John Noonan

Tokyo Institute of Technology, Technion – Israel Institute of Technology

Papers

Total Citations

H-Index

About

John Noonan’s research centers on vision-based indoor positioning for robotic vehicles, leveraging floorplan knowledge to achieve robust localization without dense 3D maps or prior environment exploration. His major contributions include developing monocular camera systems that extract initial geometry from building floorplans, enabling robots to determine their pose using only a single camera and known architectural layouts. In his 2018 paper, “Vision-Based Indoor Positioning of a Robotic Vehicle with a Floorplan,” he demonstrated a system that uses floorplan geometry to guide a small vehicle’s localization, while his 2019 follow-up, “Global Monocular Indoor Positioning of a Robotic Vehicle with a Floorplan,” extended this to global positioning from a known start, eliminating dependence on scene consistency or pre-exploration. Though each of these works has garnered 6 citations, their impact lies in advancing practical, low-cost solutions for indoor robotics—critical for applications in logistics, inspection, and autonomous navigation. Noonan’s work stands out for its minimalist approach, reducing reliance on expensive sensors or extensive mapping, and offers a scalable path for robots to navigate unfamiliar indoor environments with just a camera and a blueprint.