Results 281 to 290 of about 5,245,598 (349)

Muscle Control of an Extra Robotic Digit

open access: yesAdvanced Robotics Research, EarlyView.
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ   +7 more
wiley   +1 more source

A Multidirectional Textile Interface for Remote Control Using Dynamic Area‐Based Capacitance Modulation

open access: yesAdvanced Robotics Research, EarlyView.
Here, we present a textile, wearable capacitive interface enabling multidirectional remote control by dynamically modulating electrode overlap and spacing via a freely gliding upper electrode. A forearm‐mounted prototype drives robotic and media tasks with 12–15 ms latency, maintains < 0.8% drift after 500 cycles, and remains stably functional at 90 ...
Cagatay Gumus   +8 more
wiley   +1 more source

Origami‐Inspired Structural Design for Aquatic‐Terrestrial Amphibious Robots

open access: yesAdvanced Robotics Research, EarlyView.
This work presents a lightweight amphibious origami robot actuated by a single shape memory alloy wire. A rigid foldable origami structure with displacement amplification enables efficient terrestrial crawling and aquatic swimming. The addition of fan‐shaped units allows controllable turning in both environments.
Weiqi Liu   +5 more
wiley   +1 more source

Molecular and neural circuit mechanisms of parvalbumin (PV) neurons in depression: Insights and advances. [PDF]

open access: yesiScience
Li ZX   +9 more
europepmc   +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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