Risanuri Hidayat

Papers

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About

Risanuri Hidayat is a researcher whose work bridges image processing and mobile robotics, with a particular focus on practical, real-world applications. His key research areas include image compression techniques and autonomous robot navigation, where he has made notable contributions to solving fundamental engineering challenges. Hidayat’s most cited work, “Compression Ratio and Peak Signal to Noise Ratio in Grayscale Image Compression using Wavelet” (2011), has garnered 18 citations and explores the critical trade-off between compression efficiency and image quality—a cornerstone issue in multimedia systems. This research addresses the exponential growth of digital data by optimizing wavelet-based compression methods. In mobile robotics, Hidayat’s 2018 paper on “Omnidirectional Sensing for Escaping Local Minimum on Potential Field Mobile Robot Path Planning in Corridors Environment” (3 citations) tackles a persistent problem in autonomous navigation: the tendency of potential field algorithms to trap robots in local minima within confined spaces like corridors. By integrating omnidirectional sensing, his work enhances robot mobility and reliability in structured environments. Hidayat’s contributions demonstrate a commitment to advancing both theoretical understanding and practical solutions, making his research valuable for students and engineers working in image processing and intelligent robotics.