Solution
Proven Approach to Mixed Case Depalletization
The Plus One Robotics Depalletization System handles a variety of pallets, increasing warehouse flexibility and reducing costs.
The Challenge
Not All Pallets Are Created Equal
Rainbow/Row Pallets: Different rows of homogeneous layers of any type require flexible vision and grip strategies.
Mixed Case Pallets: Each layer may contain different items, adding significant complexity to depalletization. Mixed case palletizing is rapidly becoming standard for more flexible shipping.
Although flexible depalletizing has been challenging for traditional robots, today’s advances in AI-powered vision have made it practical and reliable.
Key Performance
500 - 1,000
Typical picks per hour
350 - 480ms
Pick command processing speed
Capabilities
Intelligent Depalletization, Built for Complexity
Layer-by-Layer Picking
Fully depopulates the top layer before moving to the next to prevent toppling.
Item Classification
Classifies items by package type to dynamically adjust grip strategy, acceleration, and speed.
Empty Pallet Detection
Confirms an empty pallet so the system can replace it with a full one automatically.
Place Verification
Images the place zone to confirm single-case placement and prevent double induction.
Offset Picking
Automatically calculates offset when items are smaller than the robot end effector.
Supported Item Types
Boxes, overwrapped trays, cartons, bags — including edge cases like flat black cases and banded items.
Process
How AI-Powered Robotic Depalletization Works
A seven-step process from pallet arrival to outfeed, powered by PickOne perception and Yonder human-in-the-loop support.
Pallets are brought to the Pick Station by human workers or pallet conveyor.
The PickOne Perception Kit images the pallet using 2D, 3D, and AI algorithms.
Software analyzes data to identify each pickable item and assigns a confidence score.
PickOne sends an array of pick locations and poses to the robot controller via API.
Low-confidence items trigger a Human-in-the-Loop request resolved within 6 seconds.
HITL responses train machine learning algorithms for continuous improvement.
Items transfer to outfeed conveyor, sorter, or descrambler for subsequent processes.
Benefits
Quantified Impact for Your Operations
Increase throughput by as much as 30% for mixed pallet breakdown
Ensure high uptime with real-time exception handling
Reduce repetitive tasks, upskilling labor to higher-satisfaction positions
Reduce the number of picking errors
Achieve consistent and accurate flow of goods
Adapt in real-time to packaging changes and damaged goods
Industries
Industries We Serve
Talk to Us About Automated Depalletizing
Our team will help you evaluate how robotic depalletization fits your operations — from throughput analysis to deployment planning.
Ready to see it in action?
Talk to our team about automating your warehouse operations with proven AI-powered robotic picking.