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I R Vision Bin Picking Overview
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iRVision Bin Picking Overview

Apr 16, 2026

In this video, we walk through the essential steps for setting up a bin picking application using iRVision. We will cover the key concepts and configurations that make bin picking efficient and reliable. Our goal is to give you a clear roadmap without overwhelming you with unnecessary details, so you can confidently start building your own solution.

We begin by exploring the Vision Setup page, where all bin picking configurations are centralized. You’ll learn how to create a vision process tailored for bin picking, configure interference avoidance components, and tie everything together using the Parts List Manager. We’ll also discuss how to program a Teach Pendant (TP) program to execute the process seamlessly.

One of the highlights of this session is understanding how to manage dynamic bins. We’ll show you how to use tools like window shift and secondary vision processes to track bin movement and maintain accuracy. You’ll also discover how to configure pick scores, set reference positions, and optimize conditions for pick and approach flexibility.
To make this practical, we’ll dive into the IA system object, where you define bin dimensions, add avoidance zones, and leverage 4D graphics for visualization and debugging. We’ll also touch on IA Robot setup, UTool configuration, and strategies for handling interference during pick operations.

Finally, we’ll review the TP commands that bring it all together, including BpSearch, BpFindPickPos, and BPSetStat, along with tips for customizing the sample program for your application.

Requirements:
•    Access to iRVision and a compatible controller (R-50 or R-30iB+)
•    General knowledge of irVision
•    Basic understanding of robot programming
 

What You Will Learn:
•    How to configure a vision process for bin picking
•    Setting up interference avoidance objects
•    Using Parts List Manager 
•    Using TP commands to create a bin picking application program

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Skill Level

Intermediate

Topics Covered

Physical AI

Applications

Vision/Inspection

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