Generation of an Optimal Gait Trajectory for Biped Robots Using a Genetic Algorithm

This paper proposes a method that minimizes the energy consumption in the locomotion of a biped robot. A real-coded genetic algorithm is employed in order to search for the optimal locomotion pattern, and at the same time the optimal locations of the mass centers of the links that compose the biped robot. Since many of the essential characteristics of the human walking motion can be captured with a seven-link planar biped walking in the saggital plane, a 6-DOF biped robot that consists of seven links is used as the model used in the work. For trajectories of the robot in a single stride, fourth-order polynomials are used as their basis functions to approximate the locomotion gait. The coefficients of the polynomials are defined as design variables. For the optimal locations of the mass centers of the links, three variables are added to the design variables under the assumption that the left and right legs are identical. Simulations were performed to compare locomotion trajectories obtained with the genetic algorithm and the one obtained with the gravity-compensated inverted pendulum mode (GCIPM). They show that the proposed trajectory with the optimized mass centers significantly reduces the energy consumption, indicating that the proposed optimized method is a valuable tool in the design of biped robots.

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