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There is no universally best warehouse-picking technology. Manual picking is the least expensive and easiest to change, AMR-assisted picking can remove walking without replacing every rack, and goods-to-person (GTP) systems can deliver high, consistent output when volume and density justify a larger project. Choose by measuring your order profile, SKU mix, labor position, building constraints, integration readiness and total cost—not by a headline robot pick rate.
The practical decision is usually a staged one: keep manual work where demand is variable or low, add AMRs where travel is the constraint, and reserve dense GTP or fixed automation for repeatable flows with enough throughput to pay for engineered infrastructure.
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What each warehouse-picking alternative actually does
Manual picking
In a manual process, a worker walks to storage locations, selects units and places them in an order tote, carton or cart. Shelving and pallet racks can remain largely unchanged, and supervisors can reassign people as products and priorities shift. A basic picking cart carries totes or goods between locations; it does not find inventory, retrieve it or remove the labor requirement.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesManual picking has little automation infrastructure to buy, so it is often the sensible starting point for a small operation, a new channel or a warehouse with highly irregular demand. Its capacity is bounded by available labor, walking distance, replenishment and congestion. Actel Robotics describes pickers spending well over half of their time walking in some manual environments; that is a vendor comparison, not a universal independent benchmark. Overtime, hiring difficulty and ergonomic strain can become more important than equipment cost as volume rises.
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AMR-assisted picking
Autonomous mobile robots (AMRs) navigate the warehouse to transport totes, shelves, inventory or completed work. In a person-to-goods workflow, an AMR guides or accompanies a picker, carries the order container and presents the next task, reducing walking while the employee still selects each item. In a goods-to-person configuration, an AMR retrieves a bin or shelf and brings it to a fixed station where a worker picks.
AMRs can preserve more layout flexibility than conveyors and permanently fixed storage machinery, although they still need suitable aisles, floor conditions, wireless coverage, charging and safety controls. Fleet size can be changed or redeployed as demand changes, subject to the system design and commercial agreement. Actel says its Locus-based fulfillment AMRs can produce two to three times the productivity of manual cart picking and can be deployed in weeks. Those are directional vendor claims that depend on facility layout, SKU profile, staffing and configuration; they are not a guaranteed result.
Goods-to-person systems
GTP keeps a picker at an ergonomic station while storage equipment or robots bring inventory to that person. The label covers several different architectures, not one machine. They differ in storage density, item suitability, throughput, implementation time, flexibility, security, scalability and maintenance. A design that is excellent for small, fast-moving cartons may be a poor fit for long products, irregular cases or a very wide SKU catalog.
AMR bin-to-picker
Mobile robots retrieve totes or bins from storage and deliver them to a station. Dematic reports up to 400 order lines per hour per picker for this architecture. The figure is a supplier claim, and the achievable rate depends on the number of robots, presentation sequence, replenishment, station design, SKU handling and order mix. Storage height and density trade-offs must be evaluated alongside the rate.
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AMR shelf-to-person
A robot carries an entire shelf or rack to the operator. This can be quick to implement and relatively economical for a smaller system because the storage modules are simple and the robot fleet supplies the movement. Dematic describes typical pick rates as lower than those of the other GTP types in its comparison. It can be attractive when rapid deployment and incremental capacity matter more than maximum lines per hour.
Cube-storage systems
A cube system stores bins in a three-dimensional grid. Robots operate on top of the grid and extract the required bin for presentation at a station. Dematic says such a design may use as little as 25% of the space required by conventional shelf storage. That is a vendor-published comparison whose baseline and actual footprint depend on bin utilization, service aisles, replenishment areas, fire protection and the building design; it should not be treated as a universal space factor.
Shuttle goods-to-person
Shuttle systems use multiple shuttles in storage aisles to retrieve cartons or totes and feed fixed pick stations. Dematic reports rates exceeding 600 order lines per hour per station and storage heights up to 20 metres. Both figures are supplier claims. Ask whether the quoted rate is a sustained rate at your order-line definition, whether replenishment and exceptions are included, and what station, aisle and buffer equipment are required to achieve it.
