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
William Bynum Prize 2023: Highly Commended Overcoming Childlessness: Narratives of Conception in Early Modern North India. [PDF]
Wigh S.
europepmc +1 more source
Diagnosing Rickets in Early Modern England: Statistical Evidence and Social Response. [PDF]
Newton G.
europepmc +1 more source
Waveguide Photoactuators: Materials, Fabrication, and Applications
Waveguide photoactuators convert guided light into mechanical motion. Their tethered‐flexible design enables minimally invasive surgery and confined‐space robotics. This review aims to guide materials selection, device design, and system integration, accelerating the transition of waveguide photoactuators from laboratory prototypes to versatile ...
Minjie Xi +4 more
wiley +1 more source
Warming Technologies, Cold Bodies, and Everyday Health in Early Modern England. [PDF]
Leong E.
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
Shells of <i>Littorina littorea</i> (Gastropoda)-an archive for palaeoclimate and seasonal shellfish collection in medieval and early modern Orkney? [PDF]
Schöne BR +3 more
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
Biblical Stories on the Medieval and Early Modern Stage: A Transnational Approach. [PDF]
Bloemendal J.
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

