You’ve probably noticed how far item pickers have come these days. From picking random fruits off conveyor belts to handling those traditionally ‘hard-to-pick’ items, their abilities now stretch far beyond simple, uniform items.

Thanks to AI vision technology and over a decade in the pick and place industry, our Smart Item Picker has evolved well beyond its early days. It can now reliably handle some of the most challenging products out there.

In this article, we’ll explore five surprising product types our robots can pick, along with real-world examples and insights into how it all works.

1. Soft and delicate clothing items 

Loose clothing is known for being notoriously difficult for item pickers to handle. Clothing items are often delicate and can easily get sucked into the gripper if it relies on vacuum suction.

To avoid damage and make picking more reliable, garments are usually packed in thin plastic bags or bubble wrap. This protects the clothing item and gives it a more defined shape, making it easier to handle.

To handle clothes wrapped in plastic bags, we developed an algorithm that assesses the surface area of an item to identify spots with the highest probability of a successful pick.

The algorithm randomly samples different areas on the surface of the clothing item and assigns each one a score. The winning score is based on three key factors:

1. Surface flatness under the suction cup
2. Proximity to the item’s center
3. Available space for multiple suction cups

Areas with plastic wrinkles (which can break the vacuum seal) are automatically ruled out, while flatter regions are prioritized. If the item has carton labels, the algorithm gives preference to those areas as well, as they provide more stable suction points.

Once the optimal pick point is selected, our motion planning system generates precise approach and pick trajectories designed to minimize swing and reduce the risk of dropping the item. Combined with our fashion-specific suction cups, this approach ensures a secure grip and gentle handling, keeping each garment stable from pick to place.

2. Shiny, transparent packaging

Vision systems have a hard time fully “seeing” packaging that is clear or reflective. When edges aren’t clearly visible, it becomes difficult to identify reliable grasp points. This type of packaging is common for products like pens, toothbrushes, razors, and batteries.

While our models are trained to handle a large variety of challenging scenes, good lighting still remains essential for capturing high-quality data and maximizing detection performance in real time.

To further increase our robustness against challenging light conditions and reduce the dependency on the quality of the camera data, we are developing a new depth data processing pipeline that includes a deep learning model to improve the overall quality of the data without using extra hardware.

The pictures below show the potential of this new pipeline:

The picture above shows the depth data without the new process pipeline, containing many holes and noise.

After passing the data through our new deep learning pipeline, the output dramatically improved, producing smoother surfaces that more closely match the real item.

3. Oddly shaped & colorful toys

Picking up toys is challenging for robotic item pickers, as you might expect. Toys can be made of any material, come in any shape, and be of any size. Usually, that means no two items look the same on a conveyor belt or in a tote.

Packaging makes things even trickier. Light can bounce off colorful boxes, making it harder for the system to detect where to pick.

With AI vision and machine learning, the Smart Item Picker can adapt its grip on the fly to handle this wide variety. Lighting is, however, a critical factor here, as it directly affects the quality of the data used for calculations.

To improve item detection, our models are trained on a large variety of items and environments, allowing them to handle challenging scenes where lighting or data may be imperfect. As a result, we can often detect items even when reflections partially obscure in their centers or edges.

This adaptability is especially useful for toy makers, wholesalers, and e-commerce warehouses, where quick and accurate picking is crucial during busy times like the holidays.

4. Protective gaming cases

Even something as simple and straightforward as a sturdy gaming case can be hard for robots to pick. These cases are often covered in shiny cardboard sleeves that reflect light, making it hard for vision technology to ‘see’ where it can grab them.

If these cases are in totes where it’s cluttered or there are a lot of overlapping products, then it’s even harder from a vision and task-planning perspective. The system has to carefully plan how to approach and lift the item without hitting surrounding objects, which requires precise motion planning.

To tackle this, the Smart Item Picker uses deep learning models that are trained to recognize objects in shiny, reflective packaging. Just like with oddly shaped toys discussed above in the article, good lighting plays a key role here. While the system is trained to handle tricky scenes, having proper lighting helps it capture clean, high-quality data – making it much easier to find reliable grasp points, even in challenging conditions.

5. Lotion, shampoo and beauty products 

Beauty products such as makeup come in many different shapes, sizes, and packaging types. This makes sense considering they’re designed to appeal to a certain type of target audience. However, these variations may make it challenging for item pickers to do their job well.

For cosmetics and beauty products, we use the same algorithm described in the “soft and delicate clothing items” section. In short, the algorithm simulates how well the suction cup would stick to different parts of an item and rules out areas where the grip wouldn’t be secure, such as round edges or uneven surfaces.

This approach allows the Smart Item Picker to consistently pick oddly shaped items at the ideal location (for example, picking at the center of the beauty product below).

This is especially important in the beauty and personal care industry, where large volumes of different-sized and shaped items are sold. Logistics teams in this industry can then rely on the Smart Item Picker to consistently make successful picks.

How does vision work in item picking

To learn how item pickers decide what to pick and how to pick items, watch this video:

In short, the video shows how our AI agent uses both 2D and 3D data to make decisions based on the highest chance of success. You will see in the video that the largest and highest item in the tote was picked first.

The 3D color map then guides the robot’s pick order:
1. Green – pick first!
2. Yellow
3. Orange
4. Red

After each pick, a new image is captured to prepare for the next.

In short

Automating item picking can feel like a big risk for many logistics and e-commerce businesses. It’s natural to wonder: “Can it really handle all our different products?” or “What happens if something can’t be picked?”

As we’ve seen in this article, modern AI vision, task planning, and motion planning have come a long way. An important concept behind this advanced technology is that it is not gripper dependent. This means that if a customer requires a special gripper, we can still deliver.

By combining deep learning models that identify the best pick points to evenly distribute weight for gentle handling, along with advanced depth data processing to pick even the trickiest items, the Smart Item Picker can now handle a wide range of products – from soft clothing to shiny, reflective packaging.

