As a freelancer, I build a lot of web sites. That's a lot of code changes to track. Thankfully, a Git-enabled workflow with proper branching makes short work of project tracking. I can easily see development features in branches as well as a snapshot of the sites' production code. A nice addition to that workflow is that ability to use Git to push updates to any of the various sites I work on while committing changes.
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This is an example of how to use the PCL filtering functions in a real robot situation. | |
This node will take an input depth cloud, and | |
- run it through a voxel filter to cut the number of points down (in my case, from ~130,000 down to 20,000) | |
- with a threshold to remove noise (requires minimum 5 input points per voxel) | |
- then transform it into the robot footprint frame, i.e. aligned with the floor | |
- subtract the robot footprint (our depth sensor's FOV includes the robot footprint, which changes dynamically with the load) | |
- subtract points in the ground plane, with different tolerances for near or far | |
- ground plane by default z = 0, but |