Results 61 to 70 of about 6,944,236 (307)
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
The Optical RL-Gym: an open-source toolkit for applying reinforcement learning in optical networks [PDF]
, 2020 Reinforcement Learning (RL) is leading to important breakthroughs in several areas (e.g., self-driving vehicles, robotics, and network automation). Part of its success is due to the existence of toolkits (e.g., OpenAI Gym) to implement standard RL tasks.
Natalino Da Silva, Carlos +3 more
core +1 more source
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 +4 more
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 +14 more
wiley +1 more source
, 2016 RL-MD model consists of two parts: a reinforcement learning module and a memory decay part. The model was fitted the experimental data.
Majid Nili Ahmadabadi (494295) +3 more
core +1 more source
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion
Advanced Robotics Research, EarlyView.A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza +3 more
wiley +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
A framework for the robot skill learning using reinforcement learning
, 2003 Robot acquiring skill is a process similar to human skill learning. Reinforcement learning (RL) is an on-line actor critic method for a robot to develop its skill.
Zhao MY(赵明扬), Wei YZ(魏英姿)
core +1 more source
Model-Based Reinforcement Learning with Continuous States and Actions [PDF]
, 2008 22.10.13 KB. Ok to add the published version to spiral. ESANNFinding an optimal policy in a reinforcement learning (RL) framework with continuous state and action spaces is challenging. Approximate solutions are often inevitable.
Rasmussen, Carl E +7 more
core