerial/landing positions and timing, facilitating leaps in dynamic scenarios: through fast-moving windows (3.8 m/s), onto shifting, confined targets, and against wind disturbance. This research establishes extended range, precise, and predictable jumping through self-generated hypogravity and parabolic trajectory regulation.
Sun et al. (Mon,) studied this question.