Md Rafiqul Islam
Research Associate
¶¶Òõ¶ÌÊÓƵ
School of Eng & Tech
Dr. Rafiqul Islam is a postdoctoral researcher at UNSW@¶¶Òõ¶ÌÊÓƵ, specialising in robotics and autonomous systems. He earned his PhD in Robotics/Mechatronics from the University of South Australia, where he developed deep expertise in addressing advanced robotics challenges. His pioneering research encompasses motion planning and control, Simultaneous Localisation and Mapping (SLAM), and sensor fusion, leveraging cutting-edge technologies in control engineering, computer vision, and artificial intelligence to enhance autonomous robot navigation. Currently, Dr. Rafiqul 's work is at the forefront of innovative research on the strategic coordination of autonomous robots, significantly advancing the capabilities of these systems.
Prior to his doctoral studies, Dr. Rafiqul was employed as an Assistant Engineer at Impulse Engineering and Power Ltd. in Bangladesh, where he honed his practical engineering skills. He completed his undergraduate studies in Electrical and Electronic Engineering from Eastern University, graduating with a Magna Cum Laude award.
Dr. Rafiqul 's academic and professional journey reflects a deep commitment to advancing the field of robotics through innovative research and practical applications, aiming to enhance the functionality and efficiency of autonomous systems.
E-mail
Location
Room 370, Building 21
School of Engineering and Technology (SET)
University of New South Wales (UNSW)
Australian Defence Force Academy (¶¶Òõ¶ÌÊÓƵ)
Canberra ACT
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
ÌýÌý? 2024/05-2025/02ÌýAdaptive C-RAS Camouflage System
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Australian Department of Defence
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Asanka P., Garratt M., Islam R., and Yasas M.
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Grant amount: $52,140
? 2023/06-2023/11 Trusted Autonomy Self-Forming Research Group Bid
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýUniversity of New South Wales
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýKasmarik K., Garratt M., Islam R., and 10 others
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý ÌýGrant amount: $20,475
Ìý? 2021/09-2022/04 Manufacturing an Advanced Unmanned Ground Vehicle
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý University of South Australia
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Islam, R., and Habibullah H.
Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Ìý Grant amount: $14,500
Dr. Rafiqul is at the forefront of innovative research within the fields of robotics and artificial intelligence. His research utilises cutting-edge technologies, including computer vision, deep learning, reinforcement learning, and broad AI applications for autonomous robotics. His hands-on expertise with advanced robotic platforms is instrumental to his research. These platforms include:
- Unitree Go1 Edu: A versatile quadruped robot designed for dynamic manoeuvring across complex terrains, enabling studies in adaptive locomotion.
- Ghost Vision 60: Known for its substantial sensory and payload capabilities, this quadruped robot facilitates advanced research in robust environmental interaction.
- AgileX Scout: A 4WD robot that showcases the seamless integration of agility and precision in navigation, ideal for exploring efficient pathfinding algorithms.
- AgileX Bunker: A rugged tracked robot tailored for challenging terrains, enhancing studies in durable robotic design and functionality.
- Jackal UGV: A compact 4WD robot optimal for research on multi-robot systems, focusing on collaborative tasks and swarm intelligence.
Utilising these platforms, Dr. Rafiqul conducts research encompassing, but not limited to, the following areas:
- SLAM (Simultaneous Localisation and Mapping): Enhancing robotic understanding and mapping of unknown environments.
- Dead Reckoning and Robot Localisation through Sensor Fusion: Improving accuracy in how robots perceive their position and orientation.
- RL-Powered Motion Planning and Control: Developing smarter, more adaptable robotic movements using reinforcement learning.
- Swarming for CBRN Source Localisation: Employing both homogeneous and heterogeneous robot swarms to detect and localise chemical, biological, radiological, and nuclear sources.
- Deep Learning-Based Camouflage Generator: Creating algorithms that enable defence applications in camouflage generation, leveraging deep learning techniques.
- Autonomous Navigation: Advancing the autonomy of robots in navigating through diverse settings without human intervention.
Dr. Rafiqul's contributions significantly advance the field of robotics, making substantial impacts on both theoretical frameworks and practical applications in artificial intelligence and robotic systems.
My Teaching
As a Lecturer for Autonomous Robots (ZEIT4160) at UNSW@¶¶Òõ¶ÌÊÓƵ, Dr. Rafiqul spearheaded the curriculum for this innovative course introduced in Term 2, 2023. The course utilises TurtleBot4 mobile robots to provide hands-on learning experiences in robotics and autonomous systems, equipping students with essential skills for the future of robotics technology.
Additionally, Dr. Rafiqul was the Course Coordinator and Lecturer for several core robotics and mechatronics courses at UniSA. During his academic position at UniSA, he has played a pivotal role in teaching and developing a wide range of courses, including:
- Machine Learning and Vision Systems, 2022
- Embedded System Design, 2021-22
- Control System, 2021-22
- Mobile Autonomous Robotic Systems, 2020-21
- Robotics and Automation, 2021
- Mechatronics System Design I, 2020
Dr. Rafiqul’s commitment to educational excellence in engineering fosters a practical and theoretical understanding of complex systems, contributing to the academic and professional advancement of his students.