Digital twins-based remote semi-physical commissioning of flow-type smart manufacturing systems. [PDF]
J Clean Prod, 2021 Leng J +7 more
europepmc +1 more source
Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion
Advanced Robotics Research, EarlyView.A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza +3 more
wiley +1 more source
A Multimodal Large Language Model Framework for Intelligent Perception and Decision-Making in Smart Manufacturing. [PDF]
Sensors (Basel)Wang T, Zhang B, Jiang D, Li D.
europepmc +1 more source
An Experimental Safety Response Mechanism for an Autonomous Moving Robot in a Smart Manufacturing Environment Using Q-Learning Algorithm and Speech Recognition. [PDF]
Sensors (Basel), 2022 Kiangala KS, Wang Z.
europepmc +1 more source
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 +8 more
wiley +1 more source
Recipe Based Anomaly Detection with Adaptable Learning: Implications on Sustainable Smart Manufacturing. [PDF]
Sensors (Basel)Lee J, Jang J, Tang Q, Jung H.
europepmc +1 more source
Standard Connections for IIoT Empowered Smart Manufacturing. [PDF]
Manuf Lett, 2020 Lu Y, Witherell P, Jones A.
europepmc +1 more source
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 +4 more
wiley +1 more source
Virtual, Augmented, and Mixed Reality Robotics-Assisted Deep Reinforcement Learning Towards Smart Manufacturing. [PDF]
Sensors (Basel)Le T, Vinh LQ, Pham VH.
europepmc +1 more source
Hybrid Continuum Robot Designs and Architectures for Healthcare Applications
Advanced Robotics Research, EarlyView.Hybrid continuum robots represent an emerging class of flexible manipulators that blend materials, structures, and actuation concepts from the established fields of soft and continuum robotics. This review introduces an accessible framework to distinguish key hybridization approaches, surveys current designs aimed at complex clinical applications, and ...
Burak Ozdemir +4 more
wiley +1 more source