Gait Optimization in AIBO Robots Using an Estimation of Distribution Algorithm

Abstract

In this paper we deal with the problem of automatically optimizing the gait of a robot for forward walking speed. Each different walking surface and/or the wear and tear of the robots determines the speed of the robot. This means that a specific gait for one surface may not be valid on another surface or even on the same surface some time later. Given a parametrized walk designed for the robot and one specific robot, we approach the problem of searching over the space of gaits for this robot by using an estimation of distribution algorithm and our knowledge of the problem, which allows us to considerably reduce the space of gaits over which the algorithm searches. We have implemented and tested our method using the Sony AIBO ERS-7 robot, significantly improving on our previous gait in a short period of training time.

A Review of Gait Optimization Based on Evolutionary Computation

“…For example, EDA has been applied to optimize the gait of the AIBO robot. A fitness function based on direct evaluation of the robots was adopted, and significant improvement of the previous gait was achieved over a short training period [41].…”