Olivier J. N. Bertrand
Papers
6
Total Citations
136
H-Index
5
About
Olivier J. N. Bertrand is a leading researcher in bioinspired robotics and neuromorphic vision, whose work bridges the gap between insect neurobiology and autonomous navigation. His core research focuses on developing computational models of motion detection and collision avoidance, drawing inspiration from how bees and flies process optic flow. Bertrand’s most influential contribution is the "Spiking Elementary Motion Detector in Neuromorphic Systems" (2018, 46 citations), which introduced a neural architecture for event-driven vision that enables robots to navigate cluttered environments with insect-like efficiency. His earlier work on a "Bioinspired event-driven collision avoidance algorithm" (2015, 36 citations) demonstrated how separating translational and rotational optic flow components allows mobile agents to estimate obstacle proximity—a principle now foundational in neuromorphic robotics. More recently, his 2024 study "Finding the gap" (21 citations) tackles the challenge of dense-terrain navigation, proposing models for how animals cross narrow passages while maintaining course control. Bertrand’s research consistently emphasizes real-world applicability, from hexapod walking robots to skyline-based homing strategies. His work has been instrumental in advancing energy-efficient, event-driven sensing systems for autonomous agents, with cumulative citations exceeding 130.
Research Focus
Key Achievements
Top Papers
- 1Spiking Elementary Motion Detector in Neuromorphic Systems46 citations · 2018
- 2Bioinspired event-driven collision avoidance algorithm based on optic flow36 citations · 2015
- 3Finding the gap: neuromorphic motion-vision in dense environments21 citations · 2024
- 4The problem of home choice in skyline-based homing17 citations · 2018
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