Daniel Dueri

University of Washington

Papers

1

Total Citations

46

H-Index

1

About

Daniel Dueri is a leading researcher in autonomous systems, with a primary focus on real-time motion planning and control for agile aerial robots. His work addresses the fundamental challenge of enabling quadrotors to perform aggressive maneuvers while avoiding obstacles, a problem that is inherently non-convex and computationally demanding. Dueri’s major contribution lies in the application of lossless and successive convexification techniques, which transform these complex, non-convex problems into solvable convex optimization forms. This breakthrough allows for real-time, on-board computation, making it possible for drones to react dynamically to their environment without relying on pre-computed paths or off-board processing. His seminal 2017 paper on this topic has garnered 46 citations, underscoring its influence in the field of robotics and control. By bridging the gap between theoretical optimization and practical, on-board implementation, Dueri’s work has paved the way for more autonomous, responsive, and safer aerial vehicles, with direct applications in search-and-rescue, inspection, and high-speed drone racing.

Research Focus

Key Achievements

1
H-Index
1
Papers
46
Total Citations
46
Avg Citations/Paper
🏆 Most Cited Paper
Convexification and real-time on-board optimization for agile quad-rotor maneuvering and obstacle avoidance
46 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Washington

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago