Nagavenkat Adurthi

University at Buffalo, State University of New York, University of Alabama in Huntsville

Papers

Total Citations

H-Index

About

Nagavenkat Adurthi is a researcher whose work lies at the intersection of sensor management, nonlinear estimation, and autonomous vehicle localization. His key research areas include optimal information collection for nonlinear systems and LIDAR-based localization for autonomous driving. In his highly cited 2013 paper, Adurthi tackled the fundamental challenge of optimally deploying active sensors to maximize information gain before measurements are taken—a critical problem for applications like multiple target tracking and localization. By leveraging mutual information as a performance metric, he provided a rigorous framework for characterizing sensor performance in real-time decision-making. His more recent 2023 work addresses a practical, industry-relevant challenge: developing a scan matching-based particle filter for LIDAR-only localization. This methodology enables autonomous vehicles to determine their global 3D pose using only a 3D LIDAR sensor and a known map, eliminating the need for GPS or other sensors. With 12 and 4 citations respectively, these papers demonstrate Adurthi’s ability to bridge theoretical optimal control with applied robotics, making his contributions valuable to both academic researchers and engineers developing next-generation autonomous systems.