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Energy efficient walking control for biped robots using interval type-2 fuzzy logic systems and optimized iteration

Liang Yang1, Zhi Liu2, Yong Chen3

  • 1School of Computer Engineering, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, Guangdong 528402, China; School of Automation Engineering, University of Electronic Science and Technology of China, Chendu, Sichuan 611731, China.

ISA Transactions
|December 4, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces an energy-efficient walking controller for bipedal robots, using fuzzy logic systems (FLSs) and iterative mechanisms to correct Zero Moment Point (ZMP) errors and optimize joint positions for stable locomotion.

Keywords:
Biped robotEnergy efficiencyInterval type-2 fuzzy logic systemsWalking controlYaw momentZero moment point

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Area of Science:

  • Robotics
  • Control Systems
  • Artificial Intelligence

Background:

  • Bipedal robots require robust walking control to maintain stability amidst model uncertainties and external disturbances.
  • Existing controllers often struggle with Zero Moment Point (ZMP) error compensation, limiting reliable locomotion.
  • Physical constraints of actuators and inherent instability pose significant challenges in biped robot control.

Purpose of the Study:

  • To propose an energy-efficient walking control approach for bipedal robots.
  • To develop a novel controller that compensates for ZMP errors caused by uncertainties and disturbances.
  • To enhance the stability and performance of bipedal robot locomotion.

Main Methods:

  • A new walking controller integrating fuzzy logic systems (FLSs) and an iterative mechanism was designed.
  • FLSs were employed to deduce Center of Mass (CoM) corrections based on ZMP error.
  • An iterative mechanism, including an optimized control algorithm, was used to compute optimal joint positions and ensure convergence.
  • Interval type-2 FLSs were utilized to effectively handle system uncertainties.

Main Results:

  • The proposed controller demonstrated excellent performance in compensating for ZMP errors.
  • The integration of FLSs and iterative mechanisms led to effective Center of Mass (CoM) correction.
  • The optimized control algorithm within the iterative mechanism guaranteed convergence to optimal solutions, addressing actuator constraints and stabilization issues.
  • Experimental results validated the effectiveness and robustness of the proposed control scheme.

Conclusions:

  • The developed energy-efficient walking controller significantly improves the stability and performance of bipedal robots.
  • The combined fuzzy logic and iterative approach offers a robust solution for ZMP error compensation in the presence of uncertainties.
  • This research contributes a practical and effective control strategy for advanced bipedal robot locomotion.