Results 151 to 160 of about 10,223 (211)

Hard‐Magnetic Soft Millirobots in Underactuated Systems

open access: yesAdvanced Robotics Research, EarlyView.
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang   +4 more
wiley   +1 more source

Interventions for convergence insufficiency: a network meta-analysis. [PDF]

open access: yesCochrane Database Syst Rev, 2020
Scheiman M   +5 more
europepmc   +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

A Soft Robotic Fish With a Dielectric Elastomer Actuator Body and Negative Stiffness Spine

open access: yesAdvanced Robotics Research, EarlyView.
This work introduces a bio‐mimetic soft robotic fish driven by fiber‐reinforced dielectric elastomer actuators integrated as its body. By prestretching this active skin against a flexible spine, a negative stiffness system is created, enabling large‐amplitude bending.
Markus Koenigsdorff   +4 more
wiley   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

open access: yesAdvanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao   +4 more
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

Home - About - Disclaimer - Privacy