Papers
24
Total Citations
2,079
H-Index
18
About
Jeffrey Delmerico is a prominent robotics researcher whose work spans autonomous aerial systems, visual-inertial state estimation, and human-robot interaction. He has made foundational contributions to the field of flying robots, most notably through his highly cited benchmark comparison of monocular visual-inertial odometry algorithms (395 citations), which has become an essential reference for researchers designing state estimation systems under real-world computational constraints. His work on fast, autonomous flight in GPS-denied environments (196 citations) and vision-based quadrotor landing on moving platforms (193 citations) has significantly advanced the practical deployment of autonomous aerial vehicles. Delmerico has also shaped the field of rescue robotics, co-authoring a widely read survey on the current state and future of disaster-response robotics (361 citations). His contributions extend to active 3D reconstruction, where he developed information-gain frameworks for next-best view planning, and to semantic volumetric mapping for dynamic environments. More recently, his research has explored mixed reality and spatial computing as interfaces for intuitive human-robot interaction. With thousands of citations across diverse topics, Delmerico's research consistently bridges theoretical rigor with real-world robotic application.
Research Focus
Key Achievements
Top Papers
- 1
- 2The current state and future outlook of rescue robotics361 citations · 2019
- 3Fast, autonomous flight in GPS‐denied and cluttered environments196 citations · 2017
- 4Vision-based autonomous quadrotor landing on a moving platform193 citations · 2017
- 5
- 6An information gain formulation for active volumetric 3D reconstruction152 citations · 2016
- 7Active Autonomous Aerial Exploration for Ground Robot Path Planning142 citations · 2017
- 8
- 9Toward Domain Independence for Learning-Based Monocular Depth Estimation69 citations · 2017
- 10