Liquid Crystalline Elastomers in Soft Robotics: Assessing Promise and Limitations
Liquid crystalline elastomers (LCEs) are programmable soft materials that undergo large, anisotropic deformation in response to external stimuli. Their molecular alignment encodes directional actuation in a monolithic structure, making them long‐standing candidates for soft robotic systems.
Justin M. Speregen, Timothy J. White
wiley +1 more source
Structure-aware Multi-task Collaborative Learning: a multi-task collaborative learning framework for peptide-protein interaction prediction based on structure-aware protein language models. [PDF]
He S +5 more
europepmc +1 more source
An enhanced universal gripper combining rigid mechanics with self‐adaptable fingers is presented for industrial automation. The novel six‐bar linkage with integrated compliant pad eliminates mechanical interference while enabling passive shape adaptation.
Muhammad Usman Khalid +7 more
wiley +1 more source
Human-Machine Collaborative Learning for Streaming Data-Driven Scenarios. [PDF]
Yang F, Zhang X, Yu Z.
europepmc +1 more source
Muscle Control of an Extra Robotic Digit
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
Integrating microsurgical reconstruction in head and neck oncology: a collaborative learning curve experience. [PDF]
Oprescu AE.
europepmc +1 more source
Durability of Soft Pneumatic Actuators: A Review and Benchmarking Protocol
Lack of durability is a key challenge hindering the broad scale adoption of soft pneumatic actuators (SPAs) in automation industries. This review provides a comprehensive overview of existing research on SPA durability, introduces a standardized durability benchmarking protocol to consolidate the testing of SPAs, and outlines promising directions for ...
Dickson Chiu Yu Wong +2 more
wiley +1 more source
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
Artificial intelligence integrated WeChat social media adoption for collaborative learning engagement among university students. [PDF]
Mensah IK, Khan MK.
europepmc +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki +2 more
wiley +1 more source