For logistics teams, that means faster operations with little to no manual intervention. With technology like this, “hard-to-pick” items are quickly becoming a thing of the past.

The season has just begun. Back-to-school, Black Friday, Cyber Monday, and Christmas are all around the corner – and with them comes mounting pressure on warehouses. While customers expect fast and flawless deliveries, the reality behind the scenes is often very different: workforce shortages, rising costs, and increased error rates can quickly turn this season into a stressful challenge.

Don’t get us wrong, some warehouses and production centers are more prepared than others. But what remains true is this: having systems in place to handle surging order volumes, strict fulfillment SLAs, and ongoing labor shortages is the only way to get through the season with your customers behind you, rather than watching them abandon ship.

Picture this: a warehouse running perfectly on AS/RS cube solutions or robotic goods-to-person systems. That’s automation that has already transformed efficiency in many warehouses — so much so that some can’t even imagine going back. But with automated item picking, you take efficiency one huge step further.

Defining peak season

Peak season usually runs from the end of August through January, and sometimes even longer. But not every industry feels the pressure at the same time. Summerwear brands might hit their peak between April and July, while electronics brands often face it during the back-to-school rush.

The labor challenge

It’s not “news” that labor shortages are causing bottlenecks across Europe. While many European employers struggle to fill manufacturing roles, it’s becoming clearer that applicants simply don’t find these jobs attractive. They simply have opportunities to apply their skills elsewhere.

In fact, according to the 2023 EURES Labour Shortages and Surpluses in Europe report, even when the required skills exist, employers still fail to attract applicants due to poor working conditions or uncompetitive job offers.

And it’s not just in reports or studies. Most of our customers come to us because of labor shortages. Take Melitta, the famous German coffee brand or Packservice for example, their main reason for automating their end-of-line was simple: they couldn’t find people to do the job. And that’s not only during seasonal peaks. That’s all year round.

Automated picking technologies to the rescue

With technologies like AMRs, robotic goods-to-person, and AS/RS all around to enhance and optimize work, it might be worth looking into item pickers. Automated item pickers can be integrated with AS/RS, cube storage, or even AMRs to fulfill orders. They can pick an item and place it into a shipping box, transfer it into another tote, or put it directly onto a conveyor belt.

Our item pickers are fast, lifting up to 1,000 items per hour. They handle products gently and don’t require pre-training, thanks to our AI vision sensors. In other words, it can pick and place an item it has never seen before exactly where you need it. On top of that, our solution comes with integrated barcode scanning.

Plan smarter with automation

Peak season should never feel like a burden or cause anxiety for organizations. Yet too often, warehouses scramble in September, desperately patching up process gaps. The smart way? Plan months before your expected peak. By analyzing last year’s data and pinpointing where the bottlenecks were, you can fix weak spots before they slow you down again.

From seasonal fix to long-term strategy 

The beauty of automated item picking is that it’s not just a seasonal Band-Aid. When peak volumes drop, your systems don’t sit idle, they keep delivering consistency and efficiency all year round. This is how you shift from firefighting during peak season to building a fulfillment backbone that scales with your business.

In other words, automation shouldn’t just show up in a crisis, it should be thought through and planned months before peak season.

Benefits of smart picking during peak season

Three things come to mind when you think about automating your item picking: consistent output, reduced reliance on labor, and scalable fulfillment that grows as you grow.

Consistent output

Manual picking is unpredictable. Performance depends on the time of day, how long a worker has been on shift, or whether they’re seasonal, temporary, or full-time. With automated item picking, you get the same speed and accuracy on order 1 as you do on order 10,000. That means fewer mispicks, fewer complaints, and fewer headaches when customers expect perfection during peak.

Reduced reliance on labor

Hiring temporary workers for peak season sounds good on paper, until you realize how much time and money it takes to recruit, onboard, and train them. And even then, turnover is almost unavoidable. Automation cuts that cycle out completely. Instead of chasing staff, you let the system do the heavy lifting, literally and figuratively.

Scalable fulfillment

This is where automated picking shines. Whether orders double or triple, automated item pickers don’t get tired. They simply keep going. And once the season slows down, they keep adding value by running your daily operations with the same efficiency. In other words: you’re not investing in a seasonal fix – you’re building a scalable backbone for growth.

The future of seasonal fulfilment 

Seasonal peaks will always be there. What changes is how prepared you are to handle them. Warehouses that rely purely on manual labor will keep facing the same challenges: delays, errors, unhappy customers. But those that embrace automation, AI, and data-driven strategies can turn seasonal chaos into a smooth, scalable operation.

At the end of the day, the question isn’t whether peaks will test your operations. It’s whether your systems are ready to rise to the challenge.

Imagine running a facility manually, only to find out that automating your end of line can increase throughput per hour by around 200% – 400%. Not only that, but it reduces your reliance on finding new labor, manage increasing costs, and decreases product damage.

In fact, studies show that up to 10–11% of pallet loads arrive damaged, and around 12.5% of product damage is pallet-related, which highlights the risks manual palletizing creates.

In this article, we’ll showcase (with real-life examples!) how automating your box palletizing can significantly increase the efficiency and productivity of your facility.

The hidden costs of manual palletizing

Many warehouses choose to automate their end-of-line for reasons such as:

1. 1. Constantly needing to hire and train new staff, only to lose them soon after due to health issues or the repetitive nature of the work.
   2. Rising labor costs that don’t translate into higher output or improved consistency.
   3. Quality and throughput varying from shift to shift, creating inefficiencies and delays.
   4. Growing pressure to meet faster delivery schedules that manual palletizing simply can’t sustain.

These are hidden costs many businesses don’t have a spreadsheet for to monitor, but it can heavily hinder the profitability of the company.

How automated box palletizing works

Simply put, automated box palletizing uses a robotic arm with a gripper, sensors, and intelligent software to lift each box from the conveyor and place it gently onto the pallet.

Reducing product damage 

Every movement of the automated palletizer is carefully controlled, gripping each box securely and placing it gently onto the pallet. The result is a neat, stable stack where every box is exactly where it should be and weight is evenly distributed to prevent shifting in transport.

