Cboost helped Smart Robotics with the development of a custom AI model seamlessly integrated into the Smart Item Picker, to overcome the challenging fashion item recognition process.

Increased accuracy from 75% to 99.83%
Improved robot item range and throughput for hard-to-pick items
The solution won first place in the Vanderlande picking challenge

The challenge

Smart Robotics provides unique technology and services to automate pick and place stations. Their Smart Item Picker experienced challenges with the reflection and refraction of fashion items placed in cardboard boxes or wrapped in transparent plastic. Their dataset was also limited.

Smart Robotics fashion picker

The solution

Cboost’s AI and Machine Vision experts worked in tight collaboration with Smart Robotics to develop a custom AI model.

 

To overcome a limited amount of data, Cboost initially trained an AI using an already proven model and a transfer learning process. This led to setting up AI pipelines that seamlessly integrated within the Smart Item Picker.