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Pressure optimization for hydraulic-electric hybrid biped robot power unit based on genetic algorithm.

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This study introduces an electric-hydraulic hybrid drive system for biped robots, enhancing performance by optimizing hydraulic energy consumption. The novel approach improves efficiency by 3.49% through advanced control strategies.

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Area of Science:

  • Robotics
  • Mechanical Engineering
  • Control Systems

Background:

  • Biped robots offer flexible movement and adaptability but face limitations in current drive systems, including low torque, weak impact resistance in motor drives, and high energy consumption in hydraulic drives.
  • These limitations hinder the overall performance and efficiency of biped robot locomotion.
  • Addressing these challenges is crucial for advancing biped robot technology.

Purpose of the Study:

  • To propose and evaluate an electric-hydraulic hybrid drive system for biped robots.
  • To analyze the dynamic characteristics and load forces during walking in a biped robot.
  • To minimize energy consumption in the hydraulic drive system through optimization.

Main Methods:

  • A biped robot platform was designed based on the Zhejiang Lab prototype.
  • Models of the hydraulic drive system and mechanical structure were established for dynamic analysis.
  • A value function was developed to quantify hydraulic drive system energy consumption.
  • The genetic algorithm was employed to optimize control parameters, specifically accumulator pressure, to minimize the value function.

Main Results:

  • Dynamic characteristics and load forces during walking were analyzed.
  • An optimization algorithm was developed to reduce hydraulic energy consumption.
  • Simulation results demonstrated a 3.49% improvement in efficiency for the proposed hybrid drive system.

Conclusions:

  • The electric-hydraulic hybrid drive system effectively addresses the performance limitations of traditional biped robot drive systems.
  • Optimizing hydraulic system parameters, such as accumulator pressure, significantly reduces energy consumption.
  • The proposed optimization strategy offers a viable method for enhancing the efficiency of biped robots.