Convergent evolution in silico reveals shape and dynamic principles of directed locomotion on the ground

• Ano de defesa: 2022
• Autor(a) principal: Biazzi, Renata Biaggi
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Algoritmo evolutivo; Convergent evolution; Evolução convergente; Evolutionary algorithm; Morphological principles; Princípios morfológicos; Robôs maleáveis; Soft robots
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/95/95131/tde-19092022-143101/

Active, directed locomotion on the ground is present in many phylogenetically distant species. Bilateral symmetry and modularity of the body are common traits often associated with improved directed locomotion. Nevertheless, both features result from natural selection, which is contingent (history-dependent) and multifactorial (several factors interact simultaneously). Hence, it is difficult to show that bilateral symmetry and modularity of the body are necessary traits for an improved locomotion ability as they can result from chance or related to other body functions. We propose using evolutionary physical simulations of 3D voxel-based soft robots to test the necessity of both traits for efficient directed locomotion on the ground. We found that an intermediate number of body modules (appendages) and high body symmetry are evolutionarily selected regardless of gravitational environments, robot sizes, and genotype encoding. Therefore, we conclude that both traits are strong candidates for universal principles related to efficient directed locomotion.