Deep reinforcement learning applied to an assembly sequence planning problem with user preferences

Solving job scheduling problems in a resource preemption environment with multi-agent reinforcement learning

(2022) Xiaohan Wang et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Cyber-physical assembly system-based optimization for robotic assembly sequence planning

(2021) Kuo-Ching Ying et al.   JOURNAL OF MANUFACTURING SYSTEMS

A study on a Q-Learning algorithm application to a manufacturing assembly problem

(2021) Miguel Neves et al.   JOURNAL OF MANUFACTURING SYSTEMS

Evaluating Guided Policy Search for Human-Robot Handovers

(2021) Alap Kshirsagar et al.   IEEE Robotics and Automation Letters

Human-Guided Robot Behavior Learning: A GAN-Assisted Preference-Based Reinforcement Learning Approach

(2021) Huixin Zhan et al.   IEEE Robotics and Automation Letters

Task-level decision-making for dynamic and stochastic human-robot collaboration based on dual agents deep reinforcement learning

(2021) Zhihao Liu et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Optimizing task scheduling in human-robot collaboration with deep multi-agent reinforcement learning

(2021) Tian Yu et al.   JOURNAL OF MANUFACTURING SYSTEMS

An adaptive human sensor framework for human–robot collaboration

(2021) Achim Buerkle et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Adaptive disassembly sequence planning for VR maintenance training via deep reinforcement learning

(2021) Haoyang Mao et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

A reinforcement learning method for human-robot collaboration in assembly tasks

(2021) Rong Zhang et al.   ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING

Search algorithm of the assembly sequence of products by using past learning results

(2020) Keijiro Watanabe et al.   INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Reinforcement learning for facilitating human-robot-interaction in manufacturing

(2020) Harley Oliff et al.   JOURNAL OF MANUFACTURING SYSTEMS

An adaptive deep reinforcement learning framework enables curling robots with human-like performance in real-world conditions

(2020) Dong-Ok Won et al.   Science Robotics

Human-Centered Collaborative Robots With Deep Reinforcement Learning

(2020) Ali Ghadirzadeh et al.   IEEE Robotics and Automation Letters

A review of machine learning for the optimization of production processes

(2019) Dorina Weichert et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Mastering the game of Go without human knowledge

(2017) David Silver et al.   NATURE

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Benchmarking in Manipulation Research: Using the Yale-CMU-Berkeley Object and Model Set

(2015) Berk Calli et al.   IEEE ROBOTICS & AUTOMATION MAGAZINE