Dominique Gruyer
Groupe d’Étude de la Matière Condensée, Institut Lavoisier de Versailles
Papers
7
Total Citations
390
H-Index
6
About
Dominique Gruyer is a leading researcher in autonomous driving and mobile robotics, whose work has fundamentally advanced the safety and reliability of intelligent vehicle navigation. His primary research areas span path planning, multi-sensor perception, and high-level decision-making for autonomous systems. Gruyer’s most impactful contribution is his modified artificial potential field method for online path planning, which overcomes the critical local minima problem that plagued standard approaches—a breakthrough cited over 177 times. He has also made seminal contributions to autonomous driving architectures, authoring a highly-cited 2017 review on perception and information processing (119 citations) that serves as a foundational reference for the field. His work on safe path planning under localization uncertainties and multi-sensor fusion, including innovative combinations of stereovision and laser scanners, has been instrumental in developing robust obstacle detection and ego-localization systems. Gruyer’s research consistently addresses real-world challenges, from highway decision-making to unmapped object detection, making him a pivotal figure in the transition from theoretical autonomous systems to practical, road-ready applications.
Research Focus
Key Achievements
Top Papers
- 1Modified artificial potential field method for online path planning applications177 citations · 2017
- 2
- 3Safe path planning in an uncertain-configuration space49 citations · 2004
- 4
- 5Obstacle Detection Based on Fusion Between Stereovision and 2D Laser Scanner11 citations · 2007
- 6
- 7Safe path planning and replanning with unmapped objects detection4 citations · 2003