Pick and place with multiple references conditioning

V.1.1

Pick and place with multiple reference conditioning

Difficulty: easy

Time: ~20 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

Introduction

The goal of this application is to show multiple examples of applications you can do with the Vision Set and Ned/Ned2 but also to have a first approach with industrial processes which can be carried out with Ned/Ned2. This process consists in picking any type of object from a working area and conditioning them in a packing area according to its color.

Requirements

Knowledge:

  • 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’s documentation: https://archive-docs.niryo.com/dev/pyniryo/index.html
Hardware:

  • A Vision Set

  • A Ned (or a Ned2)

  • PyNiryo library installed on your computer

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 multiple reference

Script’s operation

This script shows an example on how to use Ned’s Vision Set in order to make a conditioning according to the objects’ color.

The objects will be conditioned in a grid of dimension grid_dimension. The Y axis corresponds to the ObjectColor: BLUE / RED / GREEN. The X axis corresponds to how many objects can be put on the same line before increasing the conditioning height. Once a line is completed, objects will be packed over the lower level.

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

You can change the variable grid_dimension below if you want to create your own environment.

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

  • observation_pose

  • center_conditioning_pose

  • sleep_pose