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Improving the map or odometry for slam_gmapping

asked 2013-11-20 13:06:02 -0500

MartinW gravatar image

Hello all,

I am currently working on building a 2D map of lab and office environment. In the lab (approx 5m x 10m) I see really good results and great map created. However, when I extend this slam_gmapping application to outside the lab we see a drastic decrease in the accuracy of the map built.

Here is a link to the map built, it should look like two rectangular hallways.

From reading other questions I believe this is from the drift of the /odom frame and in fact I can see that it has drifted when I run the robot through a loop and bring it back to its initial position.

Therefore, I was wondering if there was a way to update the odometry frame by using estimated robot poses from the slam_gmapping package? Or is there another method towards obtaining a more accurate map of a larger scale environment?

Kind Regards, Martin

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In my experience slam_gmapping is OK with dealing with slow drift, and miserable with rotation of the robot. Even more sensitive than Hector Slam. When turning corners too fast (I assume you are joysticking robot remotely) the map gets disjointed and rotated like that. Try again with slower turns.

billy gravatar image billy  ( 2016-06-22 23:06:31 -0500 )edit

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answered 2013-11-20 19:00:01 -0500

sudhanshu_mittal gravatar image

I would like to suggest a few measures which you should try out once:

1.One of the possible problems could be stalling of CPU cycles, Firstly, check the CPU processing of your laptop while gmapping package is running on turtlebot and simultaneously observe the turtlebot movement in rviz. If you observe CPU cycle striking near 100% or if rviz hangs or goes offline for short time interval every time the turtlebot moves, then one of possible solution is to increase the parameter value of "map_update_interval" in gmapping package to around 25-30.

2.If still the problem exists, the other solution is increase the the parameter value "maxUrange" in gmapping package according to the environment. According to my experience if your room is about 10m by 5m , then your range shoud lie around 5m atleast.

3.Other solution might be decreasing the angular acceleration and angular velocity parameters of the robot. You may find these parameters in "base_local_planner_params" file in gmapping package.

4.According to me, last you can try is decreasing the values of parameters "linearupdate" and "angularupdate" and increase no of particle value for better robot localization in gmapping launch file.

This worked out for me.

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Asked: 2013-11-20 13:06:02 -0500

Seen: 1,517 times

Last updated: Nov 20 '13