In short, the gentle handling and precision of automated palletizing mean every pallet arrives just as perfect as when it left your line.

Boosting efficiency & output

With companies like Heinerle Berggold finding that automating their palletizing could cover almost three employee shifts, it was almost a no-brainer for them to start automating.

With automated palletizing, you can achieve virtually no downtime; simply because the robot doesn’t get tired, need a bathroom break, or call in sick. On top of that, output increases significantly, as one robot can palletize up to 1,600 cases per hour (more than double what an operator can do). And if your products change or sizes need updating, the team can easily use the Online Product Editor to make adjustments in no time.

In fact, one of the core reasons the Smart Palletizer was chosen over other solutions, according to the German bakery Lebkuchnerei Woitinek, is the system’s user-friendliness. It’s almost as easy to operate as a smartphone.

ROI and competitive advantage

Investing in automated palletizing delivers a return you can measure. By reducing the returns based on product damage, you cut unnecessary costs and protect your margins.

Furthermore, faster, more consistent fulfillment keeps customers satisfied and service levels high, strengthening your reputation. And with a system that can easily scale as your business grows, you’re not just solving today’s challenges; you’re building a competitive advantage for the future.

Implementation considerations

Before you invest in automated box palletizing, it’s important to think through a few key factors. It doesn’t have to be complicated—and at Smart Robotics, we make sure it isn’t.

We’ll assess your floor space to ensure the solution fits seamlessly into your layout, and we’ll handle integration with your existing or new equipment and software so everything works together without disruption.

Our cobot palletizer is designed with safety at its core, using vision and motion sensors to prevent collisions with operators. We can also implement additional safety measures, such as light curtains, to create an even safer working environment.

And when it’s time to go live, we provide hands-on staff training so your team feels confident and ready to get the most out of the system from day one.

Bottom line

Automating your box palletizing is absolutely necessary to stay ahead in this competitive market. Labor is short, retraining costs are high, and manual processes create bottlenecks that slow down your entire operation. With automated palletizing, you gain reliability, higher output, and flexibility — all while reducing dependency on scarce labor. In short, automation is no longer a nice-to-have, but a must-have for long-term competitiveness.

Automation and AI adoption have become one of the most – if not the most – important topics in the workplace. And when it comes to warehouse automation, adopting these technologies is becoming critical for maintaining efficient operations, especially with ongoing labor shortages and the pressure to stay competitive.

Yet, for many warehouse managers, the road to adopting these technologies is often clouded by misconceptions and fears.

At Smart Robotics, we’ve seen firsthand how these myths can hold businesses back from becoming more efficient, more flexible, and more competitive. In this article, we’ll help separate fact from fiction.

1. “Automation is too expensive and only for big players.”

Myth: Adopting automation and AI in the warehouse comes with price tags that only big corporations can afford.

Reality: Automation isn’t just for the big corporations. In fact, around half of our customers are SMEs. Small to medium-sized companies like Vandemoortele, and even family-run businesses like Lebkuchnerei Woitinek, have successfully implemented our technologies to make their operations more efficient and future-proof.

Thanks to flexible purchasing options — including our “automation-as-a-service” model — many companies achieve ROI in less than two years, and sometimes within months, thanks to reduced labor costs, fewer errors, and faster throughput.

In short: Automation isn’t just for the big players; small and medium-sized companies are proving every day it’s affordable, fast to implement, and pays for itself quickly.

2. “Automation will replace human jobs.”

Myth: Once automation is adopted and AI is up and running, people will be out of work.
Reality: Automation doesn’t remove employees from a warehouse; it reallocates them to more fulfilling roles. Many operators we’ve spoken with say that repetitive, physically taxing tasks often have them contemplating leaving the job altogether.

When automation comes in to play, workers are freed to focus on more rewarding aspects of the job, such as quality control, system supervision, and customer service. This shift improves job satisfaction, reduces health risks, and naturally extends how long employees stay with an employer.

In short: Automation doesn’t replace people. It makes them do safer, more rewarding work they actually want to stay employed for.

3. “Automation makes operations inflexible.” 

Myth: If I automate, my processes will be locked in and unable to adapt.

Reality: Today’s automation is built for agility. Even traditional palletizing systems can now handle changing product sizes and weights on the fly. Technologies like automated item picking adapt to new inventory all the time, without any pre-training.

In short: Today’s warehouse automation and AI are designed to be flexible, adjusting seamlessly to ongoing changes in inventory and demand. It’s as flexible as you need it to be.

4. “You must overhaul your operations to use AI.”

Myth: You need to stop or slow down operations to implement automation or AI.

Reality: You do not need to shut down or overhaul your warehouse to get started. You can start small. Many AI-driven solutions integrate with your existing setup and workflows, and can be installed while operations are still running.

In short: You don’t need a full-scale overhaul to adopt AI. Start small, keep moving, and build from there.

5. “Automation and AI are the same thing.”

Myth: Automation and AI are just two different words for the same type of technology.

Reality: While automation and AI can work together, they’re very different. Automation executes tasks with little or no human intervention, but it requires prior setup. AI, on the other hand, adds on-the-fly decision-making and adaptability to those tasks.

When combined, they create a warehouse that not only works faster, but works smarter.

In short: Automation gets the job done. AI makes it flexible and adaptable, fast. Together, they transform how your warehouse works.

6. “It’s too complex for my team.”

Myth: Advanced technology requires advanced in-house skills.

Reality: Many systems are as simple to operate as a smartphone. Modern automation is designed with the user in mind — intuitive interfaces, guided setup, and thorough operator training mean your team can get up and running quickly.

In short: You don’t need tech experts to run modern automation. If you have learnt how to use a smartphone, you can learn how to operate automation machinery.

Common fears to address

Even after the myths are cleared, it’s natural to have concerns. Here’s how you can address them and move forward with confidence:

Job security – Clear communication with employees helps avoid job insecurity and low morale. Be transparent about what’s happening, how roles will change, and what the timelines look like.

