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fix pcl version 1.10 compatibility with ndt #190

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merged 3 commits into from
Dec 14, 2021
Merged

fix pcl version 1.10 compatibility with ndt #190

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cba0149
fix pcl version 1.10 compatibility with ndt
Dec 13, 2021
c85e754
Add clarifying comment
Dec 14, 2021
b09f9ec
Address PR comments
Dec 14, 2021
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27 changes: 21 additions & 6 deletions core_perception/lidar_localizer/nodes/ndt_matching/ndt_matching.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -130,8 +130,9 @@ static pcl_omp::NormalDistributionsTransform<pcl::PointXYZ, pcl::PointXYZ> omp_n
static int max_iter = 30; // Maximum iterations
static float ndt_res = 1.0; // Resolution
static double step_size = 0.1; // Step size
static double trans_eps = 0.01; // Transformation epsilon

static double trans_eps = 0.001; // Transformation epsilon. In PCLv1.10 (ros noetic) this value is squared error not base epsilon
// NOTE: A value of 0.0001 can work as well.
// This will increase the required iteration count (and therefore execution time) but might increase performance
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Just to clarify, the mentioned performance here is in terms of accuracy? So the tradeoff is speed vs accuracy?

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Yeah, I'll clarify

static ros::Publisher predict_pose_pub;
static geometry_msgs::PoseStamped predict_pose_msg;

Expand Down Expand Up @@ -322,18 +323,27 @@ static void param_callback(const autoware_config_msgs::ConfigNDT::ConstPtr& inpu
if (input->trans_epsilon != trans_eps)
{
trans_eps = input->trans_epsilon;
double rot_threshold = 1.0 - trans_eps;


if (_method_type == MethodType::PCL_GENERIC)
if (_method_type == MethodType::PCL_GENERIC) {
ROS_INFO_STREAM("Using tramslation threshold of " << trans_eps);
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Typo? tramslation

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Fixed

ROS_INFO_STREAM("Using rotation threshold of " << rot_threshold);
ndt.setTransformationEpsilon(trans_eps);
else if (_method_type == MethodType::PCL_ANH)
ndt.setTransformationRotationEpsilon(rot_threshold);
}
else if (_method_type == MethodType::PCL_ANH) {
anh_ndt.setTransformationEpsilon(trans_eps);
}
#ifdef CUDA_FOUND
else if (_method_type == MethodType::PCL_ANH_GPU)
else if (_method_type == MethodType::PCL_ANH_GPU) {
anh_gpu_ndt_ptr->setTransformationEpsilon(trans_eps);
}
#endif
#ifdef USE_PCL_OPENMP
else if (_method_type == MethodType::PCL_OPENMP)
else if (_method_type == MethodType::PCL_OPENMP) {
omp_ndt.setTransformationEpsilon(ndt_res);
}
#endif
}

Expand Down Expand Up @@ -460,16 +470,21 @@ static void map_callback(const sensor_msgs::PointCloud2::ConstPtr& input)

pcl::PointCloud<pcl::PointXYZ>::Ptr map_ptr(new pcl::PointCloud<pcl::PointXYZ>(map));

double rot_threshold = 1.0 - trans_eps;

// Setting point cloud to be aligned to.
if (_method_type == MethodType::PCL_GENERIC)
{
ROS_INFO_STREAM("Using tramslation threshold of " << trans_eps);
ROS_INFO_STREAM("Using rotation threshold of " << rot_threshold);
pcl::NormalDistributionsTransform<pcl::PointXYZ, pcl::PointXYZ> new_ndt;
pcl::PointCloud<pcl::PointXYZ>::Ptr output_cloud(new pcl::PointCloud<pcl::PointXYZ>);
new_ndt.setResolution(ndt_res);
new_ndt.setInputTarget(map_ptr);
new_ndt.setMaximumIterations(max_iter);
new_ndt.setStepSize(step_size);
new_ndt.setTransformationEpsilon(trans_eps);
new_ndt.setTransformationRotationEpsilon(rot_threshold);

new_ndt.align(*output_cloud, Eigen::Matrix4f::Identity());

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2 changes: 1 addition & 1 deletion docker/install.sh
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Expand Up @@ -25,4 +25,4 @@ echo "Build with CUDA"
sudo mkdir /opt/autoware.ai # Create install directory
sudo chown carma /opt/autoware.ai # Set owner to expose permissions for build
sudo chgrp carma /opt/autoware.ai # Set group to expose permissions for build
AUTOWARE_COMPILE_WITH_CUDA=1 colcon build --install-base /opt/autoware.ai/ros/install --executor sequential --cmake-args -DCMAKE_BUILD_TYPE=Release -DCMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs -DCMAKE_CXX_FLAGS=-Wall -DCMAKE_C_FLAGS=-Wall
AUTOWARE_COMPILE_WITH_CUDA=1 colcon build --install-base /opt/autoware.ai/ros/install --cmake-args -DCMAKE_BUILD_TYPE=Release -DCMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs -DCMAKE_CXX_FLAGS=-Wall -DCMAKE_C_FLAGS=-Wall