Nabil Shaukat

Papers

Total Citations

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About

Nabil Shaukat is pioneering the frontier of autonomous robotics for critical infrastructure inspection, with a focused expertise in miniature robotic systems, confined-space navigation, and TinyML (Tiny Machine Learning). His major contributions lie in developing resource-efficient, intelligent robots capable of operating in the most challenging environments—small-diameter sewer pipes and other confined spaces. Shaukat’s work on the "Mega-Joey" robot platform represents a breakthrough: a tether-less, autonomous miniature robot designed for collaborative, in-pipe infrastructure assessment, directly addressing the high costs and disruptions of traditional sewer inspection in the UK. Complementing this, his research on "TinyML-Based In-Pipe Feature Detection" introduces a novel, low-power machine learning method that enables these miniature robots to recognize key pipeline features in real time, a critical capability for autonomous navigation. With his most cited works accumulating citations in 2025, Shaukat’s impact is rapidly growing, establishing him as a key innovator in applying edge AI to practical, real-world robotics. His achievements promise to make infrastructure maintenance safer, cheaper, and more efficient.