AI mistakes – To see if automation will work in your specific environment, many businesses feel more confident starting with a pilot project before full deployment.

Cybersecurity – When talking to vendors, ask about their cybersecurity protocols so you know exactly how your data and systems will be protected.

Workflow disruptions – Our team comes straight from the logistics and warehouse sector, so we understand how damaging disruptions can be. At Smart Robotics, we work with you to create an implementation plan that keeps disruptions minimal to non-existent, so your business keeps moving while we apply automation.

Resistance to change – When implementing automation or AI, it’s smart to involve the teams early. Celebrate wins together. Working towards something great as one team can make change feel more exciting and less intimidating.

Bottom line

Automation and AI are not here to replace human work. They’re here to take away the boring, repetitive tasks so people can focus on more value-driven roles.

The warehouses of the future will be hybrid environments where people and technology work together, not against each other. The sooner we embrace that reality, the sooner we can unlock simpler, smarter, and more productive operations.

If you work in production, manufacturing, or logistics, a big part of your end-of-line process is probably palletizing. But a question remains: with all the options available in the palletizing market, which palletizer is right for your business?

Considering factors like space available in your facility, budget, speed and throughput needs, this article will dive into which palletizers can do what, and which one is right for your business.

What is a robotic palletizer?

A robotic palletizer is an automated system that uses a robotic arm to stack products such as boxes, cartons or bags onto a pallet. The system combines intelligent software with precise hardware to grip, lift and place items in a defined stacking pattern, offering a flexible and efficient solution for end-of-line automation.

Key features of a robotic palletizer:

Robot arm: To stack products neatly and reliably, a 6-axis robotic arm is typically used. It gives the flexibility needed to move and orient each product into the right position on the pallet.

Gripper end-effector: Often referred to as the hand of the robot, the end-effector gripper uses suction to lift products. Most robotic palletizers use either a vacuum or forklift-type gripper to handle different types of cases, whether they’re open, closed, taped, or glued.

Sensors: Robotic palletizers use AI-driven sensors to avoid collisions and handle products gently. Force and proximity sensors help the robot understand how firmly to grip a box and how close it is to the product before picking it up.

Software: Every palletizing system relies on software to control the robot’s movements. These movements are configured based on product size, weight, stacking pattern, and any specific palletizing needs.

At Smart Robotics, we’ve developed our software in-house to give customers full flexibility, whether they need a single setup today or want to scale and adapt in the future.

What is a gantry palletizer?

Unlike robotic palletizers, gantry palletizers use components like conveyors and pushers to arrange items into layers before stacking them on a pallet.

They’re typically built for high-throughput palletizing (often 2,000 cases per hour or more) and work best with products that stay the same in size and weight. But if anything changes, like the product dimensions or stacking pattern, reconfiguring the system is usually complex and takes time.

Key components of gantry palletizers:

Frame: The frame is the mounted structure that supports and allows the movement of the system along the X, Y, and Z axes. Typically, it is installed above the work area to give the gantry access to multiple pallet positions across the workspace.

Linear drive system: This system controls the linear movements of the gripper or tool head.

Gripper: The gripper is known as the “hand” of the machine. Most gantry systems use a vacuum or clamp-style gripper to pick up products and place them onto the pallet.

Product infeed conveyor: This conveyor moves products to the pickup zone. It works in sync with the gantry to make sure each item is in the right position at the right time.

Pallet station: This is where the gantry stacks products. Some systems support multiple pallet stations to reduce downtime.

Controls and software: The software manages everything from movement to stacking patterns and system configurations. It’s the core of the operation and can be adjusted to match your specific palletizing needs.

Safety area: Gantry palletizers are not collaborative systems, so they require safety fencing or barriers around the work area to protect operators during operation.

What are the pros and cons of robotic palletizers?

Now that we’ve covered what robotic palletizers can do, it’s worth looking at the benefits and drawbacks of using one.

Benefits of a robotic palletizer

Highly flexible systems: Robotic palletizers adapt easily to changes in product size, weight, or stacking pattern. If you introduce a new SKU or switch to a heavier box, the system can be quickly reprogrammed to handle it with no gantry changes needed.

Small footprint palletizer: Compared to gantry palletizers, robotic palletizers take up far less space. A typical setup fits within 2.5 x 3 meters, while gantry palletizers often need 8 x 5 meters or more. That larger footprint includes the space needed for layer-forming zones, pushers, conveyors, and safety access areas.

A typical setup fits within 2.5 x 3 meters, while gantry palletizers often need 8 x 5 meters or more. That larger footprint includes the space needed for layer-forming zones, pushers, conveyors, and safety access areas.

Safety: Robotic palletizers that use collaborative applications comply with ISO 10218-2 and are safe to use.

They slow down when someone comes close and stop if they come into contact with anything unexpected, like an operator. They also reduce the need for manual picking and placing, which helps prevent strain and back injuries on the work floor.

Lower maintenance and costs: Robotic systems are compact, have fewer moving parts (like pushers and conveyors), and run on simpler software compared to gantry machines. As a result, they experience less wear and tear and typically require less maintenance over time.

Drawbacks to owning a robotic palletizer:

Cost of investment and operation: Both gantry and robotic palletizers require a similar upfront investment, though robotic systems typically cost less to maintain over time. Robotic systems also take up less space and are easier to adapt, which helps reduce the overall cost of ownership.

Requires professional setup: To set up a robotic palletizer properly, programming expertise is needed.

At Smart Robotics, our service team handles that from start to finish. From the moment the system is approved to the moment it’s up and running at the customer’s site, the team makes sure everything works as it should and stays that way.

Payload limitations: Robotic palletizers using cobot applications typically handle up to 30 kg per product.

That’s more than enough for most operations. But if you need to lift products heavier than that, you can look into mixed-case palletizers that are designed for higher payloads and stacking different product types on a single pallet.

