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
Sinogram-based flow estimation in computed tomography using a physics-informed neural network: Impact of gantry rotation speed, X-ray fluence and pulsed acquisition on accuracy. [PDF]
Guo J +4 more
europepmc +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
Physics-Informed Neural Network-Based Pulsatile Flow Modeling and Targeted Drug Delivery Optimization in Computational Hemodynamics. [PDF]
Vaghela AK.
europepmc +1 more source
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
A Physics-Informed Neural Network (PINN) Approach to Over-Equilibrium Dynamics in Conservatively Perturbed Linear Equilibrium Systems. [PDF]
Dutta A +5 more
europepmc +1 more source
This review identifies key design considerations for insect‐inspired microrobots capable of multimodal locomotion. To draw inspiration, biological and robotic strategies for moving in air, on water surfaces, and underwater are examined, along with approaches for crossing the air–water interface.
Mija Jovchevska +2 more
wiley +1 more source
Identification of Adiabatic Temperature Rise Characteristics for Mass Concrete Using the Physics-Informed Neural Network. [PDF]
Lee JM, Lee CJ, Jeong W.
europepmc +1 more source
Degradable Magnetic Composites from Recycled NdFeB Magnets for Soft Actuation and Sensing
This work presents a degradable soft magnetic composite made from recycled NdFeB particles embedded in a gelatin‐based organogel. The material is processed into magnetic sensors and soft robotic components, which can later be dissolved in a green solvent to recover NdFeB magnetic particles.
Muhammad Bilal Khan +14 more
wiley +1 more source

