i did not get your point !!!

Sorry, I can't upload any pictures here. With that I could present it much more understandable.

Cloud: I understand by a cloud a quasi arbitrary accumulation of points. I only get them when I scan unsuitable surfaces.

Question: do you get an incomprehensible jumble or a blurred image of your surroundings?

My scans: I don't get a clean line (row of dots) for a wall, but a row of dots, with dots deviating within the tolerance of the laser (approx. +-10cm). If I don't clean up my display, I get a wide line of dots over several scans. This is not helpful for distance measurement. Therefore I make an average over 10 scans for each angle. Now I get an almost straight line of points. These values are suitable for distance measurement.

One more question: do you already have the laser data as a tuple? Each value in the tuple is the distance for the angle, corresponding to the position in the tuple.

@citkid I upvoted your answer, I think you can already upload your photo (it's from 10+ karma points, I think)

thanks, i am working with Ros kinetic, the pkg that you mentioned is for melodic and noetic. in the environment i have 3 objects, i want to identify the distance from these object to the vehicle, based on the point cloud received from Lidar.

I get stuck in this phase:(

Are you hard set on using old and unsupported ROS version? Upgrade could be possibly the easiest route. Backporting software to the older environment can break a lot of dependencies. Maybe this package could work?

https://github.com/introlab/find-object (branch: kinetic-devel, but for a normal 2D camera...)

There is some ancient software called ORK too: https://github.com/wg-perception/ork_tutorials/blob/master/doc/source/tutorial03/tutorial.rst

I have point cloud coming from a 3D lidar. I do not want to make it so complicated. I just want to identify the distance from the detected object to the lidar from the pointcloud that i have received.

Let's get our definitions straight - what do you mean by "detected object"? In a point cloud you have points, do you want the distance to each of them? Or only to some of them? Do you assume any grouping of them - if so, how? The distance will be a Frobenius (Euclidean) norm of the position + (LiDAR offset) vector of the robot (from AMCL, odometry etc.) minus the center point of the object, e.g. (x_object, y_object, z_object), but at the moment I don't really know what you mean by "detected object`.

That's why I assumed these steps:

• use a library to detect objects in the point cloud and get their positions

• use robot position/it's LiDAR position to calculate the distance as a sqrt((x_lidar-x_object)^2+(y_lidar-y_object)^2+(z_lidar-z_object)^2)

maybe i did not use a proper word. i wanted to mention the objects that appeared in the pointcloud. i want distance to the object. i donot want distance to each of the points. I think for instance if i could find the middle point (or any other point) in the pointcloud related to the object, then distance can be calculated easily.

from the steps which you mentioned, which library do you propose, which is easy to implement as well?