Jennifer Treanor

Papers

Total Citations

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About

Dr. Jennifer Treanor’s research lies at the intersection of autonomous robotics, sensor-limited navigation, and computational geometry. Her most cited work, “Robotic Path Planning and Visibility with Limited Sensor Data” (2007, 19 citations), introduces a novel implementation of an environment-mapping algorithm grounded in Essentially Non-oscillatory (ENO) methods. This contribution addresses a fundamental challenge in robotics: how an autonomous agent equipped only with range sensors can discover and navigate an initially unknown environment. By integrating visibility analysis with sparse sensor data, Treanor’s approach enables more efficient path planning under real-world constraints, where complete environmental information is unavailable. Her work has influenced subsequent studies in robotic exploration, sensor fusion, and adaptive mapping, providing a practical framework for systems operating in uncertain terrains. Though her citation count reflects a focused, early-career impact, the methodological innovation—applying ENO techniques from numerical analysis to robotic perception—demonstrates cross-disciplinary thinking. Treanor’s research remains relevant for engineers and computer scientists developing autonomous systems for search-and-rescue, planetary exploration, or industrial inspection, where limited sensing and unpredictable environments are the norm.