Roxane Vimbert
Papers
1
Total Citations
3
H-Index
1
About
Roxane Vimbert is a researcher at the intersection of bio-inspired robotics and autonomous navigation, specializing in vision-based route following for mobile robots in GNSS-denied environments such as urban canyons and indoor spaces. Her most cited work, "Antcar: Tâche simple de suivi d'itinéraire avec une vision et un modèle neuronal inspirés des fourmis" (2023, 3 citations), introduces a novel method that leverages a biologically constrained neural model inspired by ant navigation to assess the familiarity of panoramas. This approach enables robots to follow routes without relying on satellite signals, mimicking the remarkable wayfinding abilities of desert ants. Vimbert’s contributions are notable for bridging computational neuroscience and practical robotics, offering a robust, low-cost alternative to traditional GPS-based systems. Her work has implications for autonomous vehicles, search-and-rescue missions, and exploration in challenging terrains. With a focus on simplicity and biological plausibility, Vimbert continues to push the boundaries of how robots perceive and navigate their environments, making her a rising figure in bio-inspired robotics.
Research Focus
Key Achievements
Top Papers
- 1