Dynamic grasping system based on visual algorithm and robot arm collaboration in logistics production line. [PDF]
He B, Chen B.
europepmc +1 more source
Auto‐Routing Fluidic Printed Circuit Boards
This work introduces (STREAM) software tool for routing efficiently advanced macrofluidics, an open‐source software tool for automating the design of 3D‐printable fluidic circuit boards. STREAM streamlines tube routing and layout, enabling the rapid fabrication of fluidic networks for soft robotics, lab‐on‐a‐chip devices, microfluidics, and biohybrid ...
Savita V. Kendre +3 more
wiley +1 more source
The Effect of Telehealth on Alzheimer's Disease, Dementia and Mild Cognitive Impairment: A Systematic Review of Clinical Trials. [PDF]
Ghaddaripouri K +6 more
europepmc +1 more source
The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley +1 more source
ASAS-NANP SYMPOSIUM: MATHEMATICAL MODELING IN ANIMAL NUTRITION: quantum computing in agricultural sciences: from theory to reality. [PDF]
Tedeschi LO.
europepmc +1 more source
Hard‐Magnetic Soft Millirobots in Underactuated Systems
This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang +4 more
wiley +1 more source
QuPepFold: A python package for hybrid quantum-classical protein folding simulations with CVaR-optimized VQE. [PDF]
Uttarkar A +3 more
europepmc +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source

