Local Mapping algorithm for LiDAR sensor and monocular camera.
The algorithm is as follows:
- The ground plane is removed from the LiDAR point cloud using RANSAC.
- The outlier points (not on the ground plane) are clustered using DBSCAN.
- On the camera image, a bounding box is cropped for each detected cone of the point cloud,, by knowing the LiDAR resolution and the camera model.
- The cone is classified by its class (or as a "not cone") by a simple convolutional neural network.
- For each cone classified, associate its class to the previous detected position.
/pointcloud
(sensor_msgs/PointCloud2
)/image
(sensor_msgs/Image
)/camera_info
(sensor_msgs/CameraInfo
)
/cones
(lart_msgs/ConeArray
)
base_link
->lidar_link
base_link
->camera_link
- ROS Humble
- CMake
- C++ compiler
- Open3D
- LibTorch
- lart_msgs