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Simulation of Upward Jump Control for One-Legged Robot Based on QP Optimization.

Dingkui Tian1, Junyao Gao1, Chuzhao Liu1

  • 1School of Mechatronical Engineering, Intelligent Robotics Institute, Beijing Institute of Technology, Beijing 100081, China.

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Summary

This study introduces a quadratic programming (QP) optimization framework for robotic upward jumping. The method successfully generated a 16.4 cm jump while adhering to constraints like zero moment point (ZMP) and anti-slippage.

Keywords:
CoMQPZMPangular momentumanti-slippageupward jumping

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Area of Science:

  • Robotics
  • Control Systems
  • Biomechanics

Background:

  • Generating dynamic humanoid motions like jumping is challenging.
  • Existing methods struggle to simultaneously satisfy multiple complex constraints.

Purpose of the Study:

  • To develop an optimization framework for robust upward jumping motion.
  • To integrate trajectory generation and real-time control for jumping.
  • To ensure adherence to critical constraints such as ZMP and anti-slippage.

Main Methods:

  • Discretized continuous trajectories for launch phase into a nonlinear optimization problem.
  • Employed quadratic programming (QP) for real-time control during stance phase.
  • Unified control objectives (CoM, angle, angular momentum) and constraints (anti-slippage, ZMP, joint acceleration).

Main Results:

  • Achieved a successful upward jump simulation of 16.4 cm height.
  • Demonstrated full satisfaction of all imposed control objectives and constraints.
  • Validated the effectiveness of the QP-based optimization framework.

Conclusions:

  • The proposed QP optimization framework enables successful and constrained upward jumping motions.
  • The integrated approach addresses limitations in trajectory generation and real-time control.
  • This method provides a robust solution for dynamic robotic locomotion.