B.L.U. Udugama Vithanage MSc (Bavantha)

As a seasoned Robotics Engineer with a passion for innovation, I bring a wealth of industry and research experience to the field. My expertise includes Humanoid Robotics, Machine Learning, Image Processing, SLAM, and Navigation with Advanced Control Systems, honed through my Master of Science in Robotics from Middlesex University.

At Expert Hub Robotics, I have served as a Senior Robotics Engineer and Project Lead, showcasing my skills in configuring SLAM and navigation systems on humanoid robots, designing custom attachments, developing AI-based Chatbot applications, and executing specialized software implementations. My experience also extends to the VLSI industry, where I worked as a Corporate Application Engineer and was involved in complex customer feature validation, product development, and hierarchical CDC flow validation.

My commitment to excellence has been recognized through several awards, including the Best Undergraduate Project Award from the IESL and the Best Technical Paper Award from the IET. With a desire to make a meaningful impact, I am eager to bring my industry expertise to the research field and contribute to the ongoing advancements in robotics.

Faculty of Geo-Information Science and Earth Observation (ITC), Department of Earth Observation Science (EOS)

My current research endeavors are aimed at advancing the field of UAV mapping through the integration of photogrammetric computer vision, deep learning, deep reinforcement learning, and robotics. The objective is to develop algorithms for reliable and autonomous real-time mapping capabilities for drones.

I am working towards creating autonomous drones that can perform complex tasks by combining autonomous navigation algorithms with 3D semantic understanding of the environment. The aim is to achieve advanced capabilities in various applications such as patrolling, search and rescue operations in both outdoor and indoor environments, and precision farming.

I am deeply passionate about the potential of this research and am committed to making a meaningful impact in the field of robotics. I believe that my efforts will lead to innovative solutions that can address real-world challenges and push the boundaries of what is possible.

Udugama, U. V. B. L. , Vosselman, G. , & Nex, F. (2023). Mono-hydra: Real-time 3D scene graph construction from monocular camera input with IMU. In N. El-Sheimy, A. A. Abdelbary, N. El-Bendary, & Y. Mohasseb (Eds.), ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (Vol. X-1/W1-2023, pp. 439-445). (ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences). Copernicus. https://doi.org/10.5194/isprs-annals-X-1-W1-2023-439-2023

Udugama, U. V. B. L. , Vosselman, G. , & Nex, F. (2023). Mono-hydra: Real-time 3D scene graph construction from monocular camera input with IMU. ArXiv.org. https://doi.org/10.48550/arXiv.2308.05515

Udugama, U. V. B. L. (2023). Review on Efficient Strategies for Coordinated Motion and Tracking in Swarm Robotics. ArXiv.org. https://doi.org/10.48550/arXiv.2302.06360

Udugama, U. V. B. L. (2023). Evolution of SLAM: Toward the Robust-Perception of Autonomy. ArXiv.org. https://doi.org/10.48550/arXiv.2302.06365

Udugama, U. V. B. L. (2023). Review of Deep Reinforcement Learning for Autonomous Driving. ArXiv.org. https://doi.org/10.48550/arXiv.2302.06370

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Naar mijn profiel

Master of Science in Robotics,