Scalable Task Planning via Large Language Models and Structured World Representations
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari +4 more
wiley +1 more source
The influence of teacher leadership on students academic burnout in China: potential multiple mediating effects of meeting basic psychological needs. [PDF]
Fang A.
europepmc +1 more source
From Rigid to Soft Robotic Approaches for Neuroendoscopy
Robotic assistance has had minimal impact on deep intraventricular surgeries, where small‐scale, precision, and reduced invasiveness can contribute to improved patient outcomes. Emerging technologies in rigid, soft, and hybrid robotics are reviewed to identify the most promising mechanisms for deep brain navigation in addition to an attempt to identify
Kieran Gilday +3 more
wiley +1 more source
Enhancing creative process engagement in university students: the mediating role of trust and empowerment and the moderating effect of proactive personality in humble teacher leadership. [PDF]
Zhang X, Chi J.
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
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
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Echinoderm‐Inspired Autonomy for Soft‐Legged Robots
Inspired by echinoderms, a modular soft robot achieves autonomous phototaxis without a central controller or explicit communication. Each limb independently adapts its actuation timing through local sensing and short‐term memory. Coordination emerges purely from physical interactions, demonstrating resilience to changes in morphology, environment, and ...
Harmannus A. H. Schomaker +2 more
wiley +1 more source
The structure and influencing factors of educationalist spirit among students majoring in education: an integrated model based on entrepreneurial leadership and teacher efficacy. [PDF]
Jinke L, Siya Z, Yifei L.
europepmc +1 more source

