idc-milab/openlh

The OpenLH is a Liquid handling system based on an available robotic arm platform (uARM swift Pro) which allows for creative exploration by biologists and bio-enthusiasts.

OpenLH: Open Liquid-Handling System

The OpenLH is a Liquid handling system based on an available robotic arm platform (uARM swift Pro) which allows for creative exploration by biologists and bio-enthusiasts.

You can find full and detailed step-by-step guide for building one on our Instructables page, including BOM, STL models and precise instructions. Find more info on the project's website. Share with us if you're building one!

Getting Started

Before you continue reading, make sure you have:

Python 3.7 and PyCharm IDE. Then, clone this repository by:

git clone https://github.com/idc-milab/openlh

Setting up Python Environment

Open the folder you cloned as a project, through PyCharm.
First, we will create virtual environment for this project (For more information https://www.jetbrains.com/help/pycharm-edu/creating-virtual-environment.html):

1. Enter File → Settings → Project: → Project Interpreter.
2. Click the ⚙️ icon and choose Add
3. In Add Python Interpreter window, select Virtualenv Environment:
   • Specify the location of the new virtual environment in the text field, or click Virtual environment location and find location in your file system. Note that the directory where the new virtual environment should be located, must be empty!
   • Choose the base interpreter from the drop-down list, or click Choose the base interpreter and find the base interpreter in your file system.
   • Select the Make available to all projects check-box, if needed.
4. Click Ok

Install packages

This project uses several libraries within it:

• flask: Flask is a web framework for Python based on the Werkzeug toolkit.
• bokeh: Interactive Data Visualization in the browser, from Python.
• pyserial: Python serial port access library
• python-osc: Open Sound Control server and client in pure python
• numpy & matplotlib: calculating and visualizing auto-generated grids

After setting up the virtual environment, use pip to install the required packages through the Terminal in the bottom left:

pip install -r requirements.txt

Running for the first time

After setting it all up, run both app.py and listener.py modules. Then, in your web browser enter: http://127.0.0.1:5000/. Now you can easily create programs for the arm via the blockly interface and run them with the OpenLH!

Main features

• Move To: Move the arm to a specific location. To use it, just generate a new Move to block (from 'Robot' section) as well as the relevant coordinates block (from 'Robot' section). In the coordinates block, X Y Z stands for the coordinates, E for extrusion level and S for movement speed.

• Move Wrist: Rotate arm's wrist with the required angle. Useful to drop used tips from the arm to a disposal area.

• Bitmap to Bioprint: An interface that would load a png bitmap, select all the pixels of a single color, and print these pixels with the OpenLH. To use it, just generate a new Image block (from 'Image' section) as well as the relevant coordinates blocks (from 'Robot' section).

• Manual Position: Puts the arm in disjoint mode, allowing the user to move it around manualy and sample coordinates. After reaching a desired location, a tip to pick up for example, hit set button to generate the location's coordinates as a new useable block.

Project Structure

The uArm runs on top of an Arduino Mega 2560 with a custom version of Marlin firmware (available under GPL license). The robot operates using G-code definitions sent through UART protocol.

Overview

The code flows throughout the project in the following way: The user may generate different programs manipulating the arm using google's Blockly interface. The generated program is then compiled to python code, using the Swift API (which compiles to G-code commands), and sent as an XML Http Request to app.py. The message is then being sent as a UDP message to the listener. Eventually, the listener is executing the code which activates the arm. In addition, it is possible to save programs for later use and upload images for the Bitmap to Bioprint feature.

• app.py
  • Main app module. Dealing with all the different app routes (receiving XML HttpRequests from index.html)
• listener.py
  • This is the listener of the project. Registered to receive messages which was sent from the app.py through SimpleUDPClient.
  • The message will include strings with python code including instructions for the arm - using SwiftAPI and generated on the Blockly environment.
  • messages will always end with "xxx" string, indicating that the whole message successfully transferred.
• coordsplotter.py
  • This script receives a .coords file name as a parameter (a list of coordinates representing an image. created by uploads/convert.bat) and generates an html page including a visual representation of the image. the html page will be saved on the templates folder.
• /google-blockly
  • This handles the blockly infrastructure
• /programs
  • directory for xml files representing blockly programs that the user have chosen to save for later use.
• /pyuf
  • modified version of the uArm-Python-SDK (version 1.0)
• /templates
  • index.html - main software page
  • different templates of visual representations for images (before printing)
• /uploads
  • .png files uploaded.
  • .coords files representing the image coordinates.

openlh's Issues

Consider replacing XMLHttpRequest library (index.js) with a better one

how to connect nema17 and swiftpro

Is there need change Swift pro's code?

Move JS code from index.html to index.js

TBD

Swift API for 3D-printers

Hi, it seems a very good project. I wonder where to modify the swift api so that this project can be adopted for generic 3D-printers, not just uARM. Thanks.

Replace the "hardcoded" python code inside index.js with a python API