Md Rafiqul Islam

Md Rafiqul Islam

Research Associate
UNSW Canberra
School of Eng & Tech

Dr. Rafiqul Islam is a postdoctoral researcher at UNSW@ADFA, specialising in robotics and autonomous systems. He earned his PhD in Robotics/Mechatronics at the University of South Australia in 2022, 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 in 2016, 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.

Location
Room 370, Building 21 School of Engineering and Technology (SET) University of New South Wales (UNSW) Australian Defence Force Academy (ADFA) Canberra ACT
  • Journal articles | 2023
    Islam R; Habibullah H; Hossain T, 2023, 'AGRI-SLAM: a real-time stereo visual SLAM for agricultural environment', Autonomous Robots, 47, pp. 649 - 668, http://dx.doi.org/10.1007/s10514-023-10110-y
    Journal articles | 2023
    Karunanayake I; Ahmed N; Malaney R; Islam R; Jha SK, 2023, 'Darknet Traffic Analysis: Investigating the Impact of Modified Tor Traffic on Onion Service Traffic Classification', IEEE Access, 11, pp. 70011 - 70022, http://dx.doi.org/10.1109/ACCESS.2023.3293526
    Journal articles | 2022
    Hossain T; Habibullah H; Islam R; Padilla RV, 2022, 'Local path planning for autonomous mobile robots by integrating modified dynamic-window approach and improved follow the gap method', Journal of Field Robotics, 39, pp. 371 - 386, http://dx.doi.org/10.1002/rob.22055
    Journal articles | 2022
    Hossain T; Habibullah H; Islam R, 2022, 'Steering and Speed Control System Design for Autonomous Vehicles by Developing an Optimal Hybrid Controller to Track Reference Trajectory', MACHINES, 10, http://dx.doi.org/10.3390/machines10060420
    Journal articles | 2022
    Islam R; Habibullah H, 2022, 'Place Recognition with Memorable and Stable Cues for Loop Closure of Visual SLAM Systems †', Robotics, 11, http://dx.doi.org/10.3390/robotics11060142
    Journal articles | 2022
    Sun N; Li CT; Chan H; Islam MZ; Islam MR; Armstrong W, 2022, 'How Do Organizations Seek Cyber Assurance? Investigations on the Adoption of the Common Criteria and Beyond', IEEE Access, 10, pp. 71749 - 71763, http://dx.doi.org/10.1109/ACCESS.2022.3187211
  • Conference Papers | 2024
    Islam R; Anavatti S; Kasmarik K; Garratt M, 2024, 'Robust and Scalable Swarming of Quadruped Robots for Chemical, Biological, Radiological, and Nuclear Source Localisation', in 2024 10th International Conference on Mechatronics and Robotics Engineering (ICMRE), IEEE, presented at 2024 10th International Conference on Mechatronics and Robotics Engineering (ICMRE), 27 February 2024 - 29 February 2024, http://dx.doi.org/10.1109/icmre60776.2024.10532170
    Conference Papers | 2024
    Tungthamrongkul Y; Perera A; Islam R; Anavatti S, 2024, 'Intelligent Control System for Ground Vehicles', in 2024 10th International Conference on Mechatronics and Robotics Engineering (ICMRE), IEEE, presented at 2024 10th International Conference on Mechatronics and Robotics Engineering (ICMRE), 27 February 2024 - 29 February 2024, http://dx.doi.org/10.1109/icmre60776.2024.10532179
    Conference Papers | 2021
    Islam R; Habibullah H, 2021, 'A Semantically Aware Place Recognition System for Loop Closure of a Visual SLAM System', in 2021 4th International Conference on Mechatronics, Robotics and Automation, ICMRA 2021, pp. 117 - 121, http://dx.doi.org/10.1109/ICMRA53481.2021.9675715

 📅 2023/06-2023/11 Trusted Autonomy Self-Forming Research Group Bid
                                   University of New South Wales
                                   Kasmarik K., Garratt M., Islam R., and 10 others
                                   Grant amount: $20,475

 📅 2021/09-2022/04 Manufacturing an Advanced Unmanned Ground Vehicle
                                    University of South Australia
                                    Islam, R., and Habibullah H.
                                    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 the Course Convenor and Lecturer for Autonomous Robots (ZEIT4160) at UNSW@ADFA, 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.