Risang Yudanto

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About

Risang Yudanto is a researcher whose work sits at the intersection of robotics, sensor fusion, and industrial automation, with a particular focus on enabling precise navigation in challenging indoor environments. His most influential contribution, the 2015 paper "Sensor fusion for indoor navigation and tracking of automated guided vehicles," has garnered 32 citations and presents a novel approach that integrates a wireless Ultra-Wideband (UWB) Indoor Positioning System with an Inertial Navigation System (INS). This fusion technique is critical for real-time tracking of Automated Guided Vehicles (AGVs) and mobile robots in factories and warehouses, addressing a key bottleneck in modern logistics and manufacturing. Yudanto further advanced the field by developing automatic mitigation methods for compensating drifts in low-cost Inertial Measurement Units (IMUs), as detailed in his 2015 work on online trajectory estimation for moving robot arms. This research, which has earned 6 citations, demonstrates his commitment to making high-performance navigation accessible by improving the reliability of inexpensive MEMS-based sensors. Through these contributions, Yudanto has helped bridge the gap between theoretical sensor fusion algorithms and practical, real-world industrial applications.