Aravind Sundaresan

Papers

Total Citations

333

H-Index

About

Aravind Sundaresan is a pioneer in autonomous robotics, specializing in perception, navigation, and runtime verification for robots operating in unstructured environments. His work bridges the gap between real-time sensing and robust decision-making, with a focus on off-road and challenging terrain. Sundaresan’s contributions include developing a fast color/texture segmentation method for outdoor robots, enabling efficient online image clustering using a compact descriptor and K-means—a foundational tool for real-time scene understanding. His leadership in the DARPA Learning Applied to Ground Robots (LAGR) project resulted in a complete autonomous system for off-road navigation using stereo vision, demonstrating mapping, planning, and learning in unstructured settings. Sundaresan also advanced three-dimensional perception and motion planning through the “Leaving Flatland” project, which integrated comprehensive localization, mapping, and planning for the RHex robot, pushing the boundaries of autonomous action on rugged terrain. With over 333 citations across his top five papers, including the highly cited “ROSRV: Runtime Verification for Robots” (97 citations), Sundaresan’s work has profoundly impacted field robotics, earning recognition for its practical, real-world applications and its role in shaping autonomous systems for complex environments.