This repository was archived by the owner on Apr 24, 2023. It is now read-only.
Add design doc for actual_arrel_segmentationn issue #569#602
Open
Add design doc for actual_arrel_segmentationn issue #569#602
Conversation
oswinso
approved these changes
Nov 21, 2019
Contributor
oswinso
left a comment
oswinso
left a comment
There was a problem hiding this comment.
I'd like a bit more detail with regards to how the clustering algorithms would work.
Comment on lines
14
to
16
| - Use the clustering algorithm inside PCL. | ||
| - (If necessary)Program a clustering algorithm that take in a pointcloud and returns a clustered pointcloud. | ||
| - Both clustering algorithm is based on the same general idea. You pick a point in a pointcloud and get all the point within a certain radius. Repeat the last process recursively with all the points inside the radius are processed. This finish the segmentation of a cluster. After this, you pick another point and repeat this process. |
Contributor
There was a problem hiding this comment.
I think you should describe the actual clustering algorithm(s) that you are thinking of using a bit more.
oswinso
suggested changes
Nov 21, 2019
Contributor
oswinso
left a comment
oswinso
left a comment
There was a problem hiding this comment.
Woops meant to say request changes
oswinso
suggested changes
Nov 21, 2019
Contributor
oswinso
left a comment
oswinso
left a comment
There was a problem hiding this comment.
One more small thing. Check the github render to see the formatting issues.
Comment on lines
17
to
27
| ''' | ||
| 1. create a Kd-tree representation for the input point cloud dataset P; | ||
| 2. set up an empty list of clusters C, and a queue of the points that need to be checked Q; | ||
| 3. then for every point pi in P, perform the following steps: | ||
| - add pi to the current queue Q; | ||
| - for every point pi in Q do: | ||
| - search for the set P^i_k of point neighbors of pi in a sphere with radius r < dth; | ||
| - for every neighbor pki in P^k_i, check if the point has already been processed, and if not add it to Q; | ||
| when the list of all points in Q has been processed, add Q to the list of clusters C, and reset Q to an empty list | ||
| 4. the algorithm terminates when all points \boldsymbol{p}_i \in P have been processed and are now part of the list of point clusters C | ||
| ''' |
Contributor
There was a problem hiding this comment.
I don't think this is displaying properly in markdown.
added 3 commits
November 21, 2019 19:30
oswinso
suggested changes
Nov 28, 2019
Contributor
oswinso
left a comment
oswinso
left a comment
There was a problem hiding this comment.
I think you meant to put these changes on a different branch.
Comment on lines
1
to
44
| #include <ros/ros.h> | ||
| #include <pcl/PointIndices.h> | ||
| #include <pcl/segmentation/extract_clusters.h> | ||
|
|
||
| ros::Publisher pub; | ||
| std::string pub_topic = ""; | ||
| std::string sub_topic = ""; | ||
|
|
||
| double clusterTolerance; | ||
| int minClusterSize; | ||
| int maxClusterSize; | ||
|
|
||
| void clusteringCallBack(pcl::PointCloud<pcl::PointXYZ>::Ptr pointcloud) { | ||
| pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>); | ||
| tree->setInputCloud (pointcloud); | ||
|
|
||
| std::vector<pcl::PointIndices> cluster_indices; | ||
| pcl::EuclideanClusterExtraction<pcl::PointXYZ> ec; | ||
| ec.setClusterTolerance (clusterTolerance); | ||
| ec.setMinClusterSize (minClusterSize); | ||
| ec.setMaxClusterSize (maxClusterSize); | ||
| ec.setSearchMethod (tree); | ||
| ec.setInputCloud (pointcloud); | ||
| ec.extract (cluster_indices); | ||
|
|
||
| pub.publish(cluster_indices); | ||
| } | ||
|
|
||
| int main(int argc, char** argv) | ||
| { | ||
| ros::init(argc, argv, "week5"); | ||
|
|
||
| ros::NodeHandle nh; | ||
|
|
||
| ros::NodeHandle pnh{"~"}; | ||
| pnh.getParam("clusterTolerance", clusterTolerance); | ||
| pnh.getParam("minClusterSize", minClusterSize); | ||
| pnh.getParam("maxClusterSize", maxClusterSize); | ||
|
|
||
| pub = nh.advertise<std::vector<pcl::PointIndices>>(pub_topic, 1); | ||
| ros::Subscriber pointcloud_sub = nh.subscribe(sub_topic, 1, clusteringCallBack); | ||
|
|
||
| ros::spin(); | ||
| } No newline at end of file |
Contributor
There was a problem hiding this comment.
These changes should be put in a separate branch, not this one.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Add design doc for actual_arrel_segmentationn issue #569
Link to design document