RBS — Random Box Stacking

A robotic solution that automatically recognizes mixed-size boxes to automate palletizing and depalletizing.

Introduction

Robotic Palletizing and Depalletizing Automation for Mixed-Size Boxes

RBS is a robotic automation solution that automatically recognizes boxes of varying sizes and shapes in logistics and distribution environments and performs palletizing or depalletizing.
Built on 3D vision and stacking algorithms, it enables the robot to identify target objects and carry out stacking tasks even where mixed-size boxes are intermingled.

Process

How RBS Works

Box recognition, stacking pattern generation, stability verification and robot execution run as separate, distinct stages.

  1. 1
    3D box recognition
  2. 2
    Load stability check
  3. 3
    Placement generation
  4. 4
    Robot task command
  5. 5
    Robotic stacking
Key Feature

Key Features of RBS



01Automation Throughput

The RBS system is designed to handle approximately 560,000 items per year with a single robot, automating repetitive stacking work on site and reducing reliance on manual labor.

02Cost Efficiency

With a relatively simple setup compared to conventional logistics automation equipment, RBS helps distribution centers and parcel sorting sites lower operating costs when adopting automation.

03Broad System Compatibility

RBS connects the robot to an external AI computing server over TCP/IP and UDP. AI computation runs on external high-performance hardware, and the resulting task commands are sent to the robot controller. This architecture allows integration with a wide range of industrial robots, including Hyundai Robotics, Kawasaki Robotics, Doosan Robotics and FANUC.

Specification

Specifications

Detailed specifications for technical evaluation.

Throughput targetApprox. 560,000 items per year per robot
OperationsSupports both palletizing and depalletizing
Box handlingMixed-size boxes of varying sizes and shapes, including mixed loads
3D visionToF (Time of Flight) 3D camera, identification of adjacent objects
Stacking simulationER STACKER (accounts for gravity, friction, irregular shapes and center-of-gravity shift)
Stacking methodsLayer rotation, symmetric placement, slip-sheet insertion and other stacking methods
Stacking algorithmOptimization algorithm, enhanced with reinforcement learning (RL)
Communication protocolsTCP/IP, UDP
Robot compatibilityHyundai Robotics, Kawasaki Robotics, Doosan Robotics, FANUC and more (manufacturer-agnostic)
ApplicationsDistribution centers, parcel sorting sites and other environments with mixed-size boxes
Validation

Ongoing Collaboration

Backed by government R&D support, RBS is being advanced into a next-generation unmanned logistics system.

TIPS

RBS 2.0 — Selected for 2025 Deep Tech TIPS

Selected for Korea's Ministry of SMEs and Startups' 2025 Deep Tech TIPS program, Euler Robotics is developing RBS 2.0 with approximately KRW 2 billion in R&D funding. Goals include an automated logistics process spanning unloading → sorting → stacking, real-time recognition and sorted stacking of boxes moving on conveyors, digital twin–based stacking pattern generation, and integration with autonomous mobile robots (AMRs).

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