Abstract. This paper presents a new approach to optimize gait parameter sets using evolutionary algorithms. It separates the crossover-step of the evolutionary algorithm into an interpolating step and an extrapolating step, which allows for solving optimization problems with a small population, which is an essential for robotics applications. In contrast to other approaches, odometry is used to assess the quality of a gait. Thereby, omni-directional gaits can be evolved. Some experiments with the Sony Aibo models ERS-210 and ERS-7 prove the performance of the approach including the fastest gait found so far for the Aibo ERS-210.
A genetic algorithm that used interpolation and extrapolation for the crossover step was used to optimize a parameterized gait with a half-elliptical locus REF .
Evolutionary Gait-Optimization Using a Fitness Function Based on Proprioception
RobuCup
Computer Science