PyLabRobot Feature Demo: cLLD Probing for Resource Definition Automation

Hi everyone,

In a recent conversation with an engineer interested in using PLR, the question was raised how we aim to validate resource definitions across the PyLabRobot ecosystem.

This made us create the following PLR feature demonstration, showcasing the ideal level of data-driven evidence behind resources added to the PLR Resource Library:

This demonstration uses the STAR.probe_z_height_using_channel(channel_index_as_int) function, added in PR#69, to detect the surface of a PlateCarrierSite on the plate_carrier PLT_CAR_L5AC_A00.
Specifically, it showcases the PlateCarrierSite’s 3 different z layers, and gathers the data to confidently add an updated pedestal_z_height to this plate_carrier’s PLR Resource Library definition (see pylabrobot/resources/ml_star/plate_carriers.py).

Ultimately though, with tools like these we aim to automate the definition generation process for resources in general and increase the robustness of these definitions.

Note that this function only works on probing conductive material, and is therefore not usable on most plates.

Please feel free to add feedback on how we as an open-source community can improve and build upon this tool, or if you have any questions regarding this feature demonstration, in this thread.

Happy automation :mechanical_arm:


PS.: With demonstrations like these we aim to highlight the myriad of advantages that programmatic control of your lab machines can bring to your research.
If you’d like to showcase some of your work in a similar manner on the PyLabRobot YouTube channel and/or documentation pages please reach out to @rickwierenga and me.

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