Michał Pełka michalpelka

Steps to create Textured Mesh from Point Cloud using Meshlab

Import the pointcloud file in ".ply" file format in Meshlab. Before importing make sure you do some pre-processing / cleaning on point cloud so as to ease the process of meshing.

Next we need to reduce the number of point samples for smooth meshing.
- So go to Filters -> Point Set -> Point Cloud Simplification. Enter Number of samples circa 5% of original number of points. Make sure Best Sample Heuristic is checked.
After point cloud simplification, make sure to select Simplified point cloud in the Show Layer Dialog on the right hand side. If not visible, it can be opened by navigating to View -> Show Layer Dialog. Now we need to compute normals for point set.
So go to Filters -> Point Set -> Compute normals for point sets . Enter Neighbour num between 10 - 100. Initially try with 10 and

sudo -s

apt-get purge *nvidia*
apt autoremove

ros2 Humble, ubuntu 22.04

Clone:

mkdir -p ~/husky_ws/src
cd ~/husky_ws/src
git clone https://github.com/husky/husky.git
cd husky

	#include <glob.h>
	#include <vector>
	#include <string>
	inline std::vector<std::string> glob(const std::string& pat){
	using namespace std;
	glob_t glob_result;
	glob(pat.c_str(),GLOB_TILDE,NULL,&glob_result);
	vector<string> ret;
	for(unsigned int i=0;i<glob_result.gl_pathc;++i){
	ret.push_back(string(glob_result.gl_pathv[i]));

	# docker build -t livox -f Dockerfile .
	# rocker --x11 --nvidia --network host livox

	# set host ip to 192.168.1.5
	# assume Livox ip is 192.168.1.177

	# inside container:
	# ping 192.168.1.177
	# vim /ws/src/livox_ros_driver2/config/MID360_config.json
	# screen -m bash -c '. /ws/devel/setup.sh && roslaunch /ws/src/livox_ros_driver2/launch_ROS1/msg_MID360.launch'