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How the options compare
| Decision axis | Manual picking | AMR-assisted picking | GTP or fixed automation |
|---|---|---|---|
| Best demand pattern | Low or steady volume with labor available; highly variable assortments | Growing or variable demand where travel is the main constraint | Stable, repeatable throughput that justifies engineered capacity |
| Where the work happens | Picker travels to each location | Robot reduces transport or walking while people pick | Inventory travels to a stationary pick station |
| Layout impact | Works with ordinary shelving and frequent changes | Often retains existing racks, subject to aisle, floor and workflow requirements | May require new storage, conveyors, stations, building work and controls |
| Capacity constraint | Staffing, walking distance, congestion and replenishment | Fleet size, congestion, charging, station capacity and pick labor | Designed equipment rate, buffers, replenishment and system availability |
| Scaling method | Recruit, train and schedule more people | Add or reassign robots and stations where the design allows | Add engineered modules, shuttles, storage or stations |
| Initial investment | Low automation investment | Subscription/robot-as-a-service or capital purchase; site-specific pricing | Usually high capital and integration cost |
| Density and ergonomics | Depends on rack layout and walking/reach | Varies by storage approach and robot workflow | Cube and shuttle designs can increase density and present goods ergonomically |
| Systems required | Existing WMS processes and basic scanning | WMS or WES interface, fleet manager, network, safety and service | Controls, storage, conveyors or shuttles, WMS/WES, commissioning and maintenance |
Dematic says as many as 65% of warehouse employees may be dedicated to picking tasks. Because that is a vendor-published figure with no year stated on the source page, use your own labor study to establish the share in your facility before sizing an automation project.
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Match the technology to your operating profile
Choose manual picking when flexibility is worth more than speed
Manual work is defensible when order volume is modest, the SKU range changes frequently, products are awkward or nonconveyable, and local labor is dependable. It also suits a pilot operation where future demand is unknown. Improve it with slotting, barcode validation, batch or zone picking, clear replenishment rules and carts that reduce carrying. Measure walking and touches before assuming equipment is the problem.
Add AMRs when travel consumes the shift
AMR assistance is most useful when pickers spend large portions of the shift walking, racks are serviceable, and demand is growing but not yet stable enough for a fully engineered storage system. It can let the warehouse retain shelf storage, introduce capacity in phases and shift robots between zones. Confirm that aisles, turning radii, floor joints, lifts, doors, fire egress and network coverage support safe movement. A robot that waits for replenishment or a congested intersection will not deliver its quoted peak rate.
Use GTP when repeatable volume supports a station-centric design
GTP becomes compelling when order lines are high and predictable, pickers can be concentrated at stations, and dense storage or labor reduction has measurable value. It is particularly suited to small and medium items that can be stored in standardized bins or cartons. Verify how the architecture handles slow movers, oversized products, returns, cycle counts, hazardous or controlled items, lot and expiry rules, and replenishment. Keep a separate process for products that do not fit the automated presentation envelope.
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Conveyors, high-density storage and shuttle machinery can provide consistent high throughput, but changing the layout or product profile later may require substantial engineering. A building lease, channel strategy or SKU strategy that may change soon is a warning sign. Design expansion points and manual bypasses before approving a system that depends on a single forecast.
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Can goods-to-person automation use existing racks?
Sometimes. The answer depends on rack dimensions, load ratings, tote compatibility, aisle geometry, floor flatness, fire and building rules, and whether robots can safely access every required location. Shelf-to-person systems may use purpose-built shelves, while bin-to-picker systems often require standardized containers and an inventory map. A retrofit can preserve valuable rack investment, but it may also reduce usable locations or require relocation of beams, guards, lighting and sprinklers.
