Papers
1
Total Citations
6
H-Index
1
About
Olivier Antoni is a researcher focused on advancing real-time perception for autonomous vehicles, with a particular emphasis on sensor fusion and environment modeling. His key research areas include occupancy grid mapping, vehicle detection, and the performance optimization of perception algorithms for self-driving systems. Antoni’s most notable contribution is his comparative study of five vehicle detection methods on occupancy grid maps, a foundational work that systematically evaluates trade-offs between accuracy and real-time performance—a critical challenge for autonomous navigation. This paper, published in 2023, has already garnered 6 citations, signaling its growing influence in the field. By addressing how different range sensor technologies can be fused into a unified grid representation, Antoni’s work helps bridge the gap between theoretical detection algorithms and practical deployment in autonomous vehicles. His research is particularly valuable for students and engineers seeking to understand which detectors are best suited for real-time constraints, making his contributions both immediately applicable and forward-looking in the rapidly evolving domain of autonomous driving.
Research Focus
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Top Papers
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