robot_localization ekf faster than realtime offline post-processing

asked 2019-06-01 03:42:06 -0500

runerer
26 ●1 ●1 ●3

Hi,

I'm using a Robot Localization EKF configured to receive twist - linear and angular velocity derived from a wheel encoder and odometry derived from SLAM position estimates.

The EKF is working reasonably well in real time, however I'd like to be able to replay ROS bagged data through this EKF in faster than realtime. I've tried speeding up the bag file replay and am getting some errors in position from the EKF. Is faster than realtime offline / post-processing possible with the Robot Localization EKF?

Thanks

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answered 2019-06-09 08:11:24 -0500

runerer
26 ●1 ●1 ●3

Thanks for the response. I believe the issues I was having were related to the size of the bag data I was trying to replay. Once I stripped out the topics that are not used by the EKF from the bag data the high rate replay worked fine.

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answered 2019-06-06 02:28:15 -0500

Tom Moore

flag of United Kingdom of Great Britain and Northern Ireland

13689 ●74 ●240 ●232 http://github.com/ayrton04

What's the CPU usage like? The filter just uses ROS time, so theoretically, all the message queuing and timing should work the same. But if a given update cycle takes too long in real seconds, I can see the queues overflowing and messages getting dropped.

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robot_localization ekf faster than realtime offline post-processing

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