Multi‐Material Additive Manufacturing of Soft Robotic Systems: A Comprehensive Review
This review explores the transformative role of multi‐material additive manufacturing (MMAM) in the development of soft robotic systems. It presents current techniques, materials, and design strategies that enable functionally graded and adaptive structures.
Ritik Raj +2 more
wiley +1 more source
Predictive modeling of coagulant dosing in drilling wastewater treatment using artificial neural networks. [PDF]
Kalhormohammadi M, Khoramipour S.
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
Different artificial neural networks for predicting burnout risk in Italian anesthesiologists. [PDF]
Cascella M +10 more
europepmc +1 more source
Amphiphilic chloroazobenzenes, bearing different amino acids as end groups alanine, phenylalanine, and valine, exhibit excellent photoisomerizations. Varying structures of three amino acid groups participate in supramolecular formations and therefore photoinduced morphological transformations via adjusting intermolecular interactions. These interaction
Shuangshuang Meng +3 more
wiley +1 more source
Optimum Carbon Fiber Reinforced Polymer (CFRP) Design for Flexural Strengthening of Cantilever Concrete Walls Using Artificial Neural Networks. [PDF]
Bekdaş G +3 more
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
Determination of Composition of Masonry Mortars for Conservation of Historical Constructions Using Artificial Neural Networks. [PDF]
Chyliński F +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
Comparative analysis of classical growth models and artificial neural networks in predicting egg production parameters in three commercial broiler parent stocks. [PDF]
Moradi Gharajeh Z +2 more
europepmc +1 more source

