Fractional-order stochastic delayed neural networks with impulses: mean square finite-time contractive synchronization. [PDF]
Palanisamy G +3 more
europepmc +1 more source
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar +8 more
wiley +1 more source
The impact of virtual synchronous compensator on the transient synchronous stability of renewable energy. [PDF]
Sun F, Chen Y, Wang W.
europepmc +1 more source
Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion
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
Secure Signal Encryption in IoT and 5G/6G Networks via Bio-Inspired Optimization of Sprott Chaotic Oscillator Synchronization. [PDF]
Maamri F +7 more
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
Neuroecology and educational equity: neural regulation, interpersonal synchronization, and social development. [PDF]
Ben-Soussan TD, Lamas L, Paoletti P.
europepmc +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
A Unified AI-Driven Multimodal Framework Integrating Visual Sensing and Wearable Sensors for Robust Human Motion Monitoring in Biomedical Applications. [PDF]
Chen Q +6 more
europepmc +1 more source
Hybrid Continuum Robot Designs and Architectures for Healthcare Applications
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