Gantry palletizers are also an option, but they don’t offer the same flexibility as robotic or cobot systems.

Robotic palletizers vs gantry palletizers

Compared to traditional gantry palletizers, robotic palletizers offer a far more flexible and space-efficient solution. While gantry systems are rigid and limited in their application, robotic palletizers are easily programmable and highly adaptable to different product types and layouts.

They require minimal maintenance, consume less energy, and can deliver a return on investment within 6 months to 2 years, significantly faster than the 2–5 years typically seen with gantry setups. For businesses seeking a compact, future-proof palletizing solution with lower long-term costs, robotic palletizers offer a practical option.

Which palletizer is right for your business?

Palletizing needs depend on your products, output targets, and the space you have available. Gantry palletizers are often used for high-speed stacking of uniform products, but they’re difficult to adapt when products change.

That’s where robotic and cobot palletizers have the advantage. They can handle different case sizes, stacking patterns, and workflows with minimal setup time. If you’re scaling up, updating SKUs, or working in a tighter space, a robotic palletizer offers the flexibility and ease of use that fits most operations today and tomorrow.

When considering automation, one of the first questions potential buyers ask is: How much will it cost? Not just the upfront investment, but the long-term costs too. Are there recurring expenses that keep showing up year after year?

Understanding the total cost of ownership (TCO) in automation is key to making informed, confident decisions before committing to any investment.

TCO includes all costs tied to the system, both at the time of purchase and in the years that follow. That means development, implementation, maintenance, support, and any ongoing services needed to keep things running smoothly.

By looking beyond the initial price tag, organizations can evaluate whether an automation solution will deliver lasting value and truly meet their operational needs.

In this article, we’ll break down what TCO means in the context of automation, drawing on our 10+ years of experience in the industry.

What’s included in the TCO of automation?

Many cost factors come into play when calculating the total cost of ownership. Let’s look at what’s involved:

System costs

The first thing that comes to mind when thinking about automation is the system itself: the hardware and software. In the case of (de)palletizing and item picking systems, this includes components like the robotic arm, gripper, and frame. In some cases, conveyor systems are also part of the automation solution and are included in the system costs. However, if the robotic system needs to connect to your existing conveyor setup, that would fall under integration costs.

And of course, none of it works without the right software. That’s where our in-house development team comes in. Thanks to their work, the system is easy to set up and ready for installation straight away.

Integration costs

Of course, a system on its own isn’t enough. You also need to factor in how it integrates with your current setup, or the one you’re aiming for.

Want the system to connect with software like WMS or hardware like AutoStore? That comes under the umbrella of integration costs.

Installation, maintenance, and training costs

Getting the system up and running properly at your site is key to a successful automation project. Training your team to operate the system and troubleshoot basic errors is just as important to keep everything running smoothly.

If you’re working with Smart Robotics, you don’t need to worry about separate training fees. We believe it’s essential to train your team on how to use the system when you purchase from us.

Maintenance costs help ensure your system continues to perform well for years to come. This includes preventive maintenance and software updates, if needed.

Servicing and helpdesk

In the unlikely event that the system stops and your team can’t fix it, our customer success team is ready to help. If you choose to subscribe to our online service and helpdesk, we can jump on a call or even resolve the issue remotely through our connection to the system.

In fact, more than 9 out of 10 calls are fixed on the spot. This helps our customers keep uptime high.

Are TCO and ROI related?

Yes, the total cost of ownership (TCO) and return on investment (ROI) are closely related. If you can identify the TCO of a solution, it becomes much easier to calculate the potential ROI for your business.

Of course, TCO is not the only factor when determining ROI. Things like time and money saved by the organization, fewer employee shifts, and increased production output also contribute to the overall return.

Curious about the TCO for your business?

If you’d like to calculate the total cost of ownership for automating a process like palletizing, depalletizing, or item picking, feel free to reach out. Our experts are happy to help you explore whether automation is the right fit, and what kind of return you can expect.

Cobots, or collaborative robots, have been on the market for a while, working together with people without the need for a fence to secure safety. With the new 2025 ISO/TS 15066 regulations, cobots are no longer classified as a separate type of robot. Instead, they’re considered a type of robot application.

One of the great advantages of working with a cobot application is the reduced need for floor space and the ability for humans to support cobots with complex tasks. But how do we guarantee operator safety when working in close proximity to a collaborative robot without a security fence?

Guaranteeing safety with a collaborative application (cobot in short) is defined in the ISO standards, requiring that contact between human and robot shall not result in pain or injury.

In this article, we’ll dive deeper into how you, as a cobot user, can make sure that safety is properly implemented in your operations.

Enabling power and force limits for cobot safety

There are multiple ways to limit power and force, but all of them boil down to measuring the moment of impact and stopping the robot as quickly as possible in such a situation. Until the robot has stopped and is de-energized, it should not have exceeded force and power limits, as defined in the available standards. Cobots accomplish this by having a low inertia (low moving mass) and moving at limited speeds.

In addition to force and power limits, the cobot’s (and gripper’s) geometry needs to be properly designed. It must have rounded edges and no clamping possibilities near the joints.

The most common way to limit the power and force of a cobot is through measuring the force applied to the environment, derived from the motor current or torque sensors found in the robot’s joints. In other words, this method gives the robot insight into both intentional and accidental contact, including forces transmitted through the object it is holding.

For example, when picking up a 10 kg box, the robot must be informed of the weight so it can adjust its internal safety thresholds accordingly. At the same time, it must ensure that its safety functions comply with ISO 10218-2:2025 requirements, meet specific performance levels (e.g., PL d / SIL 2 for speed monitoring), and undergo proper risk assessment validation.

Quasi-static vs. transient contact with a cobot

The cobot’s safety PLC continuously monitors speed and force, but it is up to the robot integrator to ensure that the speed and force limit settings are appropriate for the specific application. To do this, the integrator must consider two types of physical contact: quasi-static and transient.

