Comparison between Three Approaches for Solving Biped Robot Walking Problem Based on Truncated Fourier Series


Controlling a biped robot with a high degree of freedom to achieve stable, straight and fast movement patterns is one of the most complex problems. With growing computational power of computer hardware, simulation of such robots in high resolution real time environment has become more applicable. In this paper for first time we compare three approaches with together for solving the biped robot walking problem. In this scene, first we have used a modified Truncated Fourier Series (TFS) to generate angular trajectories, then to find the best angular trajectory we used three approaches. 1. Genetic Algorithm(GA) 2. Genetic Algorithm parameters adaption using Learning Automata(GALA) 3. Particle Swarm Optimization(PSO) algorithm. Evaluations performed on Simulated NAO robot in RoboCup 3D soccer simulation environment.

  • Abstract
  • Key Words
  • 1. Introduction
  • 2. TFS Gait Generator
  • 3. Exprimental Result
  • 4. Summaries
  • References

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