Susama Bagchi

Tun Hussein Onn University of Malaysia, Chitkara University

Papers

Total Citations

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About

Susama Bagchi’s research lies at the intersection of autonomous systems, human-robot interaction, and artificial intelligence, with a strong focus on advancing unmanned aerial vehicle (UAV) technology. Her most cited work, a comprehensive 2020 review of cell decomposition path planning methods for UAVs (39 citations), established her as a key voice in navigation algorithms for autonomous flight. She has pioneered novel approaches to gesture-based UAV control, developing a deep learning framework for 3D hand gesture segmentation and optimized classification (27 citations) that bypasses traditional electronic controllers, offering operators greater ease and natural interaction. Bagchi has also explored theoretical foundations of machine intelligence, drawing on Turing’s legacy to propose a “Big Bang theory” inspired model for machine learning environments. Her recent work extends into construction robotics with a floor tiling robotic system, demonstrating her commitment to translating research into practical, real-world automation. Through her diverse contributions, Bagchi continues to shape how robots perceive, plan, and interact with humans.