With 2019.5 we are introducing the brand new compute3D camera localization feature. Only a handful of teams have even attempted to add this feature to their vision systems, and now it is available to all Limelight 1 and Limelight 2 users.
This is not a silver bullet for this year’s game. We highly recommend thinking of creative ways to use the standard high-speed 90 fps tracking unless this feature is absolutely necessary. You may notice significant noise after about 5ft of distance to the target.
All example gifs were created with an LL2 mounted on the side of a kitbot. This is why you will see slight changes in translation during turns.
Features
- High-Precision Mode and PnP
In the following gif, a Limelight 2 was placed 37 inches behind and 14.5 inches to the right of the target.
The Limelight was later turned by hand. Notice how the distances remain mostly unchanged:
With 2019.4, we introduced corner sending. This allowed advanced teams to write their own algorithms using solvePNP. With 2019.5, this is all done on-board.
Upload a plain-text csv file with a model of your target. We have pre-built models of 2019 targets hosted on our website. All models must have a centered origin and use counter-clockwise ordering.
Enable the new high-res 960x720 mode, and then enable “Solve 3D” to aquire the position and rotation of your Limelight relative to your target.
Corner numbers are now displayed on the image for easier model creation.
Read all 6 dimensions of your camera’s transform (x,y,z,pitch,yaw,roll) by reading the “camtran” networktable number array.
- Black Level
- With the new black level slider, thresholding is even easier. Increase the black level offset to further darken your images.
Breaking Changes
- The reported vertical FOV for LL2 has been fixed to match the listed value of 49.7 degrees. This will change your “ty” values
Bug Fixes
- Fix stream-only crash that could occur when fisheye USB cameras were attached.
- Fix rare hang caused by networking-related driver.
- Corner approximation is now always active.