Results 191 to 200 of about 10,426 (266)

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

open access: yesAdvanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu   +5 more
wiley   +1 more source

Backpropagation Through Soft Body: Investigating Information Processing in Brain–Body Coupling Systems

open access: yesAdvanced Robotics Research, EarlyView.
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka   +3 more
wiley   +1 more source

Optimizing carrier collection in solar cells through nanoscale junction design.

open access: yesEnergy Adv
Micali M   +4 more
europepmc   +1 more source

A Soft Robotic Device for Targeted Massage Therapy of Residual Limbs

open access: yesAdvanced Robotics Research, EarlyView.
Residual limb edema after amputation can hinder recovery and delay prosthetic fitting. This study presents a soft‐robotic wearable device that delivers sequential compression through pneumatic McKibben actuators. By replicating the principles of manual lymphatic drainage, the device generates controlled mechanotherapeutic pressure patterns, providing a
Maria Grazia Polizzotto   +5 more
wiley   +1 more source

Anti-interference diffractive deep neural networks for multi-object recognition. [PDF]

open access: yesLight Sci Appl
Huang Z   +13 more
europepmc   +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

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