Papers
16
Total Citations
329
H-Index
10
About
Bertrand Douillard is a leading roboticist whose research spans autonomous navigation, perception, and human-robot collaboration, with a particular focus on challenging outdoor and underwater environments. His most impactful work centers on developing robust perception systems that enable robots to understand and operate in complex, unstructured settings. Douillard's contributions include pioneering the use of conditional random fields for outdoor object mapping, a method that significantly advanced scene understanding by jointly classifying laser data. He also developed self-supervised radar-vision systems for ground segmentation, allowing autonomous vehicles to adapt to natural terrains without manual labeling. A key achievement was his role in Team RoboSimian's 5th-place finish at the 2015 DARPA Robotics Challenge, where his work on semi-autonomous mobile manipulation demonstrated practical supervised autonomy in disaster response scenarios. With over 290 citations across his top papers, Douillard's influence extends to underwater robotics, where he contributed to benthic monitoring and 3D mapping for Australia's Integrated Marine Observing System. His recent work on behavior prediction for autonomous driving continues to push boundaries, making him a versatile figure in modern robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Laser and Vision Based Outdoor Object Mapping48 citations · 2008
- 3
- 4Visual ground segmentation by radar supervision25 citations · 2012
- 5
- 6
- 7Multi-level State Estimation in an Outdoor Decentralised Sensor Network19 citations · 2008
- 8
- 9Out-of-Core Efficient Blending for Underwater Georeferenced Textured 3D Maps16 citations · 2013
- 10