Papers
39
Total Citations
951
H-Index
15
About
Balakrishnan Ramalingam is a prominent robotics and artificial intelligence researcher whose work sits at the dynamic intersection of autonomous mobile robotics, deep learning, and intelligent inspection systems. His research has made substantial contributions to autonomous cleaning and maintenance robotics, path planning, and surface inspection technologies — areas of growing global relevance, particularly in the wake of the COVID-19 pandemic. Ramalingam's most celebrated contribution, "Complete Coverage Path Planning using Reinforcement Learning for Tetromino Based Cleaning and Maintenance Robot" (2020), has garnered over 185 citations, establishing him as a leading voice in autonomous navigation methodologies. His complementary work on hybrid RRT* path planning algorithms further demonstrates his commitment to advancing robot mobility in complex environments. Across multiple high-impact studies, he has pioneered deep learning frameworks enabling robots to perform nuanced tasks — from disinfecting door handles and cleaning tables to detecting aircraft surface defects and pavement cracks — with each paper attracting between 50 and 96 citations. With a cumulative citation count exceeding 675 across his top works, Ramalingam's research directly addresses real-world challenges in sanitation, infrastructure maintenance, and industrial safety. His interdisciplinary approach, blending fuzzy logic, cascaded machine learning, and AI-driven predictive maintenance, makes his portfolio essential reading for anyone exploring the future of intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 5Table Cleaning Task by Human Support Robot Using Deep Learning Technique58 citations · 2020
- 6Deep Learning Based Pavement Inspection Using Self-Reconfigurable Robot52 citations · 2021
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