Publications by authors named "Tiana Rakotovao"
Occupancy grid maps are widely used as an environment model that allows the fusion of different range sensor technologies in real-time for robotics applications. In an autonomous vehicle setting, occupancy grid maps are especially useful for their ability to accurately represent the position of surrounding obstacles while being robust to discrepancies between the fused sensors through the use of occupancy probabilities representing uncertainty. In this article, we propose to evaluate the applicability of real-time vehicle detection on occupancy grid maps.
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- Environment perception is essential for safely navigating vehicles, robots, and even humans in low-visibility situations by detecting obstacles around them.
- Obstacle avoidance systems usually combine various sensors like LiDAR, radar, and ultrasound to work under different conditions, but they often require significant computing power, making them suitable mostly for advanced vehicles and robots.
- INSPEX aims to develop a lightweight and low-power environment perception system that can be integrated into portable or wearable devices, such as a white cane, by miniaturizing existing sensors and utilizing data fusion techniques for effective obstacle detection.