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Technical details of the VSLAM package

asked 2012-03-19 22:46:28 -0500

Divya gravatar image

updated 2014-01-28 17:11:41 -0500

ngrennan gravatar image

Hi, Can anyone help me with the technical details of the VSLAM package? Like What feature matching techniques were used (in the VSLAM_SYSTEM package available in ROS), what was the main uncertainty algo used - Kalman Filter? EKF? or Monte-Carlo Implementation?

Or is there any paper that I could refer to that would help me figure these out. I want to know what methods were used to implement the VSLAM package available in ROS.

I'm trying to analyze the performance of VSLAM for my thesis and I really need to find out what algorithms have been used in order for me to get started.

Thank you.

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answered 2012-03-20 04:47:17 -0500

Mac gravatar image

The VSLAM package in ROS (, is (a) unsupported (b) out of date and (c) very brittle, as most VSLAM systems are.

If you want to know how it works, read the code. If you're looking for a highly general VSLAM that will work on your system, for your data, we recommend you look elsewhere.

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Um.. I know its slightly out-dated. Unfortunately, my project is based on this particular version of VLSAM implementation and I've already done my testing using this particular set of packages! That's precisely why I need the technical details of this particular implementation! :| ..

Divya gravatar image Divya  ( 2012-03-20 16:44:09 -0500 )edit

I'm also using another Visual odometry method called libviso which works with OpenCV.. I am basically trying to compare the performance of that with VLSAM.. Sorry if I am making it all the more confusing!

Divya gravatar image Divya  ( 2012-03-20 16:45:25 -0500 )edit

Then you'll need to read the code; since it's not supported anymore, that's the best we can do.

Mac gravatar image Mac  ( 2012-03-21 08:15:51 -0500 )edit

ahh!! I read through most of the code. To be honest, I don't understand most of it! Anyways, thank you :)

Divya gravatar image Divya  ( 2012-03-21 22:03:33 -0500 )edit

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Asked: 2012-03-19 22:46:28 -0500

Seen: 230 times

Last updated: Mar 20 '12