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[Nav2] 3D obstacle avoidance with Realsense D435(i)

asked 2021-07-20 08:32:39 -0500

p0rys gravatar image

Hey!

i'm working on a mobile robot platform and tuning the navigation right now. After a few hours on the real hardware and in gazebo simulations i encountered a problem with the voxel layer. Everytime one of the Realsense D435 on my robot (4 in total - one for each site) detects an obstacle it is marked correctly in the voxel layer but if i remove the obstacle some of the voxels still stay in the costmap (mostly the lower and upper part). This will block the area and result in replanning or aborted navigation.

I read multiple github issus / questions here on answers.ros.org and it seems that this is a common problem with the raytracing algorythm. I tried almost all "solutions" that i have found but nothing seems to work.

Is it really the only answer to use the non-persistent voxel layer or STVL for Realsense 3D pointclouds? And if so, why is almost every example in the internet using the normal voxel layer?

Thanks in advance!

p0rys

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answered 2021-07-20 17:43:21 -0500

updated 2021-07-20 17:44:26 -0500

Is it really the only answer to use the non-persistent voxel layer or STVL for Realsense 3D pointclouds? And if so, why is almost every example in the internet using the normal voxel layer?

It's an answer, there are several, including building your own 3D perception layer. The examples you find online are likely much older than STVL. I've made some documentation / tutorials on STVL but that was only released in 2018 while the Nav stack has been in business for about a decade prior to that. So you'll find many more resources from that time and from momentum as the "default" in the Nav stack. It's also not a general purpose replacement, it really has a niche it is built to support requiring pretty decent sensor coverage and/or operating in reasonably dynamic environments.

Don't fear, there are many companies using STVL and its stable (since I rarely hear complaints) so its a decent option to consider -- especially if you have good sensor frustum coverage like your describe.

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Asked: 2021-07-20 08:32:39 -0500

Seen: 181 times

Last updated: Jul 20 '21