NEO Intralogistics describes a retrofit at Conrad Electronic’s Wernberg, Germany, warehouse. The site held about 250,000 items in existing shelf storage plus a shuttle system for fast movers. NEO says AMRs retrieved bins from the shelving and delivered them to a station without moving the racks; an employee still performed the item pick. Its case study reports about 4.5 million picks at one station across roughly 180 working days between January and August 2026, 25% to 30% of shelf-warehouse floor released for other projects, and six to eight weeks from project start to production. These are results reported by the supplier for one customer deployment, not a forecast for another warehouse.
Conrad chief executive Ralf Bühler is quoted in that case study saying, “Currently, there is no other provider besides NEO that offers goods-to-person automation specifically for shelf-racking environments.” That is a customer statement presented by the vendor, not an independently verified market conclusion. The same case study quotes supply-chain expert Thomas Kellner: “Confidence in the system grows day by day.”
Measure the operation before selecting equipment
- Build a demand baseline. Record order lines, units, orders per hour, lines per order and service cutoffs by hour, shift, day and peak season. Separate average, 95th-percentile and promotional peaks.
- Profile the inventory. Count SKUs and classify dimensions, weight, packaging, velocity, lot or expiry requirements, security restrictions, replenishment frequency and whether each item fits a tote, shelf, carton or automated gripper.
- Map the current work. Measure picker travel, touches, search time, replenishment delays, congestion, mispicks, ergonomic incidents, overtime, turnover and available labor by shift. Video or scan data is more reliable than assumptions.
- Document the building. Capture rack type and height, aisle widths, floor condition, clear height, doors, lifts, fire systems, columns, usable floor area, charging locations and expansion plans. Have a qualified engineer check building and safety requirements.
- Define the target service. State required sustained peak lines per hour, order cutoffs, accuracy, uptime, labor per line, replenishment response, recovery time after a fault and acceptable manual fallback.
- Shortlist architectures, not brands. Compare manual, AMR person-to-goods, AMR bin-to-picker, shelf-to-person, cube and shuttle designs against the same workload and site assumptions.
- Model total cost. Include hardware or subscription, software, integration, rack and building changes, network, safety, commissioning, training, spares, maintenance, support, energy, licenses, financing and downtime during installation. No directly comparable public total-cost or ROI figure establishes a generic payback for these three alternatives.
- Run a representative validation. Request a pilot or reference site with similar SKU dimensions, order profile, peak behavior and labor model. Require suppliers to show the assumptions behind every rate and savings claim.
Integration, data and facility requirements
- WMS/WES/WCS interfaces: agree which system owns inventory, task release, reservations, replenishment, exception handling and confirmation. Test duplicate, cancelled, short and substituted lines.
- Data quality: dimensions, weights, barcodes, locations and stock status must be accurate enough for routing and presentation. Create a process for new-SKU induction and master-data correction.
- Network and fleet control: survey wireless coverage, latency, roaming and interference. Specify charging strategy, battery rotation, fleet orchestration and behavior during network loss.
- Safety: validate pedestrian segregation, speed zones, emergency stops, guarding, light curtains, audible warnings, fire egress and procedures for a disabled robot or blocked aisle.
- Human work: design station height, reach, lighting, scanning, replenishment and exception ergonomics. Automation can move walking out of the job while leaving repetitive lifts or awkward reaches at the station.
- Resilience: document manual pick paths, spare equipment, recovery priorities, backup power where needed and how orders are released when robots, conveyors or the host system are unavailable.
Performance claims: how to read the numbers
| Claim | Source context | How to use it |
|---|---|---|
| Up to 400 order lines per hour per picker for AMR bin-to-picker | Dematic comparison; year not stated on the page | Use as an architecture reference. Obtain a site-specific sustained rate with your line definition and mix. |
| More than 600 order lines per hour per station and storage heights up to 20 metres for shuttle GTP | Dematic supplier claims; year not stated | Check whether buffers, replenishment, station staffing and exceptions are included. |
| As little as 25% of conventional shelf-storage space for a cube system | Dematic vendor-published comparison | Recalculate against your actual utilization, fire aisles, replenishment and expansion space. |
| About 4.5 million picks in roughly 180 working days; 25%–30% floor released; six to eight weeks to production | NEO case study of Conrad Electronic, Germany, January–August 2026 | Treat as one deployment’s reported outcome, not a transferable forecast. |
| Two to three times manual-cart productivity and deployment in weeks | Actel Robotics page updated July 28, 2026 | Treat as a directional vendor claim dependent on facility, SKU profile and configuration. |
Do not compare a supplier’s maximum station rate with your current average picker rate. Request the same definitions for gross and net lines, replenishment, breaks, quality checks, downtime, SKU presentation and peak duration. A credible acceptance test should run your real order waves for long enough to expose congestion and recovery behavior.
