Immanuel Ashokaraj
Papers
9
Total Citations
106
H-Index
5
About
Immanuel Ashokaraj is a robotics researcher whose work sits at the intersection of autonomous navigation, sensor fusion, and state estimation for mobile and aerial robotic systems. His research has made significant contributions to solving one of robotics' fundamental challenges: enabling robots to accurately localize and navigate themselves in real-world environments using affordable, multi-sensor configurations. Ashokaraj is particularly recognized for his innovative combination of interval analysis with nonlinear Kalman filtering techniques — including the Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) — to achieve robust robot localization. His most cited work, "Robust Sensor-Based Navigation for Mobile Robots" (2008, 37 citations), demonstrates a deterministic localization approach using ultrasonic sensors that eliminates the need for initial position estimates, a notable practical advancement. His 2004 paper on sensor fusion using interval analysis and UKF has garnered 32 citations, reflecting sustained community interest. Beyond ground robots, Ashokaraj extended his navigation frameworks to aerial platforms, broadening the applicability of his methods. He has also explored fuzzy logic as a complementary tool for feature-based navigation. Collectively, his body of work, accumulating over 100 citations, has helped establish rigorous, computationally grounded approaches to autonomous robot navigation that remain relevant to researchers and engineers in the field today.
Research Focus
Key Achievements
Top Papers
- 1Robust Sensor-Based Navigation for Mobile Robots37 citations · 2008
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- 5Feature based robot navigation: using fuzzy logic and interval analysis6 citations · 2005
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