| Name | roboflo JSON |
| Version |
0.2.1
JSON |
| download |
| home_page | |
| Summary | Scheduler for automation tasks that involve multiple stations/workers. |
| upload_time | 2022-12-24 23:39:06 |
| maintainer | |
| docs_url | None |
| author | Rishi Kumar |
| requires_python | |
| license | MIT |
| keywords |
research
science
machine
automation
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://mybinder.org/v2/gh/rekumar/roboflo/HEAD?labpath=.%2FExamples%2Fbasic%20usage.ipynb)
[](https://badge.fury.io/py/roboflo)
[](https://codecov.io/gh/rekumar/roboflo)
`pip install roboflo`
Task scheduler for any system with coordinated workers. The original use case is for the Perovskite Automated Spin-Coating Assembly Line (PASCAL) in the Fenning Lab at UC San Diego, where a robotic arm moves small glass slides between stations to perform experiments.
`roboflo` assumes that you have a set of `Worker`'s that act (independently or in unison) to perform `Task`'s of set duration. Furthermore, one or more `Worker`'s can function to transition between `Task`'s (eg my robot moves a sample from the hotplate to a camera, or my mom moves me from school to soccer practice). These transition moves constitute a special case of `Task`'s , called `Transition`'s. The total set of `Worker`'s and `Transition`'s define your `System`. Sets of `Task`'s are consolidated into `Protocol`'s (eg the same process for five samples or five kids), which are then scheduled (using the `Scheduler` on your `System`) to minimize the total working time. An example schedule is shown below.
Happy robot-ing!
PS - shoutout to [Taskpacker](https://github.com/Edinburgh-Genome-Foundry/Taskpacker), from which I drew heavy inspiration. `roboflo` carries much of the design philosophy from `Taskpacker`, but uses only Python packages (the backend is Google ORTools as opposed to Numberjack, which can be difficult to install especially on Windows). `roboflo` also introduces `Transitions`, which define a finite state machine, as a critical component in the workflow under the assumption that many robotic platforms involve workers whose specific jobs are to move things between other workers.
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