Sathian Pookkuttath
Papers
10
Total Citations
106
H-Index
6
About
Sathian Pookkuttath is a robotics and artificial intelligence researcher whose work sits at the intersection of autonomous robotics, predictive maintenance, and condition monitoring. His research focuses primarily on developing AI-driven frameworks that ensure the health, safety, and operational efficiency of mobile robots across diverse real-world environments — from indoor cleaning systems to outdoor agricultural platforms. Pookkuttath's most influential contribution, "AI-Enabled Predictive Maintenance Framework for Autonomous Mobile Cleaning Robots" (2021, 37 citations), established vibration analysis as a practical diagnostic tool for detecting performance degradation in cleaning robots, laying the groundwork for a broader research agenda. He has since expanded this paradigm through optical flow-based condition monitoring, LiDAR-assisted diagnostics, and reinforcement learning-driven vibration-aware path planning, demonstrating a systematic evolution in his methodology. Beyond maintenance, Pookkuttath has contributed to deep learning-based selective floor cleaning, false ceiling inspection using reconfigurable robots, eco-friendly steam mopping autonomy, and precision agricultural pruning through the KOALA dual-arm robotic system. His cumulative citation record reflects growing recognition across the robotics community. His work is particularly valuable for researchers and engineers seeking to bridge the gap between robotic autonomy and long-term operational reliability in real-world deployment scenarios.
Research Focus
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Top Papers
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