The robot moves. The gripper makes contact.

A robot may have the reach, payload and speed required on paper. But a poorly specified gripper can still cause:

• missed picks and operator interventions;
• crushed cartons, damaged bags or unstable pallet layers;
• slow robot motion caused by excessive tool weight;
• lengthy format changes;
• production stops caused by unreliable detection or poor product retention.

A line operating at 30 pick cycles per minute completes 1.800 cycles per hour. Even a 1% pick-failure rate creates 18 failed cycles in one hour – before the time required to recover the product, reset the cell and restart production.

Start with the real package – not a drawing

The first question should not be: Which robot should we use?

It should be: What exactly must the gripper handle, under real production conditions?

That means evaluating more than a product’s stated dimensions and weight. A robust gripper design needs to account for:

• actual package weight, including the heaviest permitted variant;
• centre of gravity and load stability;
• surface quality: dust, moisture, seams, holes, labels or porous cardboard;
• allowable compression or deformation;
• product presentation at the infeed;
• required pallet pattern and placement accuracy;
• current and future SKU range;
• environmental conditions, including hygiene, temperature and contamination.

A carton that looks identical in a CAD model may behave very differently on a production line after a supplier change, humidity shift or minor packaging redesign. The right solution is designed around the full operating range, not only the ideal sample.

Different products need different gripping principles

There is no universally “best” robotic gripper. The right principle depends on the package, the line speed and the level of flexibility required.

Vacuum and area grippers are often effective for cartons and other products with suitable surfaces. They can offer fast pick-and-place performance and, with properly designed vacuum zones, can handle some format variation. But material porosity, cut-outs, dusty surfaces and leakage must be evaluated properly.

Mechanical grippers use clamps, fingers or side-contact elements. They can be a strong option where vacuum is unsuitable, especially for irregular, porous or open products. The engineering challenge is to apply enough force for a secure hold without marking or deforming the packaging.

Fork and support grippers lift from underneath rather than relying only on surface contact. They are useful where product geometry, stability or load weight requires additional support.

Custom or hybrid grippers combine principles for complex applications: different packaging formats, mixed product flows, pallet layers, slip sheets or changing product dimensions.

Throughput is a trade-off, not a catalogue number

A larger gripper may lift more products in one movement and reduce the number of picks per pallet. But it also adds weight and inertia to the robot arm, which can limit acceleration and slow the cycle.

A smaller gripper may move faster, but it may require more picks.

The best answer comes from analysing the complete cycle:

1. product arrives at the pick point;
2. gripper positions and secures the load;
3. product presence is verified;
4. robot accelerates, moves and decelerates;
5. product is placed accurately;
6. gripper releases and returns for the next cycle.

The relevant metric is not the robot’s theoretical maximum speed. It is the sustained, verified output of the complete cell.

Reliability requires sensing, maintenance and safe failure modes

A good gripper does not only pick a product. It confirms that it has picked it correctly.

Depending on the application, that can include product-presence sensing, vacuum monitoring, position feedback and fault handling logic. The goal is to identify an incomplete or unstable pick before it creates a damaged load, a pallet pattern error or an unexpected stop downstream.

Gripper maintenance matters too. Worn suction cups, damaged seals, leaking pneumatic connections and misaligned contact surfaces can gradually reduce reliability long before a full failure occurs.

Safety must also be engineered at cell level. ISO 10218-2:2025 sets safety requirements for industrial robot applications and robot cells. A gripper is a moving, load-carrying component of that cell, so risks such as loss of vacuum, dropped product or unexpected motion must be considered in the overall assessment.

The right gripper makes automation flexible

Robotic automation is increasingly important in food and beverage, where the IFR recorded 20.792 food-industry robot installations in 2024, up roughly 42% from the previous year. But the value is not in adding a robot for its own sake.

It is in creating a packaging line that handles product variation reliably, maintains pallet quality, supports future formats and keeps the end of line from becoming the constraint on the rest of production.

The robot provides movement.

The gripper determines whether that movement becomes a reliable process.