• Quasi-static contact refers to situations where a part of the body becomes trapped or clamped between the robot and another surface. These are slower, sustained contacts where the robot presses against the human body. ISO 10218-2:2025 (previously ISO/TS 15066) defines maximum permissible pressure and force for each body part in such cases. For example, the palm of a person’s hand may be subjected to a maximum pressure of 260 N/cm² and a maximum force of 140 N.
• Transient contact addresses situations in which the robot hits the operator with a short impact. These contacts are momentary and do not involve clamping. The standard also defines maximum permissible values for transient contact, which are typically twice as high as those allowed for quasi-static contact.

Analyzing cobot safety according to ISO 10218-2

There are two main ways to determine whether a robot application fulfills safety requirements:

• Empirical validation: measuring pressure and force at all critical points and scenarios using a certified tool. Many companies offer these tools along with consultancy services to perform these measurements.
• Theoretical analysis: applying formulas provided in ISO 10218-2:2025 to calculate maximum allowable speeds, torques, and forces for the specific robot configuration.

In practice, integrators often apply general design rules to ensure a safe setup. For example, using only mechanical parts with rounded corners (e.g radius ≥ 5 mm), limiting robot speed, and capping applied force, can significantly reduce the most common risks.

Note: The updated standard places greater emphasis on application-specific validation: each collaborative setup must be assessed based on its environment, use case, and the configured safety functions. Functions like monitored standstill (formerly known as safety-rated monitored stop) and reduced speed mode must meet the required performance levels.

Protecting the head while working with cobots

A difficult part in each safety analysis is possible contact with the head of an operator. The new standards still do not give practical advice on this topic. One way of dealing with this is a zero-risk policy, in which the cobot is typically fenced off to prevent contact with the head. However, this diminishes all advantages and flexibility that a cobot gives. One could then better use a standard industrial robot at higher speeds.

Hence, most integrators choose to use common sense to analyze this risk. They position the robot in such a way that contact with the head is prevented as much as possible.

A high-speed cobot solution

If you’re a cobot user looking to operate at higher speeds, it’s possible under one key condition: using safety scanners and light curtains in the cobot’s working zone.

These safety devices ensure that when an operator enters the area, the cobot is immediately alerted and slows down to a safe speed.

Cybersecurity and new functional requirements

ISO 10218-1:2025 introduces cybersecurity requirements for collaborative applications. Systems must be protected against unauthorized access, manipulation, or tampering. Every cobot setup must include emergency stops, hand detection sensors, and speed and separation monitoring systems.

These safety functions must meet defined performance levels (e.g., PL d / SIL 2), and all potential hazards must be addressed through a thorough risk assessment.

Final thoughts

Safety standards are essential for guiding cobot implementation, but common sense remains one of the most important tools at your disposal. By integrating force validation, cybersecurity, and performance-level requirements, you can ensure a compliant, safe, and flexible setup, just as ISO 10218:2025 helps enable.

Stacking cases of different sizes and weights onto a pallet can be a challenging task to accomplish. It’s almost like playing real-life Tetris – although it can be fun and challenging, people naturally need to slow down and think: what to stack when, and where? That costs businesses money. That’s where automated mixed case palletizing comes in.

Mixed case palletizers speed things up by using AI and intelligent sensors to stack mixed cases faster and more consistently than any operator can.

In this blog, we’ll give you a deep dive into 5 ways mixed case palletizing is helping improve the overall supply chain, starting with:

1. Boosting end-of-line efficiency

Operators manually palletizing mixed cases constantly have to think about how to place each case to keep the pallet stable and use space efficiently. On the other hand, robotic mixed case palletizers use AI to process data and make quick stacking decisions. The software instantly calculates the optimal stacking pattern – much faster and more consistently than a human can.

This not only speeds up the workflow, but also reduces downtime caused by fatigue or errors — getting goods out the door faster and keeping customers happy.

2. Cutting down the number of lines you need

Most palletizing setups keep lines separate so that each one handles products of the same size and weight.

Thanks to mixed case palletizers, facilities can run a single line of different products – not worrying about the weight or size.

Having just one (or only a few) line(s) running products with different sizes and weights dramatically reduces costs of infrastructure, maintenance, and overall footprint.

3. Reducing labor strain and injury risk

Manually palletizing mixed cases often means repetitive lifting, sometimes in awkward ways. That adds up and can take a toll on workers over time, especially when lifting heavy cases over the head.

Mixed case palletizers come in to take over the heavy, repetitive work, helping reduce the risk of injuries on the floor. This doesn’t just improve worker safety; it also helps companies comply with the new strict EHS regulations, especially in Europe.

4. Keeping pallets stable during transport

When a pallet travels long distances, you want to make sure it’s stable enough for the journey. Mixed case palletizers don’t just make decisions based on size, they also consider box weight and fragility to build a balanced pallet.

This lowers the risk of damage during transit and helps prevent pallets collapsing on the warehouse floor.

5. Increasing flexibility for retail and e-commerce

A T-shirt, sunscreen, and a pen, all in the same order? These days, that’s the norm.

Retail and e-commerce orders are getting smaller, more frequent, and more varied. Mixed case palletizers make it easy to stack different SKUs on the same pallet, so there’s no need for separate lines or setups.

Whether it’s beverages, snacks, or electronic products, mixed case palletizers adapts to different product sizes and stacking patterns on the fly.

Key takeaway

Mixed case palletizing brings real, measurable improvements to warehouse operations. It reduces the number of lines needed, lowers your footprint, and cuts infrastructure costs, all while increasing throughput and overall output.

No surprise, then, that more and more facilities are choosing mixed case palletizers over traditional single-SKU systems.

An end-effector is the tool that sits right at the end of a robotic arm, basically, the robot’s hand. It’s what allows the robot to interact with its surroundings. Whether it’s gripping, placing, welding, or scanning, this is the part allows the action to be fulfilled. For example, in a pick-and-place setup, the end-effector needs to grab an item, hold it securely, and place it exactly where it needs to go.

