Rapti Chaudhuri
Papers
8
Total Citations
28
H-Index
4
About
Rapti Chaudhuri is an emerging researcher specializing in autonomous mobile robotics, indoor navigation, and intelligent path optimization. Her work sits at the intersection of machine intelligence, sensor fusion, and simultaneous localization and mapping (SLAM), where she has made consistent contributions to solving real-world challenges in robot autonomy and environmental perception. Chaudhuri's most cited work explores bio-inspired and sensor-fused approaches to point-to-point navigation, integrating technologies such as LiDAR, depth data analysis, and graph-theoretic optimization to enable robust obstacle detection and spatial mapping in GPS-denied indoor environments. Her research on YOLO v4-integrated visual inference and adversarial surround localization further demonstrates her commitment to advancing perception systems for autonomous ground vehicles (AGVs). Notable contributions include her development of the "Spatio SLAM" framework, which addresses robot autonomy under variable indoor lighting conditions — a persistent challenge in dynamic scene understanding. With a growing body of work accumulating over 28 citations since 2022, Chaudhuri has established a focused research identity in autonomous systems engineering. Her interdisciplinary approach, blending biological computing paradigms with ROS-integrated robotics, makes her an increasingly relevant voice in the intelligent robotics and mobile agent research community.
Research Focus
Key Achievements
Top Papers
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- 4LiDAR Integration with ROS for SLAM Mediated Autonomous Path Exploration4 citations · 2022
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