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About

Elankovan Sundararajan is a robotics and computer vision researcher whose work bridges real-time object tracking, autonomous navigation, and industrial manipulator control. His most cited paper (22 citations) investigates the Threading Building Blocks framework for color-based visual object tracking, addressing critical performance bottlenecks in surveillance, search-and-rescue, and augmented reality applications. Sundararajan further advanced autonomous systems by demonstrating object detection without color features (15 citations), a key capability for robots operating in monochrome or low-light environments. His foundational work on contour following for industrial robots—using a dual sensor logic algorithm for Adept SCARA manipulators—tackles tedious manufacturing tasks like welding, sealing, and grinding. Though early citations are modest, Sundararajan’s research trajectory shows a clear focus on making robotic perception and control more efficient, robust, and hardware-aware. His contributions are particularly relevant for students and engineers working on embedded vision systems, multi-threaded real-time processing, and sensor integration for autonomous platforms.