Autonomous mobile robots, or AMRs, have moved from “interesting pilot project” to an increasingly established part of warehouse and manufacturing operations for exactly this reason. They don’t fix everything, but they solve a specific, recurring set of problems better than almost any other tool on the floor. Here are three of the most common ones, and what actually changes when an AMR fleet takes them on.

Labor shortages, turnover, and the safety risk that comes with both

Warehouse and manufacturing labor has been tight for years, putting additional pressure on companies to make better use of the workforce they already have. Repetitive transport tasks are a clear place to start. Moving pallets, materials, or components between storage, production, and shipping is essential, but it also takes employees away from activities where their skills and judgment create more value.

The safety picture adds pressure on top of that. Frequent movement of forklifts and other material handling equipment through areas shared with employees creates additional safety risks, particularly in busy production and warehouse environments. Every trip a person makes across a busy floor to move a pallet or feed a line is a small, repeated exposure to that risk.

AMRs take over exactly the tasks driving both problems: the constant back-and-forth transport of goods between storage, production, and shipping. A fleet built around units like a forklift-style mobile robot for stacking and transfer, or a conveyor-equipped unit that docks automatically with a production line, removes people from the most repetitive transport journeys on the floor.

That doesn’t mean replacing the workforce – it means the people you do have are picking, inspecting, and solving problems instead of walking pallets from A to B, which is a better use of increasingly scarce labor and can reduce employee exposure to repetitive material transport tasks and interactions with moving equipment.

Material flow bottlenecks and inflexible workflows

Fixed infrastructure is the quiet cause of a lot of material flow problems. Conveyors and rail-guided systems move goods efficiently along one path, but the moment volume shifts, a product mix changes, or a new line gets added, that fixed path can become the constraint. Changes in production volume, routing, and product mix can expose inefficiencies that were less visible when a system was first designed. Most of that shows up as exactly what floor teams already recognize: equipment waiting, congestion at pinch points, unnecessary travel, or storage that doesn’t match how goods actually move.

AMRs don’t need a fixed path. They navigate the space that’s already there, using sensors and mapping software to plan routes and reroute around obstacles or congestion as operating conditions change. That matters most in facilities with irregular layouts, under-rack storage, or narrow aisles where a conveyor or a wide industrial truck simply wouldn’t fit – this is the specific gap that low-profile, latent mobile robots are built for, since they can move underneath compatible racks and transport loads within space-constrained areas. When a production line moves, a new pickup point gets added, or a seasonal layout change comes through, routes and missions can often be reconfigured through software rather than through major physical modifications to fixed transport infrastructure.

Scaling up without a full infrastructure overhaul

The third challenge only shows up once a facility has actually solved the first two: what happens when volume grows, or a new product line needs its own material flow, or demand spikes for eight weeks a year and then drops back down? Traditional automation – conveyors, fixed racking, or transport systems designed around predefined routes and capacities – tends to lock a facility into whatever throughput and layout it was designed for. Scaling up can therefore require changes to physical infrastructure rather than simply increasing transport capacity.

Scaling an AMR fleet is closer to adding capacity than rebuilding infrastructure. Adding capacity for a busy season, a new SKU, or a second shift generally means adding units to an existing fleet and letting the fleet management software absorb them into the routing and task allocation it’s already running – rather than rerouting conveyors or restructuring a layout that was built around a different volume. That said, this is also the point where a lot of AMR projects get harder than expected, and it’s worth being honest about it: integrating a fleet with an existing warehouse management system, IT network, and power infrastructure takes real planning. Getting that integration right is essential if the system is to deliver the flexibility and scalability it was designed for.

Matching the AMR to the Material Handling Challenge

None of this is really about robots in the abstract – it’s about matching the right unit to the actual problem on your floor. That’s why our AMR range isn’t a single product: a latent mobile robot built for compact, under-rack transport solves a different problem than a forklift-style unit built for heavy stacking, and a conveyor-equipped robot that docks straight into a production line solves a different one again. Facilities in food and beverage, petrochemical, paper and wood, and similar sectors rarely have one material flow problem – they usually have two or three running at once, in different corners of the same building.

