Case Palletizing with Robots: How Vision-Guided Systems Handle Mixed Loads

Case palletizing is one of the most physically demanding and relentless tasks on any warehouse or distribution floor. Cases arrive continuously, in varying sizes, from multiple lines. Workers stack them onto pallets in patterns designed to maximize stability and load density, then do it again, and again, across an entire shift.

The repetition and physical load make manual case palletizing a prime target for automation. But traditional palletizing robots have a limitation: they work well when every case is the same size, arrives in the same orientation, and follows a predictable pattern. The moment you introduce mixed case sizes, patterned surfaces, or variable incoming order, fixed-program systems break down.

Vision-guided robotic case palletizing solves that. This post explains how it works, what the technology enables that fixed-program palletizers cannot, and which cobots Blue Sky Robotics recommends for the job.

The Problem with Traditional Case Palletizing

Fixed-program palletizing robots are programmed with a specific pallet pattern for a specific case size. They are fast, reliable, and well proven at high volumes. What they cannot do is adapt.

A logistics transfer center handling multiple SKUs receives cases of different dimensions arriving in no particular order. A food manufacturer running multiple product lines palletizes cartons with printed patterns, reflective tapes, and barcodes across the surface. A distribution center building mixed pallets for retail customers needs to stack different case sizes together in a configuration that will not collapse in transit.

None of those scenarios work with a fixed program. Every case size needs its own program, every change requires reprogramming, and mixed pallets require human judgment that fixed automation cannot replicate.

How 3D Vision Solves Mixed Case Palletizing

A vision-guided palletizing system uses a 3D industrial camera mounted above the work area to capture precise image data of each incoming case before the robot picks it. The vision software processes that data to determine the case dimensions, position, and orientation, then passes the information to an intelligent palletizing algorithm that plans the optimal stacking sequence in real time.

The Mech-Eye DEEP-GL camera is designed specifically for this application. It features a large field of view that covers a full pallet footprint from a fixed overhead mount, and its structured light technology produces accurate 3D point clouds even on cases with patterned surfaces, printed graphics, reflective tape, express bills, and barcodes. These are the surface conditions that defeat most standard cameras but are standard on real warehouse cases.

The palletizing software takes the camera data and does several things automatically. It plans a stacking pattern that is both stable and space-efficient, accounting for each case's dimensions and weight distribution. It determines the sequence in which cases should be picked to build the pallet correctly. It guides the robot to pick multiple cases in a single grasp when the multi-pick strategy applies, increasing throughput. It maintains a record of the pallet pattern so the robot can resume stacking partial pallets after an interruption without starting over. And it runs continuous collision detection and trajectory planning to navigate the robot safely around camera brackets, support structures, and other obstacles in the workspace.

The result is a system that handles variable incoming cases at high speed without reprogramming, human intervention, or the throughput loss that manual palletizing introduces.

What This Looks Like in Practice

A large food industry logistics transfer center faced exactly this challenge. Cases of different sizes arrived randomly at their palletizing station, with intricate and uneven surface patterns across the case exteriors. The speed requirement was demanding. Manual palletizing could not keep pace without adding headcount, and fixed-program automation could not handle the case variability.

The Mech-Eye DEEP-GL camera combined with Mech-Mind's vision and path planning software guided the robotic arm through the full palletizing cycle automatically. The camera read each incoming case, the software planned the stack, and the robot built stable mixed pallets continuously without human interaction. The workstation ran with high efficiency and no stops for changeover or reprogramming.

Which Cobots Handle Case Palletizing

Case palletizing puts specific demands on a robot arm. Payload is the primary constraint. Most shipping cases for consumer goods, food, and beverage fall in the 5 to 20 kg range depending on product type, and multi-pick strategies push that requirement higher when the arm is grasping multiple cases simultaneously.

The Fairino FR10 ($10,199) is the entry point for serious production palletizing work. A 10 kg payload handles the majority of consumer goods and food and beverage cases. Its 1,450 mm reach covers a standard pallet from a fixed mount, and full ROS compatibility makes integration with vision software and conveyor systems straightforward.

For heavier cases or multi-pick applications where the combined weight of two cases at once pushes past 10 kg, the Fairino FR16 ($11,699) provides 16 kg of payload headroom while maintaining the reach needed for standard pallet layouts.

For the heaviest case palletizing applications, the Fairino FR20 ($15,499) and Fairino FR30 ($18,199) extend capacity to 20 kg and 30 kg respectively, covering bulk goods, bagged product, and industrial materials that exceed the limits of lighter arms.

For smaller operations with lighter products under 5 kg, the Fairino FR5 ($6,999) can handle case palletizing tasks in a proof-of-concept or lower-throughput cell before scaling to a larger arm.

Getting Started

Use our Automation Analysis Tool to model the labor savings and throughput gains of a vision-guided palletizing cell against your current operation. The Cobot Selector can help confirm the right arm based on case weight and pallet dimensions. When you are ready to see a live demonstration, book a session and we will walk through a cell design for your specific application. To learn more about computer vision software visit Blue Argus.

Browse our full Fairino lineup with current pricing and specs.

FAQ

What is mixed case palletizing?

Mixed case palletizing is the process of stacking cases of different sizes onto a single pallet in a stable, space-efficient pattern. It requires real-time planning rather than fixed programming, because the dimensions and sequence of incoming cases vary. Vision-guided robotic systems handle this automatically by scanning each case before it is picked and planning the stack dynamically.

How fast can a robotic case palletizer work?

Speed depends on case weight, arm payload, and pallet pattern complexity. Vision-guided systems on capable hardware can reach several hundred picks per hour on straightforward single-SKU applications. Mixed-case palletizing runs somewhat slower due to the planning overhead, but consistently outperforms manual palletizing on throughput and eliminates the variability of human fatigue.

Do I need a structured light camera for case palletizing, or will a simpler camera work?

For mixed case palletizing with variable surface patterns, a structured light 3D camera is the standard choice. It produces accurate point clouds on patterned, printed, and reflective case surfaces that stereo cameras handle less reliably. For single-SKU palletizing where all cases are the same size and surface, a simpler 3D camera may suffice.