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Yuqian Lu

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Lecturer

University of Auckland

New Zealand

Research Interests

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About

Yuqian Lu is a Lecturer at The University of Auckland, New Zealand. His research areas include smart manufacturing, human-robot collaboration, and digital twin technologies. His recent publications focus on topics such as multi-agent reinforcement learning, machining quality characterization, and dynamic reconfiguration in manufacturing systems.

Recent Grants

Grant: Open

Ultra-flexible human-robot collaborative product assembly

Open Date: 2024-10-01

Close Date: 2027-09-30

Grant: Close

Developing a Construction 4.0 transformation of Aotearoa New Zealand's construction sector

Open Date: 2022-10-01

Close Date: 2026-09-30

Articles (21)

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2022

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2022

Collaborators (11)

Sihan Huang

Research professor

Beijing Institute of Technology

CHINA

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Meng Jiang

Associate Professor

Harbin Institute of Technology

CHINA

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Chao Liu

Senior Lecturer

Aston University

UNITED KINGDOM

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Seyed Hesam Hosseinizadeh Mazluomi

Professional Casual Staff

University of Auckland

NEW ZEALAND

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Yuchun Xu

Prof

Aston University

UNITED KINGDOM

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Lihui Wang

The Hong Kong Polytechnic University

HONG KONG

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Jaspreet Singh Dhupia

Senior Lecturer

University of Auckland

NEW ZEALAND

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Shokraneh K. Moghaddam

University of Hertfordshire

UNITED KINGDOM

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Yu Jia

Aston University

UNITED KINGDOM

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Madhurjya Dev Choudhury

Assistant Professor

Birla Institute of Technology and Science (BITS), Pilani

View details

Ming Zhang

Aston University

UNITED KINGDOM

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Yuqian Lu

Research Interests

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About

Recent Grants

Articles (21)

Reducing Barriers to Vibration Condition Monitoring of Rotating Machinery: A Self-Configuring Algorithm Without Requiring Prior Fault Samples

Multi-view fusion for human action recognition and cognitive assistive systems in industrial assembly

Multi-Agent Continuous Decision-Making for the Continuous Dynamic Flexible Job Shop Scheduling Problem

Digital Twin-driven multi-scale characterization of machining quality: current status, challenges, and future perspectives

A method for constructing a machining knowledge graph using an improved transformer

An ontology and rule-based method for human–robot collaborative disassembly planning in smart remanufacturing

Smart manufacturing enabled by intelligent technologies

Deep Reinforcement Learning-Based Dynamic Reconfiguration Planning for Digital Twin-Driven Smart Manufacturing Systems With Reconfigurable Machine Tools

Ensemble Bayesian Network for root cause analysis of product defects via learning from historical production data

Knowledge graph-enhanced multi-agent reinforcement learning for adaptive scheduling in smart manufacturing

Human-Robot Shared Assembly Taxonomy: A step toward seamless human-robot knowledge transfer

A systematic framework for tackling anomalous pre-welding workpiece postures with regular butt joints based on prototype features

One-shot, integrated positioning for welding initial points via co-mapping of cross and parallel stripes

Full-cycle data purification strategy for multi-type weld seam classification with few-shot learning

A digital thread-driven distributed collaboration mechanism between digital twin manufacturing units

Dynamic muscle fatigue assessment using s-EMG technology towards human-centric human-robot collaboration

Dynamic production scheduling towards self-organizing mass personalization: A multi-agent dueling deep reinforcement learning approach

Prognostics and health management via long short-term digital twins

Adaptive reconstruction of digital twins for machining systems: A transfer learning approach

Multi-Agent Reinforcement Learning for Real-Time Dynamic Production Scheduling in a Robot Assembly Cell

3DSMDA-Net: An improved 3DCNN with separable structure and multi-dimensional attention for welding status recognition

Collaborators (11)

Sihan Huang

Meng Jiang

Chao Liu

Seyed Hesam Hosseinizadeh Mazluomi

Yuchun Xu

Lihui Wang

Jaspreet Singh Dhupia

Shokraneh K. Moghaddam

Yu Jia

Madhurjya Dev Choudhury

Ming Zhang

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