Results 201 to 210 of about 450,271 (307)

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

Nonlocomotory Robotic Strategies for Dynamic Rotation Control in Terrestrial Robots: A Review

open access: yesAdvanced Robotics Research, EarlyView.
Terrestrial robots increasingly require rapid body rotation to maintain stability and agility in complex environments. This review shows nonlocomotory rotational control strategies that operate without ground contact, including reaction wheels, tails, bars, limbs, and thrusters.
Y. Liang   +14 more
wiley   +1 more source

Degradable Magnetic Composites from Recycled NdFeB Magnets for Soft Actuation and Sensing

open access: yesAdvanced Robotics Research, EarlyView.
This work presents a degradable soft magnetic composite made from recycled NdFeB particles embedded in a gelatin‐based organogel. The material is processed into magnetic sensors and soft robotic components, which can later be dissolved in a green solvent to recover NdFeB magnetic particles.
Muhammad Bilal Khan   +14 more
wiley   +1 more source

A Self‐Healing Permanent Magnet Putty for Soft Robot Skins With Force Sensing and Functional Recovery

open access: yesAdvanced Robotics Research, EarlyView.
Permanent magnet putty (PMP) integrates high‐coercivity NdFeB particles with a dynamic polyborosiloxane–Ecoflex matrix, achieving rapid self‐healing (90% mechanical recovery in 10 s) and magnetic recovery within 20 min. With twice the sensitivity of commercial putties, PMP enables precise 5–30 N force detection and discrimination between pressing and ...
Ruotong Zhao   +5 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

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