---
title: Solving Pick and Place Automation Challenges with 3D Machine Vision
description: This eBook covers typical challenges in industrial automation applications and how we can solve them with new machine vision technologies.
---

[3D machine vision blog - Zivid ](https://blog.zivid.com)

# [Solving Pick and Place Automation Challenges with 3D Machine Vision](https://blog.zivid.com/solving-pick-and-place-automation-challenges-with-3d-machine-vision)

 Written by [NARI SHIN](https://blog.zivid.com/author/nari-shin) | 2021-02-09

1. [Introduction](https://blog.zivid.com/solving-pick-and-place-automation-challenges-with-3d-machine-vision?hs_amp=true#introduction) 
2. Industrial Automation Challenges and Solutions  
   Objects that are hard to separate  
   Densely stacked  
   Colors  
   Shiny and reflective  
   Occlusion  
   Trueness
3. Application Examples  
   Bin-picking   
   Piece picking 
4. Considerations when choosing a machine vision camera
5. Conclusion 

[Download the full eBook](https://info.zivid.com/solving-pick-and-place-automation-challenges-with-industrial-3d-machine-vision?hsLang=en) for free.

<https://info.zivid.com/solving-pick-and-place-automation-challenges-with-industrial-3d-machine-vision?hsLang=en>

## Introduction 

Across logistics and e-commerce companies, we see a need for more automation to meet the increase in online shopping and demand for international shipping. Traditional picking, handling, and order-fulfillment tasks are highly repetitive, physically strenuous, and prone to human error.

Automation of high-volume processes gives vendors increased throughput, accuracy, and trustworthiness. It also enables logistics firms to assign human operators to safer or complex tasks, with additional value added.

However, performing a simple task like automated picking and placing an object is still challenging for robots in industrial environments. According to [The Robot Report](https://www.therobotreport.com/fully-automated-bin-picking-finally-here/), the adoption rate of bin-picking stations is low at large manufacturers, and the number is still close to zero at SMEs. For example, [Amazon hired additional 400,000 workers](https://www.washingtonpost.com/technology/2020/10/29/amazon-hiring-pandemic-holidays/) to keep pace with e-commerce demand that is not fully automated. It indicates that fundamental challenges in robotic solutions are not solved with existing systems.

This eBook covers typical challenges in industrial automation applications and how we can solve them with new machine vision technologies. Like humans, machines need high-performance vision sensors to detect, pick, and place objects accurately. You will also learn about key considerations for choosing the right machine vision for your industrial robots.

Throughout the e-Book, you will see examples of 3D point clouds used in bin-picking and piece picking applications, captured with industrial [Zivid 3D color cameras](https://www.zivid.com/zivid-two?hsLang=en) as well as other depth-sensing cameras. This will help you understand real-world problems in automation scenes and compare results between different machine vision sensors.

[Download the full eBook](https://info.zivid.com/solving-pick-and-place-automation-challenges-with-industrial-3d-machine-vision?hsLang=en) for free.

[View full post](https://blog.zivid.com/solving-pick-and-place-automation-challenges-with-3d-machine-vision)

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