Anirudh Krishna Lakshmanan
Papers
5
Total Citations
313
H-Index
4
About
Anirudh Krishna Lakshmanan is a robotics and artificial intelligence researcher whose work sits at the intersection of autonomous systems, computer vision, and intelligent path planning. His research focuses primarily on developing smarter, more capable robotic platforms for real-world applications, including floor cleaning, aircraft surface inspection, and multi-floor navigation. Lakshmanan's most influential contribution — garnering 185 citations — introduced a reinforcement learning-based complete coverage path planning framework for Tetromino-shaped cleaning robots, advancing how autonomous machines efficiently navigate and clean complex environments. His work on aircraft surface inspection (63 citations) demonstrated how teleoperated climbing robots, combined with enhanced deep learning, could reliably detect corrosion, cracks, and contamination, offering a safer and more efficient alternative to manual inspection processes. Beyond these landmark studies, Lakshmanan has made meaningful contributions to debris classification using cascaded machine learning techniques (50 citations), enabling floor-cleaning robots to intelligently identify and respond to challenging spillage scenarios. His research on CNN-based staircase recognition further expands the operational scope of autonomous cleaning robots into multi-floor environments. Collectively, his body of work reflects a sustained commitment to making autonomous robotic systems more perceptive, adaptive, and practically deployable across demanding real-world settings.
Research Focus
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Top Papers
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