Carlo Alberto Pascucci

University of Washington

Papers

1

Total Citations

46

H-Index

1

About

Carlo Alberto Pascucci is a leading researcher in autonomous aerial robotics, with a core focus on real-time motion planning, nonlinear control, and convex optimization for agile quadrotor systems. His most influential work, "Convexification and real-time on-board optimization for agile quad-rotor maneuvering and obstacle avoidance" (2017, 46 citations), introduced a groundbreaking framework that applies lossless and successive convexification techniques to transform the inherently non-convex problem of constrained quadrotor navigation into a tractable, real-time solvable optimization. This contribution has been pivotal in enabling high-speed, obstacle-aware flight with on-board computational efficiency, directly advancing the state of the art in autonomous drone agility and safety. Pascucci’s research bridges theoretical optimization with practical deployment, demonstrating that complex nonlinear dynamics can be reliably handled in milliseconds on embedded hardware. His work is widely cited by both academic and industrial groups developing next-generation aerial vehicles, and he is recognized for making convex optimization a practical tool for aggressive maneuvering in cluttered environments.

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