Guillaume Duceux
Papers
2
Total Citations
5
H-Index
2
About
Guillaume Duceux is a robotics researcher whose work centers on autonomous mobile robot navigation, perception, and environmental understanding. His key research areas include software architecture for exploration robots, semantic mapping, and the detection and modeling of dynamic obstacles in real-world environments. Duceux's most notable contribution is the development of a software architecture for an exploration robot under the Panoramic and Active Camera for Object Mapping (PACOM) project, which aimed to enable robots to autonomously explore unknown indoor spaces and build high-level semantic maps. This work, published in 2011, has garnered 3 citations and laid foundational principles for integrating perception and navigation in unstructured settings. Additionally, his 2014 study on unsupervised, online non-stationary obstacle discovery using laser range finders (2 citations) advanced the field by addressing a critical limitation of traditional mapping methods—their inability to handle dynamic environments. By proposing a system that identifies and models moving objects without prior training, Duceux contributed to making robots more adaptive and context-aware. His research is particularly valuable for students and engineers working on autonomous systems, offering practical insights into real-time perception and robust navigation in changing surroundings.
Research Focus
Key Achievements
Top Papers
- 1Software architecture for an exploration robot based on Urbi3 citations · 2011
- 2