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Which material-handling tasks are a good fit for AMRs?
| Task | AMR fit | Conditions to verify |
|---|---|---|
| Transporting totes between storage and a pick or pack station | Strong fit | Standard containers, clear routes, station buffers and reliable scans |
| Bringing shelves to a picker | Fit for suitable small-item assortments | Shelf weight, presentation ergonomics, replenishment and lower typical rates |
| Moving completed orders to sortation or packing | Often suitable | Container identity, route priority, fire egress and peak accumulation |
| Handling pallets, long loads or irregular cases | Case-specific | Robot payload, turning radius, floor quality and attachment design |
| Picking each item from a location | Usually collaborative rather than fully autonomous | Human selection, vision or gripper capability, SKU presentation and quality control |
| Hazardous, temperature-controlled or highly regulated goods | Possible only with specialized design | Certification, containment, environmental rating and emergency procedures |
Common failure modes and how to prevent them
Designing for average volume
A system sized to average orders can miss holiday, promotion or weather-driven peaks. Size labor, stations, buffers, charging and replenishment for a defined sustained peak, then state what happens above it.
Assuming every SKU belongs in one automation loop
Oversized, fragile, slow-moving, hazardous or exception-heavy products can lower utilization if forced into standardized storage. Keep a deliberate manual zone and a clear handoff between automated and manual inventory.
Ignoring replenishment
Pick performance is meaningless if workers spend the shift waiting for stock. Model replenishment travel, reserve locations, decanting, container induction and priority rules together with picking.
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Robots cannot correct bad dimensions, duplicate barcodes or inaccurate stock. Clean item and location data, define ownership between WMS and fleet software, and test exception transactions before commissioning.
Leaving no recovery path
Every design needs a procedure for a stopped robot, blocked aisle, empty battery, failed scanner, network outage and host-system downtime. A manual fallback is part of the operating design, not an admission that automation failed.
Accepting a headline ROI
Public sources reviewed for these alternatives do not provide directly comparable current prices or an independent payback period. Build your own model from installed cost, labor by shift, overtime, error cost, space value, service contract, financing and expected utilization. Ask what happens if volume is 20% below plan or the SKU mix changes.
Acceptance criteria to put in the contract
- Sustained peak order lines per hour, with the line and order definitions written down.
- Pick accuracy and inventory-confirmation accuracy, including short, damaged and substituted items.
- System availability, planned maintenance windows and maximum recovery time after a fault.
- Labor required per shift for picking, replenishment, induction, exception handling and supervision.
- Container, SKU and weight ranges covered by the guaranteed design.
- Measured congestion, queue time and station utilization at peak.
- Integration behavior for cancelled orders, duplicate scans, lost containers, partial picks and WMS outages.
- Expansion method, lead time and cost for additional robots, stations, storage or charging.
- Training, spare parts, software updates, cybersecurity responsibilities and local service response.
Bottom line
Keep manual picking when flexibility and low starting cost dominate. Add AMRs when walking and internal transport are the bottleneck but existing shelving and a changing demand profile still matter. Invest in bin-to-picker, shelf-to-person, cube or shuttle GTP when a stable, high-volume flow can support fixed stations, dense storage and the integration effort. The winning choice is the one that meets your measured peak service requirement with a resilient fallback and a total cost you can validate—not the architecture with the largest unqualified number.
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