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
Baseline cognitive status and adherence are associated with cognitive change following language learning in older adults: an exploratory study. [PDF]
Ghazi Saidi L +9 more
europepmc +1 more source
LLM‐Integrated Human–Robot Interaction System for Microrobots
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source
Conceptual blending in humans and language models. [PDF]
Lynn SK.
europepmc +1 more source
How Time Attitudes Shape Academic Success: The Protective Pathways of Emotion Regulation and School Well-Being in Adolescents. [PDF]
Valdebenito-Montecino Y +7 more
europepmc +1 more source
Using connectome-based predictive models to reveal the systems standardized tests and clinical symptoms are reflecting. [PDF]
Samardzija A +12 more
europepmc +1 more source
Neuropsychological assessment in adult epilepsy: rationale, test selection, and clinical integration across non-surgical care in Italian patients. [PDF]
Tomaiuolo F +6 more
europepmc +1 more source
Is "sky" bluer than "grass" is green? Word-color associations dataset for cognitive science. [PDF]
Keha E, Henik A, Kalanthroff E.
europepmc +1 more source

