Suparna Roy
Papers
3
Total Citations
8
H-Index
2
About
Suparna Roy is a robotics and autonomous systems researcher whose work centers on motion planning, multi-robot coordination, and intelligent navigation in dynamic environments. Her most notable contributions focus on the challenge of dynamic obstacle avoidance in multi-robot systems, where she developed a predictive approach that anticipates the future positions of moving obstacles undergoing linear motion with directional changes. This forward-looking methodology enables robots to proactively avoid collisions rather than reactively responding to immediate threats — a meaningful advancement in real-world deployment scenarios. Her 2012 foundational paper on this prediction principle has garnered 4 citations, with a 2013 follow-up extending the framework to real environments, demonstrating her commitment to bridging theoretical models with practical application. Roy has also contributed to fuzzy logic-based real-time motion planning, leveraging IR sensor data extracted during offline training to enable mobile robots to navigate unknown environments through reactive strategies. Collectively, her research addresses critical challenges in autonomous robotics, particularly in making multi-agent systems safer and more adaptive in unpredictable settings — work of growing relevance as robotic systems become increasingly integrated into complex real-world applications.
Research Focus
Key Achievements
Top Papers
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