Evolving soft locomotion in aquatic and terrestrial environments: effects of material properties and environmental transitions
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Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Nov 2017.
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Citing papers per year: 2022: 2; 2023: 2; 2024: 1; 2025: 1; 2026: 1.
7 papers.
- 2022Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robotscited by 47
- 2023DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Modelscited by 31
- 2023Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Designcited by 5
- 2024Evolution and learning in differentiable robotscited by 5
- 2025Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challengescited by 4
- 2022Collective control of modular soft robots via embodied Spiking Neural Cellular Automatacited by 3
- 2026Evolving Embodied Intelligence: Graph Neural Network--Driven Co-Design of Morphology and Control in Soft Roboticscited by 1
- 2026Evolving Embodied Intelligence: Graph Neural Network--Driven Co-Design of Morphology and Control in Soft Robotics20 Mar 2026
- 2025Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges4 Dec 2025
- 2024Evolution and learning in differentiable robots23 May 2024
- 2023DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models28 Nov 2023
- 2023Leveraging Hyperbolic Embeddings for Coarse-to-Fine Robot Design1 Nov 2023
- 2022Collective control of modular soft robots via embodied Spiking Neural Cellular Automata5 Apr 2022
- 2022Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robots24 Jan 2022