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Torque Curve Optimization of Ankle Push-Off in Walking Bipedal Robots Using Genetic Algorithm.

Qiaoli Ji1, Zhihui Qian1, Lei Ren1,2

  • 1Key Laboratory of Bionic Engineering, Jilin University, Changchun 130022, China.

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Summary

Biped robots can achieve faster walking speeds and improved energy efficiency through optimized ankle push-off. This study utilized a genetic algorithm to refine ankle torque, enhancing robotic locomotion.

Keywords:
ankle push-offenergy efficiencygenetic algorithmplanar biped robotpolynomial curvewalking speed

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Area of Science:

  • Robotics
  • Biomechanics
  • Control Systems

Background:

  • Ankle push-off, a key mechanism in human walking, involves generating positive power at the ankle to propel the body forward.
  • This ankle power burst is crucial for leg swing and accelerating the center of mass (CoM), enabling changes in walking speed.
  • Understanding and replicating ankle push-off in biped robots can significantly enhance their locomotion capabilities.

Purpose of the Study:

  • To determine the optimal ankle push-off strategy for achieving faster walking speeds in biped robots.
  • To identify the ankle torque profile that minimizes the mechanical cost of transport (MCOT) for energy-efficient bipedal walking.
  • To investigate the implications of ankle push-off on biped robot design and performance.

Main Methods:

  • A real-time-space trajectory method was employed to define hip and knee joint reference positions.
  • A novel ankle torque curve, comprising three quintic polynomial curves, was applied to the ankle joint.
  • A genetic algorithm (GA) was used to optimize the ankle torque curve, targeting maximum walking distance and minimum MCOT.

Main Results:

  • The optimized biped robot achieved a maximum walking speed of 1.3 m/s.
  • Ankle push-off was observed to occur between 41.27% and 48.34% of the gait cycle.
  • A highly energy-efficient gait was achieved with an MCOT of 0.70 at a walking speed of 0.54 m/s.

Conclusions:

  • Optimizing ankle push-off is critical for enhancing both speed and energy efficiency in biped robots.
  • The study demonstrates the effectiveness of using genetic algorithms to determine optimal ankle torque profiles.
  • Findings provide valuable insights for the future design of biped robot ankle joints and locomotion systems.