Results 221 to 230 of about 1,199,322 (345)

Universal Gripper for Industrial Manipulation With Enhanced Rigid Mechanics and Self‐Adaptable Fingers

Advanced Robotics Research, EarlyView.
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, Nirmal Kumar Ravikumar, Mattia Frascio, Sumanth Nagalakunta, Alessandro Seitone, Benoît Lévesque, Alessandro Zanella, Matteo Zoppi   +7 more
wiley   +1 more source

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

Advanced 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, Fulya Yenilmez, Kadir Ozlem, Hakan Kestir, Eren Tasdemir, Berkant Bakisli, Gökhan Ince, Ozgur Atalay, Asli Tuncay Atalay   +8 more
wiley   +1 more source

Durability of Soft Pneumatic Actuators: A Review and Benchmarking Protocol

Advanced Robotics Research, EarlyView.
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, Yucheng Luo, Rob Bernardus Nicolaas Scharff   +2 more
wiley   +1 more source

A deep learning-based automated Solar-Powered Fish Monitoring System. [PDF]

PLoS One
Ahene E, Agyei RO, Gyening ROM, Obirikorang KA, Takyi K, Owusu-Agyemang K, Amoako-Banning L, Walker J.   +7 more
europepmc   +1 more source

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

Advanced 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, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

Intelligent soft robotic gripper for non-destructive grasping and attribute recognition via multi-modal waveguide tactile sensors. [PDF]

Microsyst Nanoeng
Fan Y, Zhang C, Ying Y, An Z, Guo Q, Li D, Zhang L.   +6 more
europepmc   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
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, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

A Hybrid Qualitative-Quantitative FMEA Model for Risk Management in Clinical Laboratory Automation: A Case Study Integrating ISO 15189:2022. [PDF]

J Clin Lab Anal
Wei M, Li M, Lin Y, Li B, Xue H, Xia Y.
europepmc   +1 more source

Data‐Driven Bulldozer Blade Control for Autonomous Terrain Leveling

Advanced 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, Ganesh Arivoli, Huzaifa Unjhawala, Luning Bakke, Radu Serban, Dan Negrut   +5 more
wiley   +1 more source