Designing higher fourier harmonics of Tegotae function using genetic algorithm—a case study with an earthworm locomotion

Abstract

‘Tegotae’ is a Japanese concept describing how well a perceived reaction matches a generated action. We previously proposed a novel decentralised control scheme for animals’ adaptive locomotion based on a Tegotae function, a function which quantifies Tegotae and is generally given by the product of action and reaction terms. Although this scheme is helpful for extracting common control principles underlying various types of animal locomotion, there remains further room for improvement of its design. Specifically, while the previous works assumed that the action term is given by a sinusoidal function, it is expected that introducing higher Fourier harmonics in the action term improves locomotion performance. In this study, taking earthworm locomotion as an example, we design a Tegotae function whose action term includes higher Fourier harmonics by using a genetic algorithm. We demonstrate via simulations that the performance improves by implementing the higher Fourier harmonics.