Automation is taking over many repetitive, and often dangerous, tasks today. Moreover, the number of end-effectors available now is likely in the hundreds, and it’s still growing. End-effectors are getting smarter, more specialized, and more adaptive each year.

With that in mind, here’s everything you need to know about the various types of end-effectors: how they work and the role they play in industrial automation.

What are the types of end-effectors used in robots?

End-effectors generally fall into three main categories: grippers, process tools, and sensors. The choice between them depends heavily on the application.

Pick-and-place tasks usually require a type of gripper, while process tools are used in tasks like welding or painting. In fast-moving or unpredictable environments, sensors often help end-effectors perform their jobs better.

End-effector grippers

Mechanical Grippers – These are finger-like grippers, similar to how a human would pick up an object. They’re widely used in sorting and assembly applications, moving products from one place to another.

• Note: Mechanical grippers are simple, reliable, and cost-effective but may not be suitable for handling irregularly shaped objects.

Vacuum Grippers – Using suction cups and vacuum air, these grippers securely lift products. They became popular after mechanical grippers, especially in industries looking for faster cycle times and greater versatility. Applications like palletizing, depalletizing, and item picking all rely on vacuum grippers.

• Note: Vacuum grippers are easy to use, highly reliable, and have a fast cycle time but may not be suitable for handling heavy or non-porous objects.

Magnetic Grippers – These grippers use magnetic fields to lift and transport metal parts. As industries like automotive and metalworking expanded, magnetic grippers became essential for handling ferrous materials quickly and safely—while minimizing the risk of scratches or damage.

• Note: Magnetic grippers are highly reliable and require minimal maintenance but may not be suitable for handling non-ferromagnetic materials.

Servo Grippers – Unlike traditional open/close grippers, servo grippers allow precise control over grip position and force. This makes them ideal for handling delicate or varied objects, such as soft packaging, electronics, or glassware. 

• Note: Servo grippers are highly precise and flexible but may be more expensive and require more complex control systems.

Each type of gripper comes with its strengths and trade-offs. Choosing the right one depends on the object being handled, the required speed and precision, and the work environment.

Sensors in end-effectors

Without sensors, an end-effector is essentially a blind tool—only capable of repeating pre-programmed movements. But with sensors, robots gain the ability to react to their environment and make decisions on the fly. Sensors are particularly valuable in unstructured or constantly changing environments.

Here are the most commonly used sensor types:

Vision Sensors – These sensors use cameras and 3D scanners to provide the end-effector with critical visual feedback—such as where to move, what to pick (if applicable), and how the object is oriented. They’re also essential for navigating environments without causing collisions. This makes vision sensors crucial for any application that requires precise positioning and manipulation, like pick-and-place tasks.

Proximity Sensors – These help detect how close or far an object is. That gives the robot the ability to pause or adjust if it’s nearing a restricted zone, and improves positioning alongside vision data.

Force/Torque Sensors –  These are often integrated into end-effectors to measure how much force is being applied during a task. This is essential for handling delicate objects without causing damage and for performing tasks that require a precise amount of pressure.

Light Sensors – While not as common as vision systems, light sensors can support alignment and positioning. They detect changes in light or surface marks, helpful in environments with low visibility or where edge detection is needed.

Magnetic Sensors – These detect magnetic fields and are often used in metal handling or position tracking. They’re especially useful where other sensors might struggle in dusty or low-light settings.

Range Sensors – These measure the distance between the end-effector and nearby objects. That’s useful for collision avoidance, positioning, or path correction.

Applications of end effectors

Many tasks, especially those that are repetitive, hazardous, or tedious, can be automated using robots equipped with end-effectors.

Manufacturing – End-effectors are used across manufacturing—from assembly tasks using mechanical grippers to material handling using suction cups. For example, robotic arms with process tools like welders or drills take over hazardous jobs and leave safe tasks for human workers.

Food and Beverage Industry – End-effectors are essential in automating packaging, sorting, palletizing, and depalletizing. With the right sensors and grip strength, they can handle fragile or perishable items without damaging them. This is key for ensuring product quality and food safety.

Healthcare – In industries like pharma, end-effectors handle tasks such as packaging medication or preparing doses with high precision, eliminating the risk of human error. In surgical or rehabilitation settings, robotic tools support patients with mobility exercises and help them get back on track.

Agriculture – Traditionally done by farm workers, tasks like harvesting, plant care, and seeding are now being automated using end-effectors designed specifically for agriculture. These tools often include grippers and cutting mechanisms that gently handle fruits and vegetables without causing damage. With built-in vision and sensor guidance, they ensure crops are picked efficiently and with care.

Construction – In construction, end-effectors are used to automate tasks that are usually hazardous, such as bricklaying, welding, drilling, and material handling.

Robotic systems equipped with custom grippers or suction cups can lift heavy building materials like concrete blocks, glass panels, or steel beams and place them with precision. These tools increase safety, reduce manual strain, and ensure consistent quality on construction sites.

Logistics – End-effectors are at the core of modern warehouse automation. Whether it’s picking products off shelves, placing items into bins, or palletizing boxes, grippers (especially vacuum-based) speed up processes and reduce human strain.

Automotive – Robotic systems in automotive rely heavily on end-effectors for precision assembly. They’re used to weld car frames, install components like windshields, and lift heavy parts of a car. Depending on the task, end-effectors range from magnetic grippers to welding torches.

How to choose the right end effector?

When picking the right end-effector, it all comes down to what the robot needs to do and how it needs to do it. Here’s what to keep in mind:

Task requirements: Start with the basics. What task do you need the robot to perform? Picking, placing, welding, sorting? What’s the required speed and level of precision? The answers will help you narrow down your options.

End-effector capabilities: Once you’re clear on what the end-effector needs to do, start looking into which tool best fits the task. For example, if you’re automating a palletizing process, a vacuum gripper is a great choice for sealed or taped cases—but it won’t work well for crates or open boxes.

Want to talk it through with automation experts? Book a call with us today.

