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Home > AI for Supply chain > Autonomous Warehouse

Autonomous Warehouse

Automate Warehouse Operations by Leveraging AI-based Robots: counting and classifying items, picking and moving products, upload/unload boxes, navigation, packing and unpacking, assigning products to different bags (in case of grocery), package damage detection, package label reading, and more. Use predictive maintenance to optimize robots’ inspection

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ROI Examples
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1. Get Inspired

Understand the Use-case under 5 minutes

2. Know More

Get to know more Business and Technical details about the use-case (15-30 minutes)

Deeper Intro

More detailed introduction covering business and technical aspects

Business Focused

Case studies, Organizational Aspects, Return on Investment examples

Tech focused

More details on the technical aspects of the use-case

3. Do

Technical resources that will help you implement the use-case (notebooks, tutorials..)

Data Sets

Data Sets you can use to build Demos, POCs, or test Algorithms

"Shelf & Tote" Benchmark Dataset for 6D Object Pose Estimation

452 scenes with 2087 unique objects poses seen from multiple viewpoints used to objects segmentation and 6D poses

Automatically Labeled Object Segmentation Training Dataset

136,575 RGB-D images of single objects from Amazon Pick Challenge in the shelf and tote


15k annotated short object centric video clips with pose annotations supplemented with over 4M annotated images including categories like bikes, books, bottles, cameras, etc.


Off-the-Shelf Products using AI for Automating Warehouse Operations

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