Results 151 to 160 of about 23,557 (297)

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
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, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

Toward Wireless Implantable Robotic Systems Driven by Magnetic Field for Personalized Therapy

Advanced Robotics Research, EarlyView.
Robotic materials are playing an increasingly vital role in enabling sensing and actuation at small scales. This perspective highlights recent advances in magnetic materials and magnetically actuated devices for wireless sensing, actuation, and energy harvesting toward implantable robotic systems for closed‐loop therapy.
Yusheng Wang, Ruijian Ge, Xiaoguang Dong
wiley   +1 more source

Nonlocomotory Robotic Strategies for Dynamic Rotation Control in Terrestrial Robots: A Review

Advanced Robotics Research, EarlyView.
Terrestrial robots increasingly require rapid body rotation to maintain stability and agility in complex environments. This review shows nonlocomotory rotational control strategies that operate without ground contact, including reaction wheels, tails, bars, limbs, and thrusters.
Y. Liang, J. An, X. Zheng, D. Wang, S. Wang, X. Wang, P. Zhu, J. Pei, S. Li, J. Paripurana, Y. Han, Z. Tang, X. Gan, Q. He, X. Ma   +14 more
wiley   +1 more source

Backpropagation Through Soft Body: Investigating Information Processing in Brain–Body Coupling Systems

Advanced Robotics Research, EarlyView.
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka, Katsuma Inoue, Yasuo Kuniyoshi, Kohei Nakajima   +3 more
wiley   +1 more source

Automating quantitative information flow

, 2011
PhDUnprecedented quantities of personal and business data are collected, stored, shared, and processed by countless institutions all over the world.
Heusser, Jonathan
core  

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
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, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Enhancing reliability and automation of LLM-based structural analysis using a hybrid multi-agent pipeline. [PDF]

Sci Rep
Heo S.
europepmc   +1 more source

Efficient and Robust Standing Postures of Quadruped Robots

Advanced Robotics Research, EarlyView.
A calibrated static framework estimates load, optimizes torques, and adapts posture so quadruped robots stand efficiently and robustly under external payloads, achieving up to 50% lower torque demand. Inspired by the natural posture adjustments of animals under external loading, this article presents an optimization‐based framework for minimizing joint
Mohamad Kanaan, Hamza Jomaa, Jack Challita, Kawthar Zaidan, Riad Saab, Hussein Hussein   +5 more
wiley   +1 more source

Situational awareness predicts self-management of type I diabetes in adolescents and young adults. [PDF]

Health Psychol
Cook PF, Jost E, Forlenza G, Messer LH, Thompson S, Peck E, Voida S.   +6 more
europepmc   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
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