Ryan Close

United States Army Combat Capabilities Development Command, United States Army

Papers

Total Citations

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About

Ryan Close is a researcher focused on advancing perception and autonomy for ground vehicles, with a particular emphasis on sensor fusion and object detection in challenging environments. His work primarily addresses the critical problem of detecting partially obscured objects—a capability essential for safe, high-speed autonomous navigation in both civilian and military contexts. Close’s most cited paper, “Fusion of lidar and radar for detection of partially obscured objects” (23 citations), demonstrates his key contribution: combining LiDAR and radar data to overcome the limitations of individual sensors, enabling robots to perceive hazards hidden behind foliage or other obstacles. He has also explored resolving ranges of layered objects, such as tree canopies over forest floors, and the use of ground-vehicle LADAR for standoff detection of roadside hazards. Notably, his research on sensor suites for high-speed autonomous operations addresses a major barrier to the adoption of robotic systems—slow operational speed—by identifying sensor configurations that maintain reliability at greater velocities. Close’s work directly supports the development of more robust, field-ready autonomous vehicles capable of navigating complex, real-world terrain.