Iksan Bukhori
Papers
5
Total Citations
43
H-Index
3
About
Iksan Bukhori is a leading researcher in the field of mobile robotics, with a focused expertise in solving the **kidnapped robot problem** (KRP) within Monte Carlo Localization (MCL) systems. His major contribution lies in developing novel, robust detection strategies that allow a robot to instantly recognize when it has been surreptitively moved to a new location—a critical challenge for autonomous navigation. Bukhori’s work stands out for its practical, real-time applicability; he has pioneered methods that remain accurate across varying levels of particle convergence and environmental recognition, from landmark-based maps to corridor-type layouts. His most influential paper, "Detection of kidnapped robot problem in Monte Carlo localization based on the natural displacement of the robot" (2017), has garnered 18 citations, establishing a foundation for subsequent advancements. More recently, he has extended his approach to IoT-aided platforms, employing quasi-standardized 2D Dynamic Time Warping for efficient detection in range-finder-based indoor settings. Beyond KRP, Bukhori has contributed to educational robotics, notably designing a servo-motor-based robotic arm controlled by an Arduino Uno and potentiometer, aimed at making robotics accessible to students. His work collectively advances the reliability and autonomy of robots in dynamic, real-world environments.
Research Focus
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