Some distance measures for morphological diversification in generative evolutionary robotics

Abstract

Evolutionary robotics often involves optimization in large, complex search spaces, requiring good population diversity. Recently, measures to actively increase diversity or novelty have been employed in order to get sufficient exploration of the search space either as the sole optimization objective or in combination with some performance measurement. When evolving morphology in addition to the control system, it can be difficult to construct a measure that sufficiently captures the qualitative differences between individuals. In this paper we investigate four diversity measures, applied in a set of evolutionary robotics experiments using an indirect encoding for evolving robot morphology. In the experiments we optimize forward locomotion capabilities of symmetrical legged robots in a physics simulation.