EC-thor leverages Euclidean clustering to identify distinct groups of points in a points buffer, enabling efficient cone detection. The algorithm is tailored for the unique challenges of the autonomous system of a Formula Student car, specifically developed for BCNeMotorsport team.
- FEC: Fast Euclidean Clustering for Point Cloud Segmentation
- ikd-Tree: Incremental KD-Tree for Robotic Applications
- Adaptation to Point Net
- Modification
Acumulator.hpp
- Parallelization of some functions