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Development and Implementation of Intuitive Human-Machine Interaction System / SHUO ZHU

Swansea University Author: SHUO ZHU

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DOI (Published version): 10.23889/SUThesis.71084

Abstract

Robotics has been well-developed in various fields in recent years. With the widespread application of intelligent machines, the interaction between humans and them is particularly important. Simple and reliable interactive systems are the general trend of future development. This thesis focuses on t...

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Published: Swansea 2025
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
Supervisor: Li, C., and Giannetti, C.
URI: https://cronfa.swan.ac.uk/Record/cronfa71084
first_indexed 2025-12-04T14:25:28Z
last_indexed 2025-12-05T18:13:30Z
id cronfa71084
recordtype RisThesis
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spelling 2025-12-04T14:28:15.2721841 v2 71084 2025-12-04 Development and Implementation of Intuitive Human-Machine Interaction System b2855e56f40d88a07ffa46a135821464 SHUO ZHU SHUO ZHU true false 2025-12-04 Robotics has been well-developed in various fields in recent years. With the widespread application of intelligent machines, the interaction between humans and them is particularly important. Simple and reliable interactive systems are the general trend of future development. This thesis focuses on the development and implementation of serious intuitive human-machine interaction systems and explores the application of technology in graph classification, robot learning, droplet detection and robot control. First of all, the real-time observation of the intelligent machines to the outside world is particularly important. A real-time double emulsion droplet detection system based on colour space segmentation and Hough transform is proposed, which can accurately detect the contour, size and generation frequency of droplets, and provide support for quality monitoring in industrial production. In terms of graph classification, the research introduces a target-unbiased meta-learning algorithm to solve the graph structure classification problem under small sample data, demonstrates its excellent generalization ability, and improves the efficiency of image processing and recognition in human-machine interaction systems. In robot learning, the model optimized by extreme learning machine(ELM) combined with beetle antennae search(BAS)is studied, which significantly improves the accuracy and learning speed of trajectory pre-diction of KUKA iiwa robot and enhances the operational flexibility and real-time performance of the robot. The research also proposed robot path planning based on a fault-tolerant motion planning algorithm to achieve automatic drawing tasks. These studies demonstrate the important role of machine learning algorithms in robot control and planning, and significantly improve the robot’s ability to interact with the environment. In addition, the research also developed a flexible sensor data glove that can be used for remote control, further improving the naturalness and real-time nature of human-machine interaction. By integrating manual algorithms with machine learning technology, the thesis provides innovative solutions for the development of intelligent human-machine interaction systems and promotes technological progress in this field. E-Thesis Swansea Robotics, artificial intelligence, interactive systems, neural networks, path planning 25 9 2025 2025-09-25 10.23889/SUThesis.71084 COLLEGE NANME COLLEGE CODE Swansea University Li, C., and Giannetti, C. Doctoral Ph.D 2025-12-04T14:28:15.2721841 2025-12-04T14:20:06.2497560 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering SHUO ZHU 1 71084__35764__a830bc50701e49878f8f824122c3978b.pdf 2025_Zhu_S.final.71084.pdf 2025-12-04T14:24:45.3971722 Output 14998470 application/pdf E-Thesis – open access true Copyright: the author, Shuo Zhu, 2025. Distributed under the terms of a Creative Commons Attribution Non Commercial 4.0 License (CC BY-NC 4.0). true eng https://creativecommons.org/licenses/by/4.0/
title Development and Implementation of Intuitive Human-Machine Interaction System
spellingShingle Development and Implementation of Intuitive Human-Machine Interaction System
SHUO ZHU
title_short Development and Implementation of Intuitive Human-Machine Interaction System
title_full Development and Implementation of Intuitive Human-Machine Interaction System
title_fullStr Development and Implementation of Intuitive Human-Machine Interaction System
title_full_unstemmed Development and Implementation of Intuitive Human-Machine Interaction System
title_sort Development and Implementation of Intuitive Human-Machine Interaction System
author_id_str_mv b2855e56f40d88a07ffa46a135821464
author_id_fullname_str_mv b2855e56f40d88a07ffa46a135821464_***_SHUO ZHU
author SHUO ZHU
author2 SHUO ZHU
format E-Thesis
publishDate 2025
institution Swansea University
doi_str_mv 10.23889/SUThesis.71084
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
document_store_str 1
active_str 0
description Robotics has been well-developed in various fields in recent years. With the widespread application of intelligent machines, the interaction between humans and them is particularly important. Simple and reliable interactive systems are the general trend of future development. This thesis focuses on the development and implementation of serious intuitive human-machine interaction systems and explores the application of technology in graph classification, robot learning, droplet detection and robot control. First of all, the real-time observation of the intelligent machines to the outside world is particularly important. A real-time double emulsion droplet detection system based on colour space segmentation and Hough transform is proposed, which can accurately detect the contour, size and generation frequency of droplets, and provide support for quality monitoring in industrial production. In terms of graph classification, the research introduces a target-unbiased meta-learning algorithm to solve the graph structure classification problem under small sample data, demonstrates its excellent generalization ability, and improves the efficiency of image processing and recognition in human-machine interaction systems. In robot learning, the model optimized by extreme learning machine(ELM) combined with beetle antennae search(BAS)is studied, which significantly improves the accuracy and learning speed of trajectory pre-diction of KUKA iiwa robot and enhances the operational flexibility and real-time performance of the robot. The research also proposed robot path planning based on a fault-tolerant motion planning algorithm to achieve automatic drawing tasks. These studies demonstrate the important role of machine learning algorithms in robot control and planning, and significantly improve the robot’s ability to interact with the environment. In addition, the research also developed a flexible sensor data glove that can be used for remote control, further improving the naturalness and real-time nature of human-machine interaction. By integrating manual algorithms with machine learning technology, the thesis provides innovative solutions for the development of intelligent human-machine interaction systems and promotes technological progress in this field.
published_date 2025-09-25T05:32:16Z
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score 11.089407

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