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Fold Walker: An Origami‐Inspired Quadruped Robot for Multipattern Locomotion and Object Grasping

open access: yesAdvanced Robotics Research, EarlyView.
This article presents Fold Walker, an origami‐inspired quadruped robot capable of multipattern locomotion and object grasping. With each leg featuring two rotational folds, the robot can transform from a flat 2D configuration into complex 3D poses. Furthermore, its trunk and legs can be one‐shot 3D printed as a unified structure, greatly simplifying ...
Yilun Sun
wiley   +1 more source

Magnetic Field Driven Microrobot Based on Hydrogels

open access: yesAdvanced Robotics Research, EarlyView.
Hydrogel‐based magnetic microrobots synergize remote magnetic control with the biocompatibility of flexible hydrogels, emerging as promising tools for minimally invasive biomedicine. This enables remotely controllable, untethered navigation within complex biological microenvironments.
Juncai Song, Yubing Guo
wiley   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

open access: yesAdvanced Robotics Research, EarlyView.
A simulation‐driven framework for autonomous bulldozer leveling is presented, combining high‐fidelity terramechanics simulation with a neural‐network‐based reduced‐order model. Gradient‐based optimization enables efficient, low‐level blade control that balances leveling quality and operation time.
Harry Zhang   +5 more
wiley   +1 more source

Photoelectrochemical Hydrogen Production Using TiO2/Mn‐CdS Photoanode with ZnS Passivation and CoPi as Hole Transfer Relay

open access: yesAdvanced Sustainable Systems, EarlyView.
The electrode features TiO2 as a stable UV‐absorbing substrate, Mn‐doped CdS to extend light absorption into the visible range, ZnS to prevent CdS photocorrosion, and an outer cobalt phosphate (CoPi) that catalyzes oxygen evolution, efficiently enhancing hole transfer from the photoanode to the electrolyte.
Hwapyong Kim   +4 more
wiley   +1 more source

Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects

open access: yesAdvanced Science, EarlyView.
The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su   +14 more
wiley   +1 more source

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