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Which technique for 2D SLAM is easy to learn?

asked 2013-10-27 23:27:25 -0600

sarkar gravatar image

Hello Everybody,

A ROS newbie here. I'm learning ROS and currently at the file system tutorials. I'm currently running ROS on 64-bit Ubuntu 12 and soon I'm going to install it on Beaglebone Black (Angstrom).

I have a Logitech C920 webcam with hardware H264. Please suggest me 2D slam technique which can be used with my webcam and is easy to learn.

Regards, sarkar

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answered 2013-10-29 11:49:47 -0600

sudhanshu_mittal gravatar image

Hi 2D SLAM gives a 2D map of the envirnment called GMAP.(Refer to http://wiki.ros.org/gmapping) GMAP gives you detailed information about the object occupancy in that 2D plane. This occupancy grid generated from gmapping gives a accurate scaled information about the actual real world. Each x and y coordinate in this 2D grid is accurate just scaled to some particular resolution, whereas in image captured from camera is a perspective image hence there is no possible transformation possible from image to real world coordinates.

2D SLAM is technique, which is quite easily be performed using lasers. Since you are a "newbie", I would suggest you to use Kinect, which is cheapest multi-sensor available.

I am not saying that it is impossible to do 2D SLAM from a webcam, but it would require a lot of knowledge and effort.

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Related sub-question, sudhanshu_mittal, Is it fairly easy to implement the 3D SLAM instead of the 2D SLAM in the Navigation stack? I am wondering because I am more familiar with ROS but not yet familiar with the Navigation stack or SLAM :) Thanks!

MartinW gravatar imageMartinW ( 2013-10-29 12:04:11 -0600 )edit

Definitely 2D SLAM is much more easier to implement that 3D SLAM, I have implemented 2D SLAM with turtlebot as well as seen people implement 2D SLAM on self built robots using navigation stack. What i believe from my experience is, 3D SLAM is harder to implement and computationally very expensive.

sudhanshu_mittal gravatar imagesudhanshu_mittal ( 2013-10-29 12:20:37 -0600 )edit

sudhanshu_mittal, I have IR Proximity sensors which I can easily connect to Beaglebone Black. Are they good choice for 2D slam? I think I'd need some kind of middleware to read their data in ROS through BBB pins. sarkar

sarkar gravatar imagesarkar ( 2013-10-30 07:26:47 -0600 )edit

and the Kinect options seems reasonable. It's advantageous due to it's design as a slam and image processing sensor. Please provide a tutorial on how to use kinect for slam. However I think kinect doesn't have hardware H264 encoding that would make it difficult to use with Beaglebone.

sarkar gravatar imagesarkar ( 2013-10-30 07:29:36 -0600 )edit

Thanks for the reply! I eventually want to get 3D recognition (maybe SLAM) within the robot project I am working on but first I will get 2D SLAM working and then work on the more complex problems. Kind Regards, Martin

MartinW gravatar imageMartinW ( 2013-10-30 08:22:21 -0600 )edit

@sarkar: I have no experience with Beaglebone Black, but i can definitely say that its not possible to perform 2D slam/ gmapping from simple IR proximity sensor, since it gives only single point distance plus the data measured is raw.

sudhanshu_mittal gravatar imagesudhanshu_mittal ( 2013-10-30 14:43:38 -0600 )edit

@sarkar: First of all, if you have a ROS supported robot like turtlebot,..then you just have to launch a few files. If you are working with a self made robot, then a few extra steps need to be performed before using the inbuilt packages of ROS. Let me know, which robot you are using ?

sudhanshu_mittal gravatar imagesudhanshu_mittal ( 2013-10-30 14:48:56 -0600 )edit

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Asked: 2013-10-27 23:27:25 -0600

Seen: 1,391 times

Last updated: Oct 29 '13