Pick and place conditioning with two workspaces

V.1.1

Pick and place conditionning with two Workspaces

Difficulty: medium

Time: ~30 min

Note

This tutorial is working from:
The version v3.0.0 of the ned_ros_stack
The version v3.0.0 of Niryo Studio
The version v3.1.0 of PyNiryo

Objectives

  • Show multiple examples of applications you can do with the Vision Set and Ned/Ned2

  • Have a first approach with industrial processes which can be realized with Ned/Ned2

Requirements

  • Basic knowledge of Python

  • Being able to use Ned/Ned2

  • Having studied the Vision Set’s User Manual

  • Having looked at PyNiryo library documentation

Note

Documentation of Ned: https://archive-docs.niryo.com/product/ned/index.html
Documentation of Ned2: https://archive-docs.niryo.com/product/ned2/index.html
The Vision Set’s User Manual: https://archive-docs.niryo.com/product/vision-set/index.html
PyNiryo documentation: https://archive-docs.niryo.com/dev/pyniryo/index.html

What you will need

  • A Vision Set

  • A Ned (or a Ned2)

  • PyNiryo library installed on your computer

Conditioning and packing with two workspaces

This process consists in picking any type of object from one working area and conditioning them in one packing area. Then this packing area will become a working area and we will run the process again to condition the objects on a second packing area.

You can find below a schematics of the application to help you visualizing it.

Ned

The script of the application can be found here: Vision conditioning two workspaces

Explanation of the script

This script shows an example on how to use Ned/Ned2’s Vision Set with 2 workspaces: one for picking and one for packing.

The robot will first detect one pack place, then it will take one object from the picking area. This object will be packed and then, the pack will be placed on the side of the working area.

Note

The code is well commented so you can easily understand how this application is working.

Before running the application, you will have to change these variables below:

  • robot_ip_address

  • tool_used

  • workspace_name

Finally, you may change the variable below to adapt the application the perfect way to your environment:

  • observation_pose

  • center_conditioning_pose

  • sleep_pose