Decreasing the Cost of Morphing in Adaptive Morphogenetic Robots

Recent advances in locomoting robotics have demonstrated how shape morphing can enhance efficiency, mobility, and speed during transitions between domains, such as from land to water. However, prior approaches often optimize a robot's propulsor shape, stiffness, and gait to minimize the cost of transport in distinct domains while neglecting the energy required to achieve these shape and stiffness changes at domain interfaces. Additionally, many shape‐morphing robots rely on thermally driven materials that couple shape and stiffness changes to environmental temperatures, limiting their applicability in real‐world multidomain scenarios. This work introduces the Jamming Amphibious Robotic Turtle (JART), which employs pressure‐responsive, topologically altered kirigami laminar jamming to transform its limbs between hydrodynamic flippers and load‐bearing legs. Energetic analyses reveal that JART achieves a 98.5% reduction in the energetic cost of morphing compared to thermally driven predecessors. Its pressure‐responsive morphing mechanism also enables temperature‐independent energy expenditures when morphing, rapid stiffness switching, decoupled control of stiffness and shape, and robust postloading shape recovery. System‐level evaluations highlight JART's ability to efficiently transition between domains, demonstrated through a continuous terrestrial–aquatic–terrestrial transition at an ocean inlet. This study provides valuable insights into the design of deployable, multidomain robots, advancing their potential for real‐world applications.

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Institutions

Publication Details

Journal
Advanced Intelligent Systems
Published
2025-04-15
DOI
https://doi.org/10.1002/aisy.202401055
Citations
1
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.71

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article

Decreasing the Cost of Morphing in Adaptive Morphogenetic Robots

Rebecca Kramer‐Bottiglio, Bilige Yang, Robert Baines, Luis A. Ramirez
1 citations
Advanced Intelligent Systems
Modular Robots and Swarm Intelligence
0.71
article

Decreasing the Cost of Morphing in Adaptive Morphogenetic Robots

Rebecca Kramer‐Bottiglio, Bilige Yang, Robert Baines, Luis A. Ramirez
article en
1 citations

Abstract

Recent advances in locomoting robotics have demonstrated how shape morphing can enhance efficiency, mobility, and speed during transitions between domains, such as from land to water. However, prior approaches often optimize a robot's propulsor shape, stiffness, and gait to minimize the cost of transport in distinct domains while neglecting the energy required to achieve these shape and stiffness changes at domain interfaces. Additionally, many shape‐morphing robots rely on thermally driven materials that couple shape and stiffness changes to environmental temperatures, limiting their applicability in real‐world multidomain scenarios. This work introduces the Jamming Amphibious Robotic Turtle (JART), which employs pressure‐responsive, topologically altered kirigami laminar jamming to transform its limbs between hydrodynamic flippers and load‐bearing legs. Energetic analyses reveal that JART achieves a 98.5% reduction in the energetic cost of morphing compared to thermally driven predecessors. Its pressure‐responsive morphing mechanism also enables temperature‐independent energy expenditures when morphing, rapid stiffness switching, decoupled control of stiffness and shape, and robust postloading shape recovery. System‐level evaluations highlight JART's ability to efficiently transition between domains, demonstrated through a continuous terrestrial–aquatic–terrestrial transition at an ocean inlet. This study provides valuable insights into the design of deployable, multidomain robots, advancing their potential for real‐world applications.

Advanced Intelligent SystemsVol. 7(9)
Yale University (US)
National Science Foundation, Eidgenössische Technische Hochschule Zürich, Office of Naval Research, Office of Naval Research Global
Openalex Percentile: Top 34%
Modular Robots and Swarm Intelligence
0.71
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