N. Harper

Papers

Total Citations

H-Index

About

N. Harper’s research lies at the intersection of robotics, sensor technology, and bio-inspired perception, with a core focus on enabling mobile robots to recognize and interact with natural environments. Her major contribution is pioneering the use of Continuous Tone Frequency Modulation (CTFM) ultrasonic range data—a technology originally developed for mobility aids for the visually impaired—as a novel sensor modality for plant recognition in autonomous navigation. By applying artificial neural networks (ANNs) to classify plant species from ultrasonic echoes, Harper demonstrated that plants could serve as reliable, natural landmarks for robot localization, addressing key challenges such as plant similarity and rotational asymmetry. Her most cited work, “Classification of plant species from CTFM ultrasonic range data using a neural network” (2002, 15 citations), established a foundational method for non-visual plant sensing, while her subsequent papers refined the approach for real-world mobile robot deployment. Though her citation counts are modest, Harper’s work is notable for its creative cross-domain transfer—adapting assistive technology for robotics—and its early recognition of the importance of ecological perception in autonomous systems. Her research remains a touchstone for engineers exploring ultrasonic sensing in unstructured, plant-rich environments.