Priya Narayanan

K Lab (United States), United States Naval Research Laboratory

Papers

Total Citations

H-Index

About

Priya Narayanan is a robotics researcher whose work lies at the intersection of visual perception and autonomous systems. Her research focuses on enabling robots to operate reliably in unstructured, real-world environments—a critical challenge for field robotics. Narayanan’s most cited work, “An integrated perception pipeline for robot mission execution in unstructured environments” (6 citations), was developed as part of the prestigious Robotics Collaborative Technology Alliance (RCTA) program. This paper presents a comprehensive framework for object identification and localization, directly addressing the safety and success of autonomous task execution. In her earlier work, “Impact of embodied training on object recognition” (3 citations), Narayanan explored a novel approach to robot learning by combining Convolutional Neural Networks with human-assisted training. This study demonstrated how interactive, embodied teaching can improve a robot’s ability to recognize novel objects with precision. While her citation counts are modest, her contributions are notable for their practical focus on perception pipelines that bridge the gap between laboratory research and real-world deployment. Narayanan’s work is particularly relevant for students and researchers interested in the integration of computer vision, machine learning, and robotics for autonomous mission execution.