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About

Marius Juston is an emerging researcher whose work sits at the intersection of autonomous robotics, adaptive filtering, and intelligent control systems. His research focuses primarily on GPS-denied localization using ultra-wideband (UWB) technology and the design of advanced fuzzy inference systems for real-world applications. Juston's most impactful contribution to date is his development of a Robust Error State Sage-Husa Adaptive Kalman Filter for UWB-based positioning, which extends prior adaptive filtering approaches into three-dimensional environments with improved noise estimation and interference resilience — already accumulating 7 citations since its 2025 publication. Complementing this, his work on ad hoc mesh network localization demonstrates practical UWB deployment for mobile robots operating without fixed infrastructure, addressing a significant gap in GPS-denied navigation research. Beyond localization, Juston has made notable strides in intelligent systems design, introducing a hierarchical rule-base reduction framework for ANFIS architectures optimized through deep deterministic policy gradient (DDPG) reinforcement learning — a novel fusion of fuzzy logic and modern machine learning that has attracted early scholarly attention. With a growing body of work spanning sensor fusion, adaptive estimation, and neuro-fuzzy optimization, Juston represents a promising voice in the robotics and intelligent systems research community.