Papers
16
Total Citations
151
H-Index
8
About
Bruno Jouvencel is a leading figure in autonomous underwater and mobile robotics, with a career dedicated to solving the core challenges of perception, control, and navigation in complex, unstructured environments. His research spans three key areas: sensor selection and fusion, path planning and control for underwater vehicles, and reactive behavior for high-speed mobile robots. Jouvencel pioneered fuzzy-logic and geometric approaches for optimal sensor selection in data fusion, a foundational contribution that has garnered over 36 citations. He is also widely recognized for his work on autonomous underwater vehicles (AUVs), developing novel path-following and trajectory-tracking controllers for eel-like robots and pipeline inspection AUVs, with his 2011 paper on combined path following and trajectory tracking accumulating 25 citations. Notably, he led the design of the control architecture for the AUV Taipan, demonstrating his ability to translate theory into robust, real-world systems. His work on reactive collision avoidance for fast mobile robots (exceeding 5 m/s) in ill-structured environments further showcases his versatility, with multiple papers on sensor-based motion control and neural network approaches. With a strong record of high-impact publications and a focus on hardware-in-the-loop simulation for multi-vehicle cooperation, Jouvencel’s contributions continue to influence the next generation of intelligent, autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Sensor selection in a fusion process: a fuzzy approach18 citations · 2002
- 3Sensor selection: a geometrical approach18 citations · 2002
- 4Path following control for an eel-like robot14 citations · 2005
- 5A reactive control approach for pipeline inspection with an AUV14 citations · 2005
- 6
- 7
- 8
- 9Fast mobile robots in ill-structured environments6 citations · 2002
- 10Sensor-Based Motion Control for Fast Mobile Robots6 citations · 2005