August 7, 2025Open Access

Automated Evolutionary Gait Tuning for Humanoid Robots Using Inverse Kinematics and Genetic Algorithms

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The genetic algorithm optimizes gait parameters, improving stability and performance for humanoid robots.
Performance reached stability by generation 55 and near-optimal trade-offs by generation 100, indicating efficiency in evolution.
Hybrid approach combines screw-theory kinematics with genetic algorithms, streamlining parameterization and eliminating manual tuning.
The study indicates potential for further developments in dynamic stability by enhancing adaptability and sensor integration.

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This hybrid framework integrates inverse kinematics and a multi-objective genetic algorithm for optimized gait tuning in humanoid robots.

Chagas et al. (2025) studied this question.

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