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HomeTechnologiesBrightpick

Autopicker: AI-Powered Mobile Picking Robot

by BrightpickFully automated
Pallet RackingAMR - CollaborativeAutonomous Mobile RobotsRobotic Piece PickingGoods-to-Person SystemsCase and Piece Picking
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Quick Facts

Vendor
Brightpick
Automation Level
Fully automated
Key Features
5 Features
Applications
3 Use Cases

Technology Performance Metrics

Efficiency88%Flexibility92%Scalability85%Cost Effect.82%Ease of Impl.85%

Key Features

1Autonomous Mobile Robot (AMR) that picks and consolidates orders directly in aisles
2Powered by proprietary 3D machine vision and AI trained on over a billion picks
3Offers hybrid Goods-to-Person (G2P) picking for heavy or hard-to-pick items (100% pick reliability)
4Works with standard shelving and totes, requiring no fixed infrastructure (grids, conveyors)
5Designed for fast deployment in existing warehouses

Benefits

Enables fully automated e-commerce warehouse operations
Maximizes labor savings through robotic picking
Provides flexibility with a hybrid robotic and G2P picking model
Acts as an alternative to fixed infrastructure systems (e.g., shuttle systems, cube ASRS)

🎯Applications

1Fully automated e-commerce order fulfillment warehouses
2Picking ambient and chilled groceries, pharmaceuticals, medical devices, packaged goods, cosmetics, electronics, polybagged apparel
3End-to-end supply chain automation in existing logistics operations

📝Detailed Information

Technology Overview

The Brightpick Autopicker represents a cutting-edge convergence of autonomous mobility, artificial intelligence, and robotic manipulation for warehouse automation. It tackles the core challenge of e-commerce and omnichannel fulfillment: the efficient and accurate picking of individual items (piece picking) from storage shelves. Unlike traditional automation that requires goods to be brought to a fixed station (Goods-to-Person), this system brings the robot to the goods, mimicking a human picker with a cart but with AI-guided precision. By eliminating the need for extensive fixed infrastructure like conveyor grids or storage cubes, it offers a highly flexible and scalable automation solution that can be retrofitted into existing warehouse layouts with standard shelving.

How It Works

Core Principles

The core principle is autonomous, in-aisle robotic piece picking. The AMR navigates to the correct storage location using its onboard mapping and navigation systems. At the pick face, its proprietary 3D vision system and AI identify the target item within a bin or tote on the shelf. A robotic arm then executes the pick and places the item into an onboard order consolidation tote. For items its AI deems challenging, it can autonomously bring the entire bin/tote to a Goods-to-Person station for manual picking, ensuring reliability.

Key Features & Capabilities

The defining capability is that it is an Autonomous Mobile Robot that picks and consolidates orders directly in the aisles, eliminating the separate travel and pick steps of traditional systems. This is enabled by being powered by proprietary 3D machine vision and AI trained on over a billion picks, allowing it to handle a vast array of item types. To guarantee reliability, it offers a hybrid Goods-to-Person picking mode for heavy or hard-to-pick items, ensuring 100% pick reliability. A major practical advantage is that it works with standard shelving and totes and requires no fixed infrastructure like grids or conveyors, which enables fast deployment in existing warehouses without major renovation.

Advantages & Benefits

The system enables fully automated e-commerce warehouse operations by handling the most labor-intensive task. It is designed to maximize labor savings through robotic picking while using the G2P hybrid model to ensure no automation gaps. This hybrid approach provides operational flexibility, allowing facilities to automate the majority of picks while handling exceptions efficiently. Its infrastructure-free design makes it an attractive alternative to capital-intensive fixed systems like shuttle systems or cube-based ASRS (e.g., Knapp, Autostore), offering a different path to automation.

Implementation Considerations

A key consideration is that for maximum labor savings, not every SKU needs to be robotically pickable from day one, as the G2P stations provide a reliable fallback. The system's performance and AI accuracy are not static; they rely on continuous machine learning from operational data to improve over time, implying a benefit from sustained use.

Use Cases & Applications

Ideal For

This solution is ideal for e-commerce and omnichannel fulfillment centers with high volumes of small-item, multi-SKU orders, especially those looking to automate without disruptive, fixed infrastructure installation.

Conclusion

The Brightpick Autopicker offers a compelling and innovative approach to warehouse automation, particularly for the demanding e-commerce piece-picking segment. By combining the flexibility of autonomous mobility with sophisticated AI-driven picking, it addresses both the efficiency and scalability challenges of modern fulfillment. Its ability to integrate into existing warehouse environments and its hybrid robotic/manual picking model lowers the barrier to entry for automation while promising significant labor savings and productivity gains. For operations seeking a flexible, scalable, and intelligent alternative to fixed automation systems, the Brightpick Autopicker represents a forward-thinking solution that leverages the latest advancements in robotics and artificial intelligence.