Alhamdullilah, Delighted to share, after three years of dedication and hard work, I successfully defended my PhD thesis from Universiti Sains Malaysia (One of the top public universities in Gelugor, Malaysia. It is ranked #=137 in QS World University Rankings 2024), a milestone that represents not just the culmination of the academic pursuit but a gateway to new beginnings in the field of robotics and computer vision.
The essence of my thesis revolves around enhancing Simultaneous Localization and Mapping (SLAM) for autonomous robots in dynamic environments. This work, spanning several years, was driven by a passion to solve real-world problems through innovation and resilience. It’s a journey of continuous learning, unlearning, and relearning—underpinned by the belief that the pursuit of knowledge is endless.
Proposed research led to several publications that already been published and under review in the high ranking journals. I believe that will contribute meaningful advancements to the field of robotics:
1. MVS-SLAM: Our exploration into enhanced multiview geometry for semantic RGBD SLAM, aimed at improving robot navigation in dynamic settings (Journal of Field Robotics, Wiley).DOI https://lnkd.in/eyiy-J-p [Q1, WoS, SCOPUS, JCR]
2. ARD-SLAM: A testament to our commitment to accuracy and robustness in dynamic SLAM through innovative object identification and geometrical approaches (Displays, Elsevier). DOI https://lnkd.in/dyMMbavj [Q2, WoS, SCOPUS, JCR]
3. FADM-SLAM: Our approach to fast and accurate dynamic motion SLAM, enhancing autonomous robot exploration amidst movable objects (Robotic Intelligence and Automation). DOI https://lnkd.in/duYcffmq [Q2, SCOPUS]
Additionally, two of our articles published in conferences, including the integration of YoloV8 for dynamic SLAM and Review of SLAM, underscores our ongoing commitment to pushing the boundaries of what’s possible in robotic navigation and mapping.
As I share this, I am reminded of the countless hours of research, experimentation, and sometimes, the inevitable setbacks. Yet, it’s these challenges that make the journey worthwhile. They teach us resilience, humility, and the joy of discovery.
I am deeply grateful for the support of my family, supervisors, mentors, peers, and the academic community. As I look to the future, I am excited about continuing to explore, innovate, and contribute to our understanding of the world through the lens of robotics and computer vision.
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