Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
Messages
Services
Plugins
Recent questions tagged autoware_euclidean_cluster_object_detector at Robotics Stack Exchange
Package Summary
Tags | No category tags. |
Version | 0.0.0 |
License | Apache License 2.0 |
Build type | AMENT_CMAKE |
Use | RECOMMENDED |
Repository Summary
Checkout URI | https://github.com/autowarefoundation/autoware_core.git |
VCS Type | git |
VCS Version | main |
Last Updated | 2025-06-12 |
Dev Status | DEVELOPED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Yukihiro Saito
- Dai Nguyen
Authors
autoware_euclidean_cluster_object_detector
Purpose
autoware_euclidean_cluster_object_detector is a package for clustering points into smaller parts to classify objects.
This package has two clustering methods: euclidean_cluster
and voxel_grid_based_euclidean_cluster
.
Inner-workings / Algorithms
euclidean_cluster
pcl::EuclideanClusterExtraction
is applied to points. See official document for details.
voxel_grid_based_euclidean_cluster
- A centroid in each voxel is calculated by
pcl::VoxelGrid
. - The centroids are clustered by
pcl::EuclideanClusterExtraction
. - The input points are clustered based on the clustered centroids.
Inputs / Outputs
Input
Name | Type | Description |
---|---|---|
input |
sensor_msgs::msg::PointCloud2 |
input pointcloud |
Output
Name | Type | Description |
---|---|---|
output |
autoware_perception_msgs::msg::DetectedObjects |
detected objects |
debug/clusters |
sensor_msgs::msg::PointCloud2 |
colored cluster pointcloud for visualization |
Parameters
Core Parameters
euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_grid_based_euclidean_cluster
Name | Type | Description |
---|---|---|
use_height |
bool | use point.z for clustering |
min_cluster_size |
int | the minimum number of points that a cluster needs to contain in order to be considered valid |
max_cluster_size |
int | the maximum number of points that a cluster needs to contain in order to be considered valid |
tolerance |
float | the spatial cluster tolerance as a measure in the L2 Euclidean space |
voxel_leaf_size |
float | the voxel leaf size of x and y |
min_points_number_per_voxel |
int | the minimum number of points for a voxel |
Assumptions / Known limits
(Optional) Error detection and handling
(Optional) Performance characterization
(Optional) References/External links
(Optional) Future extensions / Unimplemented parts
File truncated at 100 lines see the full file
Wiki Tutorials
Package Dependencies
System Dependencies
Name |
---|
libpcl-all-dev |
Dependant Packages
Launch files
- launch/euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]
- launch/voxel_grid_based_euclidean_cluster.launch.xml
-
- input_pointcloud [default: /sensing/lidar/top/pointcloud_raw]
- input_map [default: /map/pointcloud_map]
- output_clusters [default: clusters]
- use_low_height_cropbox [default: false]
- voxel_grid_based_euclidean_param_path [default: $(find-pkg-share autoware_euclidean_cluster_object_detector)/config/voxel_grid_based_euclidean_cluster.param.yaml]
- use_pointcloud_container [default: false]
- pointcloud_container_name [default: pointcloud_container]