
Dr Erfu Yang
Senior Lecturer
Design, Manufacturing and Engineering Management
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TOP CITED ARTICLE 2021-2022 Recipient 21/2/2023 Excellent Paper Recipient 7/1/2022 TOP CITED ARTICLE 2018-2019 Recipient 5/2/2020 Best Paper Award Recipient 24/1/2019 Best Paper Award Nominee Recipient 24/9/2017 Best Poster (Application) Award Recipient 21/6/2017
Prize And Awards
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Hierarchical recursive least squares parameter estimation methods for multiple‐input multiple‐output systems by using the auxiliary models Xing Haoming, Ding Feng, Pan Feng, Yang Erfu International Journal of Adaptive Control and Signal Processing (2023) https://doi.org/10.1002/acs.3669 AMCD : an accurate deep learning-based metallic corrosion detector for MAV-based real-time visual inspection Yu Leijian, Yang Erfu, Luo Cai, Ren Peng Journal of Ambient Intelligence and Humanized Computing Vol 14, pp. 8087-8098 (2023) https://doi.org/10.1007/s12652-021-03580-4 Two-stage multi-sensor fusion positioning system with seamless switching for cooperative mobile robot and manipulator system Yang Manman, Yang Erfu International Journal of Intelligent Robotics and Applications Vol 7, pp. 275-290 (2023) https://doi.org/10.1007/s41315-023-00276-0 Human–robot collaborations in smart manufacturing environments : review and outlook Othman Uqba, Yang Erfu Sensors Vol 23 (2023) https://doi.org/10.3390/s23125663 A robust learned feature-based visual odometry system for UAV pose estimation in challenging indoor environments Yu Leijian, Yang Erfu, Yang Beiya, Fei Zixiang, Niu Cong IEEE Transactions on Instrumentation and Measurement Vol 72, pp. 1-11 (2023) https://doi.org/10.1109/TIM.2023.3279458 Bio-inspired locomotion control for UBot self-reconfigurable modular robot Cui Xindan, Zhu Yanhe, Zhao Jie, Piao Songhao, Yang Erfu 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023 2023 International Conference on Control, Automation and Diagnosis, ICCAD 2023, pp. 1-6 (2023) https://doi.org/10.1109/iccad57653.2023.10152395
Publications
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STEP - Becoming a Strathclyde Scholar (of teaching and learning) Participant 16/6/2023 Examiner Examiner 9/6/2023 The pro2 network+ (External organisation) Member 24/5/2023 The Scientific Machine Learning Seminar Participant 16/5/2023 Poster on "A novel deep neural network-based emotion analysis system for automatic detection of mild cognitive impairment" Contributor 3/5/2023 Robust Sensing, Detection and Localisation for UAV-Based Smart Visual Inspection in Complex Environments Invited speaker 27/4/2023
Cobot – Human Interaction PhD Case Study Yang, Erfu (Principal Investigator) Othman, Uqba (Researcher) 16-Jan-2022 - 31-Jan-2024 Adaptive Path Planning and Visual Navigation of Autonomous Inspection Robots in Challenging Environments Yang, Erfu (Principal Investigator) Dobie, Gordon (Co-investigator) Jiang, Meiling (Researcher) This project aims to fundamentally investigate the novel adaptive path planning and visual navigation of robots (such as an industrial robot manipulator, Cobot, UAV etc.) for autonomous inspection by enabling holistic control and interactions of robots in complex, dynamic and changing environments such that safety and interaction of nearby humans/operators/other objects etc. can be maintained while the inspection tasks are taking place. At the same time, the efficiency and flexibility of the inspection process is also achieved when process variations or environmental changes take place. 01-Jan-2022 - 30-Jan-2025 MOEA/D-PPR: Path Planning of Robots in Complex Environments via the Multiobjective Evolutionary Algorithm Based on Decomposition Yang, Erfu (Principal Investigator) Dobie, Gordon (Co-investigator) 31-Jan-2022 - 30-Jan-2024 Flexible Human-Robot Collaborative Inspection for In-Process Quality Control in Smart Manufacturing Yang, Erfu (Principal Investigator) Luo, Xichun (Co-investigator) Othman, Uqba (Researcher) The overall research aim of this project is to fundamentally investigate the novel flexible human-robot collaborative inspection strategies by enabling holistic control and interactions of collaborative robots in complex human-robot collaborative manufacturing environments such that safety and interaction of nearby humans/operators can be maintained while the in-process inspection and quality control are being done. At the same time, the efficiency and flexibility of the manufacturing process is also achieved when process variations or environmental changes occur in advanced manufacturing systems.
To achieve this aim, the proposed project will be focusing on the following three research objectives: 1) A comprehensive review of the state of the art in collaborative robotics and human-robot interactions towards smarter manufacturing in the digital age. 2) Investigation of novel concepts and algorithms for intelligent control, motion planning, and machine learning. 3) Development and testing of prototype sensing, Inspection with machine vision and NDT, path planning, and control system in the complex human-robot collaborative manufacturing environments. 01-Jan-2021 - 30-Jan-2024 Pilot Research for Cobot Solution Development Yang, Erfu (Principal Investigator) Stasse, Florian (Researcher) Moonnamthodiyil Mohandas, Aravind (Researcher) A Cobot (Collaborative Robot) pilot research project funded by an internationally leading industry. 16-Jan-2021 - 15-Jan-2022 Autonomous and Interactive Station Rover for Next-Generation Passenger Information System Yang, Erfu (Principal Investigator) Luo, Xichun (Co-investigator) Corney, Jonathan (Co-investigator) Alcantara de la Cruz, Daniel (Researcher) KTP project with TrainFX Limited. In total £190,122, funded by the Innovate UK. 01-Jan-2021 - 31-Jan-2023
Professional Activities
Projects
To achieve this aim, the proposed project will be focusing on the following three research objectives: 1) A comprehensive review of the state of the art in collaborative robotics and human-robot interactions towards smarter manufacturing in the digital age. 2) Investigation of novel concepts and algorithms for intelligent control, motion planning, and machine learning. 3) Development and testing of prototype sensing, Inspection with machine vision and NDT, path planning, and control system in the complex human-robot collaborative manufacturing environments.
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Contact
Dr
Erfu
Yang
Senior Lecturer
Design, Manufacturing and Engineering Management
Email: erfu.yang@strath.ac.uk
Tel: 574 5279