Robot localization for very accurate position [closed]

asked 2017-02-01 13:55:28 -0500

armin1215 gravatar image

##Scenario I have to do lane following in an environment where lanes are marked on the ground and many obstacles are present in those lanes. At some point, I must leave the lanes and navigate through another complex open area to reach another section of lanes. The course I am navigating is complex and requires a very accurate (less than 1m) mapping.

I already can identify the edges of lanes (including distance and shape) pretty well and I have a Lidar for the obstacles. Additionally, I have encoder, GPS, and IMU values.

##Question My question is this: If I treat the lane markings like obstacles (lines) I would receive from the Lidar and throw them into robot_localization with GPS and/or IMU data, then will I get an accurate position even if that position is only relative to my start point?

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Closed for the following reason question is not relevant or outdated by Tom Moore
close date 2020-01-24 04:20:44.360634



robot_localization provides IMU and odometry-based state estimation with a kalman filter, but it sounds like you're looking for something more like SLAM (Simultaneous Localization and Mapping.)

ahendrix gravatar image ahendrix  ( 2017-02-02 00:37:04 -0500 )edit

Seconded. r_l has no real concept of objects and obstacles. It just fuses pose, velocity, and acceleration data to provide a state estimate.

Tom Moore gravatar image Tom Moore  ( 2017-02-21 03:15:44 -0500 )edit

Can this question be closed, or are you still looking for more information?

Tom Moore gravatar image Tom Moore  ( 2017-07-20 04:20:51 -0500 )edit