arXiv subjects

Sunao Tomita

Publications and source records attributed to Sunao Tomita.

4 recordsLinked to original sources

arXiv2026

Modular fabrication and design of thick rigid-foldable origami metamaterials

Origami metamaterials offer significant potential for stiff deployable structures However, fabricating load-bearing cellular structures from thick panels introduces geometric interference at non-manifold junctions. Conventional thick-panel fabrication often disrupt ideal kinematics, thereby compromising smooth motion and scalability. This study proposes a modular fabrication framework that preserves one-degree-of-freedom rigid-folding kinematics in thick and non-manifold origami metamaterials. By decomposing non-manifold junctions into a hierarchy of stacked, modular hinged panels, our approach successfully accommodates synchronized hinge motions using scissor-like linkages. Exploiting this representation, we implement a graph-based topology optimization framework that tailors macroscopic stiffness while preserving folding connectivity. We demonstrate this approach by fabricating optimized prototypes that deploy seamlessly with a one-degree-of-freedom motion. Furthermore, we demonstrate engineering scalability through the large-scale construction of extensive deployable systems assembled from modular panels, which exhibit high load-bearing capacity. These results pave the way for the practical fabrication of structural, large-scale deployable metamaterials.

cs.CE↗

arXiv2026

Automated design of soft-rigid hybrid robots for dynamic locomotion

Rigid-bodied robots often lack compliance needed to adapt to unstructured environments, while fully soft robots, though highly adaptable, struggle with scalability and load capacity. In nature, musculoskeletal systems balance strength and flexibility by integrating hard and soft tissues. Inspired by this principle, we present an automated design method for soft-rigid hybrids that optimizes a freeform soft-body shape, a stiff truss layout, and multi-channel actuation. Our differentiable simulator couples the material point method (MPM) for deformable bodies with extended position-based dynamics (XPBD) for truss elements, enabling gradient-based search. The optimization generates truss skeletons that transmit actuation forces to the soft body. We fabricate the optimized design and evaluate it on a walking task. Experiments reproduce the walking mode predicted by the optimization, which does not emerge without the skeleton. Modal analysis further suggests that the skeleton enables deformation modes near the actuation frequency that promote effective stride generation.

cs.CE↗

arXiv2023

Stiff deployable structures via coupling of thick Miura-ori tubes along creases

Origami-based structures play an important role in the realization of deployable mechanisms and unique mechanical properties via programmable deformation by folding. Among origami-based structures, tessellation by the coupling of origami tubes enriches the variations in geometry and mechanical properties. However, thickness accommodation is a critical problem in engineering applications involving the coupling of thick origami tubes. To solve this problem, this study proposes the coupling of thick Miura-ori tubes along the creases for facile fabrication, which sustains the one-degree-of-freedom (DOF) motion of thick Miura-ori tubes owing to the local mirror symmetry around the coupling interfaces. Furthermore, the coupling method contributes to the high stiffness of the coupled Miura-ori tubes, as evidenced by the wide gap in the eigenvalues between the one-DOF mode and the elastic modes obtained by the bar-and-hinge models. Finally, meter-scale coupled Miura-ori tubes were fabricated to demonstrate one-DOF motion and high stiffness. The findings of this study enable the rapid construction of structures by one-DOF motion and enhancement of transportability via flat-foldability.

physics.app-ph↗

arXiv2023

Operational modal analysis of under-determined system based on Bayesian CP decomposition

Modal parameters such as natural frequencies, modal shapes, and the damping ratio are useful to understand structural dynamics of mechanical systems. Modal parameters need to be estimated under operational conditions for use in structural health monitoring. Therefore, operational modal analysis (OMA) without input signals has been proposed to easily extract modal parameters under operational conditions. Recently, OMA for under-determined systems with more active modes than measurement outputs has been investigated to reduce the number of sensors. This study proposes the OMA framework for under-determined systems based on Bayesian CP (CANDECOMP/PARAFAC) decomposition of second-order statistical data. The proposed method enables us to extract the modal parameters from under-determined systems without tuning the number of active modes, because the rank of the tensor data corresponding to the number of active modes is automatically determined via Bayesian inference. The effectiveness of this method is demonstrated using artificial vibration data of a mass-spring system under operational and under-determined conditions.

eess.SY↗