K. M. Ibrahim Khalilullah
Papers
4
Total Citations
28
H-Index
3
About
K. M. Ibrahim Khalilullah is a researcher focused on autonomous mobile robot navigation, particularly for assistive technologies like wheelchair robots. His core contributions lie in developing cost-effective, vision-based navigation systems that use a single camera and deep learning to operate in challenging, unstructured outdoor environments. Khalilullah’s work addresses critical problems in robot autonomy: detecting drivable road areas in real-time, handling varying weather conditions, and managing large-scale datasets efficiently. His most cited paper (14 citations) introduces a complete vision-guided navigation method using Deep Belief Neural Networks (DBNN) for urban narrow roads, creating an illuminant-invariant road database for robust performance. He further advanced this by proposing a faster road detection method using Kernel Principal Component Analysis to reduce computational load on large datasets, and developed an evolved neural controller for navigation across different weather conditions. By focusing on practical, low-cost solutions for assisting the aging population, Khalilullah’s research bridges the gap between complex deep learning models and real-world robotic applications, making autonomous wheelchairs more reliable and accessible.
Research Focus
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Top Papers
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