I Kadek Nuary Trisnawan

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About

I Kadek Nuary Trisnawan is a researcher specializing in mobile robotics and sensor-based localization systems, with a particular focus on probabilistic methods for autonomous navigation. His most cited work, "Implementation of Mobile Sensor Navigation System Based on Adaptive Monte Carlo Localization" (2019, 19 citations), introduces an efficient approach to mobile sensor localization that leverages particle filters and Kullback-Leibler Distance (KLD) sampling. This technique significantly accelerates localization time execution, enabling mobile sensors to effectively explore and map previously unknown environments. Trisnawan’s contributions are particularly valuable in the field of autonomous systems, where real-time, adaptive navigation is critical. By improving the computational efficiency of Monte Carlo localization methods, his work supports the development of more responsive and reliable mobile robots and sensor platforms. His research addresses key challenges in simultaneous localization and mapping (SLAM), offering practical solutions for environments with limited prior information. Trisnawan’s work continues to influence advancements in autonomous navigation, making him a notable figure in the robotics and sensor systems community.