Compatibility with the robotic system: The end-effector needs to integrate seamlessly with your robot—mechanically, electrically, and through the control software. There’s no value in choosing a great end-effector if it doesn’t communicate properly with your setup.

At Smart Robotics, we deliver complete solutions, including the robotic arm, software, frame, and end-effector integration, so you can leave that part to us.

Maintenance and repair: Choose an end-effector that is both reliable and easy to maintain. Downtime on a production line or in a warehouse quickly translates to lost time and revenue, so durability and ease of servicing are key.

Many systems don’t offer much support after installation, but at Smart Robotics, we do. Our service team is available for everything from remote diagnostics to on-site troubleshooting, so you’re never left without help when you need it.

Cost: When selecting an end-effector, it’s important to look beyond the upfront price and consider the overall value it brings. Think about how well it performs, how long it will last, and what additional components might be needed for integration.

Also factor in the cost of installation, daily operation, maintenance, and the potential impact of downtime. The right end-effector should deliver consistent, long-term value—not just a lower initial cost.

In short

End-effectors may be just one part of your automation system, but they play one of the most critical roles. From precise placement in high-speed palletizing to delicate handling in agriculture or pharma, the right end-effector determines how effective (and reliable) your automation really is.

At first glance, it seems like one robot and one software configuration should be able to palletize and depalletize products from a pallet.

But is that really the case? Can you deploy a single robot in your facility to manage both stacking and unstacking products, or do these two tasks require different solutions?

Considering the differences in placement within a facility and the unique requirements of each task, we can come to a better understanding of these two automation roles.

In this article, you’ll gain a clearer view of what’s required for both procedures, and which approach makes the most sense for your logistics.

Let’s dive in, starting with…

The definition of palletizing

Palletizing is the process of systematically stacking packaged goods (such as taped boxes or crates) on a pallet, ready to be shipped.

Robotic palletizing takes it a step further by using robotics to handle the task, either stacking products layer by layer or unit by unit.

In some facilities, palletizing is still done manually. An employee lifts packaged products from the end of the production line and stacks them onto an empty pallet. This is physically demanding work, and it’s no surprise that employee turnover is usually high in those environments.

However, as automation continues to rise and logistics companies face ongoing labor shortages, robotic palletizing is becoming more prominent. It’s especially valuable for companies with high throughput and a need to get products out the door fast.

The definition of depalletizing

Depalletizing is exactly the opposite of palletizing; it’s the process of unloading packaged goods from a pallet. This usually happens when a freight truck arrives full of pallets that need to be emptied.

From there, the products can be placed onto a conveyor belt at the start of the production or manufacturing line or onto another pallet (a process known as repalletizing).

As you can imagine, this task can be very physically demanding on the employees, constantly lifting and placing products onto conveyor belts for hours on end each day.

The similarities between palletizing and depalletizing

Yes, there are some similarities between palletizing and depalletizing, and it’s worth highlighting these before jumping into the differences:

• Both applications can be done with the same robot. One of our palletizers, the Smart Mixed Case Palletizer, can easily handle both palletizing and depalletizing tasks.
• They are both classified as pick-and-place jobs: very repetitive and monotonous work no one wants to do.
• They’re often a huge hurdle to production and logistics facilities, mainly due to inefficiencies caused if these tasks are done manually.
• The installation procedure for both applications takes around the same time and follows the same integration procedure. The only difference is that a depalletizer needs a top-mounted camera for vision, which adds a bit more time compared to a palletizer.

Key differences between palletizing and depalletizing

Now that we’ve discussed the similarities between palletizing and depalletizing, let’s take a look at the differences:

Depalletizing challenges

When a robot stacks a pallet with identical boxes, it knows exactly where to place them thanks to predetermined stacking pattern technology. This means the machine, even without a vision system, can pick up the packaged product and know exactly where to place it.

There is still some thinking involved, like determining the ideal spot to place the product. But for the most part, for a single SKU palletizing solution, it’s all predetermined.

Mixed case palletizing usually does not use vision to place products on a pallet but relies on intelligent software to figure out the best stacking pattern. Vision can be applied for real-time validation or adjustments, but it’s not an absolute requirement.

However, depalletizing is a bit more complicated because of…

Items moving during transit

During transit from one facility to another, products can shift and move—especially if they weren’t secured well enough with shrink wrap. This can cause problems for a visionless robot, which relies on picking up goods from an exact position. If the products have moved even slightly, the robot will likely encounter an error and won’t be able to do its job properly.

Different locations and processes in your facility

Commonly, palletizing and depalletizing processes happen in different areas of the facility. Palletizing happens at the end of the process, after packing cases, sealing, and taping, when the product is ready to be placed on a pallet and shipped.

On the other hand, depalletizing happens at the beginning of a facility’s process, in the inbound phase. Depending on the type of facility, this usually happens when packaged products arrive and need to be unpacked and sorted to start their journey through the production line.

Sometimes, two robots, one handling the palletizing process and one handing the depalletizing process, can work side by side in the same location in the facility.

But that depends on the type of solution a facility needs. You can contact us today for a free, customized solution for your business.

How to decide if you need a palletizing or depalletizing solution

One of the most common questions we get is this: should I start automating with a robotic palletizer or depalletizer?

The answer depends entirely on your facility’s needs.

Start by asking yourself these questions: –

• Where do bottlenecks usually occur in my process? At the start of my line or at the end of it?
• What is my throughput requirement; Do I need fast stacking or fast unstacking?
• Am I dealing with labor shortages in one specific area?
• Do I need the same robot to do both tasks?

Take a look at our palletizing and depalletizing solution pages. If you still have questions or would like more information about either solution, feel free to contact our experts.

In Short

Palletizing and depalletizing both involve moving packaged goods on and off pallets. They share similarities in being repetitive, physically demanding tasks that can be automated.

However, the main differences come down to where they fit in your process and what the machine needs to do to execute the application successfully.

Robotic depalletizing usually requires vision in order to do it right, while automated palletizing typically doesn’t.