Evolving soft locomotion in aquatic and terrestrial environments: effects of material properties and environmental transitions

📝 Abstract

Designing soft robots poses considerable challenges: automated design approaches may be particularly appealing in this field, as they promise to optimize complex multi-material machines with very little or no human intervention. Evolutionary soft robotics is concerned with the application of optimization algorithms inspired by natural evolution in order to let soft robots (both morphologies and controllers) spontaneously evolve within physically-realistic simulated environments, figuring out how to satisfy a set of objectives defined by human designers. In this paper a powerful evolutionary system is put in place in order to perform a broad investigation on the free-form evolution of walking and swimming soft robots in different environments. Three sets of experiments are reported, tackling different aspects of the evolution of soft locomotion. The first two sets explore the effects of different material properties on the evolution of terrestrial and aquatic soft locomotion: particularly, we show how different materials lead to the evolution of different morphologies, behaviors, and energy-performance tradeoffs. It is found that within our simplified physics world stiffer robots evolve more sophisticated and effective gaits and morphologies on land, while softer ones tend to perform better in water. The third set of experiments starts investigating the effect and potential benefits of major environmental transitions (land - water) during evolution. Results provide interesting morphological exaptation phenomena, and point out a potential asymmetry between land-water and water-land transitions: while the first type of transition appears to be detrimental, the second one seems to have some beneficial effects.

💡 Analysis

Designing soft robots poses considerable challenges: automated design approaches may be particularly appealing in this field, as they promise to optimize complex multi-material machines with very little or no human intervention. Evolutionary soft robotics is concerned with the application of optimization algorithms inspired by natural evolution in order to let soft robots (both morphologies and controllers) spontaneously evolve within physically-realistic simulated environments, figuring out how to satisfy a set of objectives defined by human designers. In this paper a powerful evolutionary system is put in place in order to perform a broad investigation on the free-form evolution of walking and swimming soft robots in different environments. Three sets of experiments are reported, tackling different aspects of the evolution of soft locomotion. The first two sets explore the effects of different material properties on the evolution of terrestrial and aquatic soft locomotion: particularly, we show how different materials lead to the evolution of different morphologies, behaviors, and energy-performance tradeoffs. It is found that within our simplified physics world stiffer robots evolve more sophisticated and effective gaits and morphologies on land, while softer ones tend to perform better in water. The third set of experiments starts investigating the effect and potential benefits of major environmental transitions (land - water) during evolution. Results provide interesting morphological exaptation phenomena, and point out a potential asymmetry between land-water and water-land transitions: while the first type of transition appears to be detrimental, the second one seems to have some beneficial effects.

📄 Content

Title: “Evolving soft locomotion in aquatic and terrestrial environments: effects of material properties and environmental transitions”
Running title (~45 chars): Evolving soft locomotion
Authors names and affiliations: Francesco Corucci1,2,*, Nick Cheney2,3, Francesco Giorgio-Serchi4, Josh Bongard2 and Cecilia Laschi1 1 The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy 2 Morphology, Evolution & Cognition Lab, University of Vermont, Burlington, VT, USA 3 Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA 4 Fluid Structure Interaction Research Group, Southampton Marine and Maritime Institute, University of Southampton, Southampton, UK

• Correspondence: f.corucci@santannapisa.it Abstract (<250 words): Designing soft robots poses considerable challenges: automated design approaches may be particularly appealing in this field, as they promise to optimize complex multi-material machines with very little or no human intervention. Evolutionary soft robotics is concerned with the application of optimization algorithms inspired by natural evolution in order to let soft robots (both morphologies and controllers) spontaneously evolve within physically-realistic simulated environments, figuring out how to satisfy a set of objectives defined by human designers. In this paper a powerful evolutionary system is put in place in order to perform a broad investigation on the free-form evolution of walking and swimming soft robots in different environments. Three sets of experiments are reported, tackling different aspects of the evolution of soft locomotion. The first two sets explore the effects of different material properties on the evolution of terrestrial and aquatic soft locomotion: particularly, we show how different materials lead to the evolution of different morphologies, behaviors, and energy-performance tradeoffs. It is found that within our simplified physics world stiffer robots evolve more sophisticated and effective gaits and morphologies on land, while softer ones tend to perform better in water. The third set of experiments starts investigating the effect and potential benefits of major environmental transitions (land ↔ water) during evolution. Results provide interesting morphological exaptation phenomena, and point out a potential asymmetry between land → water and water → land transitions: while the first type of transition appears to be detrimental, the second one seems to have some beneficial effects.

1 Objective Designing soft robots [1] [2] [3] represents a considerable challenge. The design space of these machines is vast and complex, and their effective behavior often arises from complex interactions among controller, morphology, and environment, which are not trivial to foresee. This usually results in the necessity to design, fabricate, and test multiple designs, which requires time and resources. In order to alleviate this problem, effective and realistic physical simulation tools have been developed in the past years [4] [5], which allow to analyze different robot configurations before fabricating and testing them in the real world. Although transferring a design from simulation to reality is not always straightforward [6], computer simulations can provide useful information and save time and resources before attempting tests in the real world. Moreover, increasingly sophisticated techniques that allow to preserve the effectiveness of simulated design once deployed in the real world are being developed [7] [8]. In addition to leveraging simulation tools to manually design and analyze soft robots prior to their fabrication, particularly appealing is the possibility to automatize their design altogether, with algorithms capable of automatically discovering effective morphologies and controllers for a given task and environment. This is what is done in fields such as evolutionary robotics (or evo-robo) [9], where researchers develop effective ways to encode complete robot designs [10] that are then automatically optimized thanks to powerful optimization algorithms (evolutionary algorithms [11] [12]). By abstracting certain properties of natural evolution, these algorithms aim at instantiating evolutionary dynamics in computer simulations (“in silico”), hoping to automatically produce a diversity of effective and well adapted solutions that may, one day, approach the complexity and sophistication of those found in the biological world. These techniques have recently been applied in soft robotics as well: in the field of evolutionary developmental soft robotics (evo-devo-soro) [13] [14] [15] computational processes inspired by biological evolution and development are put in place in order to let soft robots grow and evolve [16] artificial brains and multi-material bodies spontaneously, within physically-realistic simulations, letting them figure out on their own how to

This content is AI-processed based on ArXiv data.