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Visual odometry with Pose-graph optimization

asked 2019-08-24 12:23:36 -0500

incendiary gravatar image

Hello,

I am performing visual odometry with viso2 on a webcam and want to do pose-graph optimization. I can visualise the poses and draw a trajectory with jsk_rviz_plugins. I am publishing a /base_link -> /camera tf needed for viso2. I am also performing depth estimation via deep learning in another node.

Now I want to create keyframes and do pose-graph optimization on them. I know about g2o, Ceres solver, open_karto, cartographer and openslam_vertigo, but I am unsure how to use them or where to even start with them. I found other packages that require laser data be published, but I am trying to implement monocular vSLAM w/o other sensors.

Any direction, advice or reference code would be appreciated

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answered 2019-08-26 06:48:27 -0500

Sebastian Kasperski gravatar image

First of all, for graph-slam you need to establish relative constraints between your key frames. With only (visual) odometry, you cannot do optimization. If you create pointclouds from your depth-camera, you can use ICP to create constraints between key frames. Then you can add all key frames and constraints to your optimizer (e.g. g2o) to create a global map.

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Hey, thanks for the reply

What kind of global map optimization can I do for visual odom-only slam? If I understand correctly my task, I am required to correct accumulated/drift error in pose estimation.

incendiary gravatar imageincendiary ( 2019-08-26 14:52:32 -0500 )edit
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With only odometry, you cannot do any optimization. Think of optimization as a method of data fusion. With only one source of information, there is nothing to fuse. So you need to think about what additional information you have. (e.g.: relative poses from scan matching, GPS, innertial measurements, loop closure detection,...) Optimization can then use all this information to create a most likely environment model based on your sensor data.

Sebastian Kasperski gravatar imageSebastian Kasperski ( 2019-08-27 04:51:34 -0500 )edit

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Asked: 2019-08-24 12:23:36 -0500

Seen: 68 times

Last updated: Aug 26