Papers
2
Total Citations
102
H-Index
2
About
Bryan Penin specializes in trajectory planning and vision-based control for agile robotic systems, with a focus on quadrotor UAVs operating under challenging sensing constraints. His major contributions lie in developing minimum-time trajectory generation methods that explicitly account for intermittent measurements and limited sensor fields of view. In his 2018 work on "Minimum-Time Trajectory Planning Under Intermittent Measurements" (52 citations), Penin introduced robust path planning that incorporates state uncertainty and collision probability when exteroceptive cues like vision are unreliable. His 2017 paper on "Vision-based minimum-time trajectory generation for a quadrotor UAV" (50 citations) pioneered aggressive flight control by guaranteeing feature visibility within a camera’s limited field of view, enabling high-speed maneuvers without losing tracking. These contributions have advanced autonomous drone capabilities in inspection, search-and-rescue, and dynamic environments. Penin’s work is notable for bridging theoretical optimal control with practical sensor limitations, making him a key figure in robust, vision-guided aerial robotics.
Research Focus
Key Achievements
Top Papers
- 1Minimum-Time Trajectory Planning Under Intermittent Measurements52 citations · 2018
- 2Vision-based minimum-time trajectory generation for a quadrotor UAV50 citations · 2017