Results 171 to 180 of about 16,840,789 (262)
Neuro-symbolic NLP: taxonomy, assessment, and directions. [PDF]
Chatzikyriakidis S, Lappin S.
europepmc +1 more source
3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu +5 more
wiley +1 more source
The Abelian group structure of full factorial designs. [PDF]
Altieri NA.
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
Embodied intelligence-driven adaptive collaboration in supply chains: A four-dimensional synergy framework and mechanism analysis. [PDF]
Ding Z, Lin H, Xu H, Zhang X, Zhu X.
europepmc +1 more source
Liquid Crystalline Elastomers in Soft Robotics: Assessing Promise and Limitations
Liquid crystalline elastomers (LCEs) are programmable soft materials that undergo large, anisotropic deformation in response to external stimuli. Their molecular alignment encodes directional actuation in a monolithic structure, making them long‐standing candidates for soft robotic systems.
Justin M. Speregen, Timothy J. White
wiley +1 more source
Automatic Verification for Secrecy of Cryptographic Protocols in First-Order Logic
Jihong Han, Zhiyong Zhou, Yadi Wang
doaj +1 more source
Logic, inference, understanding: cross-domain generalization for generative language models. [PDF]
Blanck R, Noble B.
europepmc +1 more source
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
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 +2 more
wiley +1 more source

