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Increased version to 0.6.2

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Memory management tested on RGBD SLAM
Fixed some crashes
New parameter RGBD/LocalLoopDetectionMaxDiffID
New parameter LccIcp2/VoxelSize
Updated parameter LccIcp/Type (added "No ICP" type)
Updated parameter kLccBowMinInliers (inliers minimum reduced to 1)
TORO optimization: The graph root is explicitly defined as the last node added (fixed a TORO crash when a root could not be found)
TORO optimization: only one constraint between neighbors and loop closures
TORO optimization: added initial tree guess
Map correction/Map transform: now only used in localization mode (map correction is always identity on mapping mode)
New statistics: local loop space diff, last loop closure parent and child ids
Database: Fixed empty signatures with no poses loaded
ICP: fixed transform multiplication order
Dump memory: added 3D words
DatabaseViewer: added Export option (added ExportDialog object)
DataRecorder: Option recording in RAM or Hard drive
GUI: added a dock widget (MapVisibilityWidget) to change visibility of nodes in the 3D map
GUI: fixed progress bar step count when generating the map
Menu option: generate TORO graph (full/current map, optimized/not optimized)
Menu option: download map (full/current map, optimized/not optimized)
Preferences: added Reset all settings button
Preferences: A QGroupBox can be a boolean parameter

git-svn-id: http://rtabmap.googlecode.com/svn/trunk/rtabmap@1066 f169173b-cf89-36c8-b27e-44dbe73f0c83
This commit is contained in:
matlabbe
2014-01-22 19:49:28 +00:00
parent 2489397b49
commit 22e3082adc
33 changed files with 2103 additions and 857 deletions
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12
corelib/src/util3d.cpp
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@@ -1266,12 +1266,12 @@ int getCorrespondencesCount(const pcl::PointCloud<pcl::PointXYZ>::ConstPtr & clo
pcl::search::KdTree<pcl::PointXYZ>::Ptr kdTree(new pcl::search::KdTree<pcl::PointXYZ>);
kdTree->setInputCloud(cloud_target);
int count = 0;
float sqrdMaxDistance = maxDistance * maxDistance;
for(unsigned int i=0; i<cloud_source->size(); ++i)
{
std::vector<int> ind(1);
std::vector<float> dist(1);
kdTree->nearestKSearch(cloud_source->at(i), 1, ind, dist);
if(dist[0] < maxDistance)
if(kdTree->nearestKSearch(cloud_source->at(i), 1, ind, dist) && dist[0] < sqrdMaxDistance)
{
++count;
}
@@ -1545,16 +1545,22 @@ void optimizeTOROGraph(
return;
}
}
pg.buildMST(pg.vertices.begin()->first); // pg.buildSimpleTree();
pg.buildMST(pg.vertices.begin()->first);
UDEBUG("Initial guess...");
pg.initializeOnTree(); // optional
pg.initializeTreeParameters();
UDEBUG("Building TORO tree... (if a crash happens just after this msg, "
"TORO is not able to find the root of the graph!)");
pg.initializeOptimization();
UDEBUG("TORO iterate begin");
for (int i=0; i<toroIterations; i++)
{
pg.iterate();
}
UDEBUG("TORO iterate end");
optimizedPoses.clear();
for(std::map<int, Transform>::const_iterator iter = poses.begin(); iter!=poses.end(); ++iter)