Classes | |
class | DiscreteCell |
class | NDTMap |
class | NormalDistribution |
class | OccupancyGrid |
Functions | |
Optional[NormalDistribution] | fit_normal_distribution (np.ndarray points, float min_variance=5e-3) |
np.ndarray | grid_to_point_cloud (OccupancyGrid occupancy_grid) |
NDTMap | point_cloud_to_ndt (np.ndarray pc, cell_size=1.0) |
Variables | |
frozen | |
message | |
Optional[NormalDistribution] beluga_ros.conversion_utils.fit_normal_distribution | ( | np.ndarray | points, |
float | min_variance = 5e-3 |
||
) |
Fit a normal distribution to a set of 2D points. A minimum variance in each dimension will be enforced to avoid singularities.
Definition at line 244 of file conversion_utils.py.
np.ndarray beluga_ros.conversion_utils.grid_to_point_cloud | ( | OccupancyGrid | occupancy_grid | ) |
Convert an OccupancyGrid's occupied cells to a 2D point cloud. Uses the center of the cell for the conversion to reduce max error.
Definition at line 225 of file conversion_utils.py.
NDTMap beluga_ros.conversion_utils.point_cloud_to_ndt | ( | np.ndarray | pc, |
cell_size = 1.0 |
|||
) |
Convert a 2D point cloud into a NDT map representation. Does so by clustering points in 2D cells of {cell_size} * {cell_size} meters^2 and fitting a normal distribution when applicable.
Definition at line 269 of file conversion_utils.py.
beluga_ros.conversion_utils.frozen |
Definition at line 34 of file conversion_utils.py.
beluga_ros.conversion_utils.message |
Definition at line 29 of file conversion_utils.py.