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February 11, 2026Nature Communications2 citationsOpen Access

Robotic leaping enhanced by thrust-induced hypogravity, achieving precise, predictable, and extended jumps

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ZSZijie SunJZJianguo ZhaoYLYangmin LI

Key Points

  • To enhance robotic jumping capabilities focusing on range, precision, and predictability in unstructured environments.
  • Developed a bipedal robot using thrust-induced hypogravity.
  • Implemented thrust vectoring for regulation of aerial attitude and parabolic trajectory.
  • Tested performance clearing multi-level obstacles and navigating dynamic targets.
  • Achieved maximum leap range of 6.9 m despite leg force saturation.
  • Demonstrated precision and consistency in jump distance exceeding existing hybrid designs.
  • Enabled effective jumping through fast-moving openings and onto shifting targets.

Abstract

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.

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Cite This Study

Sun et al. (2026) studied this question.

synapsesocial.com/papers/698be001058ab1890a13b993https://doi.org/10.1038/s41467-026-68932-0
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