CORTEXA
← Browse
openalexAdvanced Science2026-07-24Cited by 0

From Folding Mechanics to Robotic Function: A Unified Modeling Framework for Compliant Origami

B Zhang, Bo Wang, Huajiang Ouyang, Zhigang Wu, Haohao Bi, Jiawei Xu, Mingchao Liu, Weicheng Huang

Origami-inspired architectures offer a powerful route toward lightweight, reconfigurable, and programmable robotic systems. Yet, a unified mechanics framework capable of seamlessly bridging rigid folding, elastic deformation, and stability-driven transitions in compliant origami remains lacking. Here, we introduce a geometry-consistent modeling framework based on discrete differential geometry (DDG) that unifies panel elasticity and crease rotation within a single variational formulation. By embedding crease-panel coupling directly into a mid-edge geometric discretization, the framework naturally captures rigid-folding limits, distributed bending, multistability, and nonlinear dynamic snap-through within one mechanically consistent structure. This unified description enables programmable control of stability and deformation across rigid and compliant regimes, allowing origami structures to transition from static folding mechanisms to active robotic modules. An implicit dynamic formulation incorporating gravity, contact, friction, and magnetic actuation further supports strongly coupled multiphysics simulations. Through representative examples spanning single-fold bifurcation, deployable Miura membranes, bistable Waterbomb modules, and Kresling-based crawling robots, we demonstrate how geometry-driven mechanics directly informs robotic functionality. This work establishes discrete differential geometry as a foundational design language for intelligent origami robotics, enabling predictive modeling, stability programming, and mechanics-guided robotic actuation within a unified computational platform.

View free PDFSource page

Related papers

openalexAdvanced Science2026-07-24

Bioinspired Ionochromic Neuromorphic Transistors for Robotic Intelligent Perception

Quanxing Yao, Xiaojian Zhu, Runsheng Gao, Qian Jiang, Cui Sun, Du Y, et al.

Intelligent perception with closed-loop information acquisition, processing, and feedback is critical for humanoid robots and embodied intelligence systems. Ionochromic transistors hold great potential for on-site signal processing and visual feedback. Here, we report a bioinspir…

View free PDFSource page
openalexAdvanced Science2026-07-23

Systematic Position Mapping of Split CRISPR‐Cas12a Activators Enables Highly Sensitive miRNA Detection and Cancer Cell Stratification

Xiaoyan Tang, Zhe Li, Yuning Lu, Ma My, Zijian Mo, Jiajun Ke, et al.

Amplification-free Cas12a diagnostics with split crRNA enable rapid and programmable target recognition, yet insufficient understanding of DNA activator architecture prevents predictable control over trans-cleavage activity and sensitivity. Here we systematically map over 200 spl…

View free PDFSource page
openalexAdvanced Science2026-07-23

DDSurfer: A Weakly‐Supervised Dual‐Stream Deep Learning Framework for Cortical Surface Reconstruction From Diffusion MRI

C L Li, Wei Zhang, Xi Zhu, Yuehua Chen, Nir A. Sochen, Jarrett Rushmore, et al.

Cortical surface reconstruction of white matter and pial surfaces from diffusion MRI (dMRI) is critical for neuroimaging analyses, including tractography, connectomics, and multimodal data integration. However, obtaining these surfaces from dMRI data is inherently challenged by i…

View free PDFSource page
openalexAdvanced Science2026-07-23

Deep Learning Prediction of <i>O</i> ‐Glycopeptide Tandem Mass Spectra Enhances <i>O</i> ‐Glycoproteomics

Yu Zong, Yuxin Wang, Liang Qiao

Protein glycosylation, a post-translational modification involving the attachment of glycans to proteins, plays critical roles in numerous physiological and pathological cellular functions. Characterization of protein glycosylation is one of the most challenging problems due to t…

View free PDFSource page
crossrefAdvanced Science2026-07-20

Machine Learning–Guided Surface Strain Engineering in Connected Platinum–Nickel Nanoparticle Catalysts for Advanced Oxygen Reduction Performance

Aparna Chitra Sudheer, Gopinathan M. Anilkumar, Hidenori Kuroki, Yuuki Sugawara, Takeo Yamaguchi

ABSTRACT Engineering the surface structure of catalysts is critical for achieving high intrinsic activity in the oxygen reduction reaction (ORR). We report a machine‐learning (ML)‐guided materials design strategy for the synthesis of support‐free, connected nanoparticle catalysts…

View free PDFSource page
crossrefAdvanced Science2026-06-30

Deep Learning Network‐Tailored Microenvironment Matching of 4D Bioprinting Bioactive Scaffolds for Bone Regeneration

Xiongjie Liang, Yuechi Zhang, Weifeng Hu, Shiyan Lv, Fan Jia, Yan Zhang, et al.

ABSTRACT Pathological microenvironments linked to aging, trauma, malignancies, and metabolic disorders significantly hinder bone fractures and frequently result in fracture nonunion, posing substantial worldwide clinical difficulties. Widely prevalent therapies encounter difficul…

View free PDFSource page