Results 141 to 150 of about 8,669,620 (261)

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

Deep reinforcement learning and snake-like robot locomotion design

, 2020
This master thesis is discussing application of reinforcement learning in deep learning tasks. In theoretical part, basics about artificial neural networks and reinforcement learning.
Kočí, Jakub
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

Hybrid Continuum Robot Designs and Architectures for Healthcare Applications

Advanced Robotics Research, EarlyView.
Hybrid continuum robots represent an emerging class of flexible manipulators that blend materials, structures, and actuation concepts from the established fields of soft and continuum robotics. This review introduces an accessible framework to distinguish key hybridization approaches, surveys current designs aimed at complex clinical applications, and ...
Burak Ozdemir, Muhammad A. Khalid, Manish Chauhan, Pietro Valdastri, James H. Chandler   +4 more
wiley   +1 more source

An introduction to deep reinforcement learning

, 2018
Written by recognized experts, this book is an important introduction to Deep Reinforcement Learning for practitioners, researchers and students ...
François-Lavet, Vincent, Henderson, Peter, Pineau, Joelle, Islam, Riashat, Bellemare, Marc G   +4 more
core  

Deep reinforcement learning for quantum Hamiltonian engineering

Source code to learn dynamical decoupling sequences in the ideal case using deep reinforcement learning.
Peng, Pai
core   +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

Improving performance in SNN-based deep reinforcement learning via transition-aware embeddings. [PDF]

Front Neurorobot
Takigasaki H, Iwata T, Yoshioka S, Miki D.   +3 more
europepmc   +1 more source

Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots

Advanced Robotics Research, EarlyView.
This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou, Zhiqiang Chen, Yuanbiao Ma, Zhiqiang Tang, Qianqian Wang   +4 more
wiley   +1 more source

Deep Reinforcement Learning for Collision-Aware Leader-Follower Formation Control. [PDF]

Sensors (Basel)
Romaniuk S, Budnik J.
europepmc   +1 more source