If any of the three challenges above sound like a normal Tuesday at your facility, the starting point isn’t picking a robot. It’s mapping where transport time, floor risk, and layout constraints are actually costing you, and sizing a fleet against that – not against a spec sheet. That’s the conversation we’d rather have first.

AGV vs. AMR: Understanding the differences

1. Structure and load capacity

2. Path planning and navigation

3. Programmability and adaptability

4. Implementation and Setup

5. Navigation technologies

6. Flexibility and obstacle avoidance

7. Scalability and system expansion

Where mobile robots are used

• Manufacturing plants for moving raw materials, semi-finished goods, and finished products.
• Warehouses for automated picking and replenishment.
• Distribution centers for order fulfillment and inventory movement.
• Hospitals and laboratories for safe, contact-free delivery of supplies and samples.

The benefits of implementing AGV and AMR systems

• Reduced labor costs through automation of repetitive transport tasks.
• Improved safety, minimizing human exposure to heavy loads or hazardous zones.
• Greater process efficiency and shorter delivery times between workstations.
• Scalability and flexibility to adapt to evolving production needs.
• Enhanced traceability of materials and workflow data.

What do AGV and AMR stand for?

AGV – Automated Guided Vehicle: A guided vehicle designed to transport materials along a set path via tracks, wired connection, or magnetic tape.

AMR – Autonomous Mobile Robot: An independent robot that navigates its environment using advanced sensors and mapping technology (no set paths required).

The main difference

The primary difference is that AGVs operate via guided pathways and set navigation, while AMRs offer a more agile solution that can navigate dynamic environments with minimal to no modification to your building.

AGV vs. AMR: Which one is best for you?

AGVs: They’ve existed for decades when it comes to automated material handling. They’re best used in a large material handling world with a consistent and unchanging production setup. Companies can invest in infrastructure development for AGVs, but it typically incurs an expensive upfront cost when they must lay physical groundwork for tracking systems. They don’t always pivot well when production needs change.

AMRs: They’re new and evolving! With LiDAR, cameras, and AI-empowered navigation, they can create maps and determine paths on the go. AMRs navigate their real-time environments to find the fastest path without human intervention, making them incredibly efficient in rapidly changing production environments.

Set path vs. smart movement

• AGVs: Operate on set paths with predetermined tracks and movement inputs. They utilize magnetic strips or QR codes to direct them. If you need them to take a different route, you will have to spend extensive time and money on reinstallation. They stop if they hit obstacles and cannot find alternative routes.
• AMRs: Operate via sensors, cameras, and mapping abilities. They acknowledge obstacles in their path and adjust their course on the fly.

Flexibility versus function

• AGVs: Best for repetitive tasks that don’t change. Once established, they’re hardwired for life with a consistent purpose unless grossly changed (and that’s expensive).
• AMRs: Flexible! They can perform similar transport tasks across multiple areas, which are effectively managed via software or fleet management. This benefits companies whose layouts change regularly.

Business model: established vs. changeable

• AGVs: Fit businesses operating under traditional models where things don’t change, and layouts remain the same. They rely on stability and infrastructure developments.
• AMRs: Created for agile business scenarios. If your production line moves or expands, an AMR can be reprogrammed or given a new map with established points to follow so your production remains stable.

Safety protocol

• AGVs: Operate with basic obstacle awareness. When they hit something, they usually stop until the object is removed.
• AMRs: Use LiDAR, 3D cameras, and effective ISO navigation standards to detect potential obstacles in real-time. They slow down or reroute depending on what’s in their way.

Cost and ROI

• AGVs: Require a hefty initial investment due to the necessary infrastructure. Even when established, additional costs may arise if routes or functions need to be realigned.
• AMRs: Deploy quickly with a relatively low investment cost due to the absence of fixed infrastructure requirements. They provide efficiency almost immediately, within weeks of deployment, providing ROI in a few short months.