Michael Burri

About

Michael Burri is a leading researcher in aerial robotics, whose work has fundamentally advanced the autonomy of micro aerial vehicles (MAVs) and drones. His primary research areas encompass real-time state estimation, trajectory optimization, and autonomous inspection path planning. Burri’s major contributions include the development of a synchronized visual-inertial sensor system with FPGA pre-processing, a cornerstone for accurate, real-time 6D pose estimation and SLAM in MAVs (cited over 270 times). He has also pioneered continuous-time trajectory optimization methods for online UAV replanning, enabling safe collision avoidance in unstructured environments (accumulating over 378 citations across two versions). For infrastructure inspection, Burri introduced novel viewpoint resampling and tour optimization algorithms, such as the iterative viewpoint resampling method for complex 3D structures (cited over 320 times) and the rapidly exploring random tree of trees (RRTOT) for incremental planning. His work on hybrid predictive control for aerial physical interaction has been pivotal for contact-based inspection operations. With over 1,400 total citations, Burri’s innovations are essential reading for any researcher or student aiming to push the boundaries of autonomous drone navigation and industrial inspection.

Research Focus

Key Achievements

Top Papers

1. 1
   A synchronized visual-inertial sensor system with FPGA pre-processing for accurate real-time SLAM

   270 citations · 2014
2. 2
   Continuous-time trajectory optimization for online UAV replanning

   247 citations · 2016
3. 3
   Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics

   206 citations · 2015
4. 4
   Three-dimensional coverage path planning via viewpoint resampling and tour optimization for aerial robots

   181 citations · 2015
5. 5
   Continuous-time trajectory optimization for online UAV replanning

   131 citations · 2016
6. 6
   Structural Inspection Path Planning via Iterative Viewpoint Resampling with Application to Aerial Robotics

   117 citations · 2015
7. 7
   Aerial robotic contact-based inspection: planning and control

   108 citations · 2015
8. 8
   Hybrid predictive control for aerial robotic physical interaction towards inspection operations

   74 citations · 2014
9. 9
   Visual industrial inspection using aerial robots

   57 citations · 2014
10. 10
    An incremental sampling-based approach to inspection planning: the rapidly exploring random tree of trees

    54 citations · 2016

Key Collaborators

Contact & Links