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There is no universally best warehouse-picking technology. Manual picking is the quickest, least expensive way to start and remains highly adaptable. Autonomous mobile robots (AMRs) reduce walking while people continue selecting items. Goods-to-person (GTP) systems bring inventory to stationary operators and can deliver high, repeatable throughput, but usually require more capital, engineering and operational change. Choose only after measuring your order profile, SKU mix, labor constraints, building and storage conditions, integration readiness and peak demand.
What the three alternatives actually do
Manual picking
A worker travels to storage locations, selects products and places them in an order tote, cart or container. Ordinary shelving or racking is sufficient, and supervisors can change slotting or processes without redesigning an automation system. The trade-off is travel time and dependence on available, trained labor. Actel Robotics describes manual operations as flexible and inexpensive to start, while stating that pickers can spend well over half their time walking. That is a vendor comparison, not an independent universal benchmark.
A warehouse picking cart can carry totes and goods and improve organization, but it does not retrieve inventory or replace the picker. It is a low-cost process aid rather than an automation system.
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Autonomous mobile robots move inventory, totes, shelves or work to people. In a person-to-goods workflow, a robot can guide or accompany a picker, reducing walking between locations. In a goods-to-person configuration, robots retrieve bins or shelves and deliver them to a station where an employee selects the required items. Fleet software assigns missions and manages traffic, charging and exceptions.
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AMRs can preserve more layout flexibility than conveyors or fixed storage machinery in some deployments, and fleets can be expanded in stages. Results depend on aisle geometry, fleet size, congestion, SKU profile, station design, network coverage and the work rules used by the site.
Goods-to-person automation
GTP keeps the operator at a pick station while storage equipment brings bins, shelves or trays to that person. The term covers several materially different designs: bin-to-picker AMRs, shelf-to-person robots, cube-storage systems and shuttle-based systems. They differ in density, achievable rate, product compatibility, implementation effort, maintenance and how easily capacity can be changed.
Side-by-side comparison
| Decision axis | Manual picking | AMR-assisted picking | Fixed or GTP automation |
|---|---|---|---|
| Demand profile | Often practical at low or steady volume when labor is available | Useful for growing or variable demand; capacity can follow fleet and workflow changes | Most compelling when sustained throughput is high and predictable enough to justify a designed system |
| How work moves | Picker travels to storage | Robots reduce transport or walking while people select items | Inventory travels to stationary pick stations |
| Layout impact | Works with ordinary shelving and changing layouts | May retain existing racks, subject to robot aisles, floor and safety requirements | May require new storage, conveyors, stations, structural work or building changes |
| Throughput | Bound by staffing, travel and replenishment | Depends on fleet, congestion, station balance and labor | Can be high and predictable when engineered for the required rate |
| Scaling | Hire, train and schedule more people | Add, reassign or sometimes lease robots, subject to system design and contract | Expansion may require additional equipment and engineering |
| Initial investment | Low automation investment | Capital purchase or subscription/robot-as-a-service; site-specific pricing | Usually high capital, integration and commissioning cost |
| Density and ergonomics | Depends on rack layout and walking or reaching | Varies by robot and storage method | Cube and shuttle designs can increase density and present goods ergonomically |
| Systems and support | Existing WMS processes and normal equipment support | WMS/WES integration, fleet management, network, safety and robot service | Controls, storage, conveyors, WMS/WES, commissioning and specialist maintenance |
When manual picking is the right choice
Manual work is a rational baseline when order volume is modest, the catalog changes often, products are irregular, or the facility cannot yet support automation. It avoids long integration projects and lets you alter slotting, packaging and order waves quickly. It can also be the best approach for seasonal or highly customized work where a permanent machine would be underused.
Its capacity is constrained by the number of available workers, walking distance, replenishment delays and the time needed to train replacements. Measure lines per labor hour rather than assuming that adding headcount will solve a peak: labor may be unavailable precisely when demand is highest. Use slotting, batch or zone picking, clear location labels and carts to reduce avoidable travel before buying robots.
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Where AMRs fit best
Good task candidates
- Transporting totes from storage or replenishment to a pick or pack station.
- Following a picker through a person-to-goods route so the worker does not push a cart or return to a staging point.
- Retrieving shelves or bins in a goods-to-person cell.
- Moving completed orders, returns or replenishment loads between defined work areas.
- Handling variable demand where a fleet can be reallocated between zones or shifts.
AMRs are less suitable when floors are uneven, aisles cannot provide safe clearance, Wi-Fi coverage is unreliable, loads exceed the robot’s rated capacity, or the process has no stable handoff points. They also do not remove every human task: employees still pick, replenish, resolve exceptions and maintain inventory accuracy.
What performance claims mean
Actel Robotics says its Locus-based fulfillment AMRs can raise picking productivity by 2–3 times versus manual cart picking and deploy in weeks. The company describes those figures as dependent on facility, SKU profile and configuration. Treat them as directional vendor claims, not a guaranteed result or an independent benchmark. Require a site-specific model that states fleet size, travel assumptions, labor content, congestion limits and peak conditions.
Understanding GTP architectures
Dematic’s comparison of GTP designs identifies four distinct approaches. Its figures are supplier-published and should be validated against a common workload definition before they are used in a business case.
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| Architecture | How it works | Published characteristics and trade-offs |
|---|---|---|
| AMR bin-to-picker | Robots retrieve totes or bins and deliver them to a station | Dematic reports up to 400 order lines per hour per picker. Storage height and density, fleet travel and station balancing affect the actual rate. |
| AMR shelf-to-person | A robot brings an entire shelf to the operator | Dematic describes potentially quick implementation and lower cost for smaller systems, with lower typical pick rates than the other GTP types in its comparison. |
| Cube storage | Bins are stored in a cubic grid; robots access bins from above and deliver them to stations | Dematic claims space requirements can fall to as little as 25% of conventional shelf storage. The percentage is a vendor comparison; the baseline, bin fill and building constraints determine real savings. |
| Shuttle GTP | Multiple shuttles retrieve inventory in storage aisles and supply pick stations | Dematic reports rates exceeding 600 order lines per hour per station and storage heights up to 20 metres. Both figures depend on system configuration and rate definition. |
GTP is not automatically better than AMR-assisted person-to-goods picking. A dense cube can save floor space but may constrain product dimensions and replenishment patterns. A shuttle can deliver high rates but needs engineered aisles, controls and maintenance access. Shelf-to-person robots may simplify a smaller retrofit while offering less peak throughput. Select the architecture that matches your SKU dimensions, velocity, replenishment frequency, fire and building rules, and expansion plan.
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What a retrofit can look like
NEO Intralogistics describes a deployment 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. AMRs retrieved bins from the shelving and delivered them to a station without moving the racks; an employee still performed the item pick.
In the vendor’s case study, one station handled about 4.5 million picks across roughly 180 working days between January and August 2026. NEO also reports that the project released 25–30% of shelf-warehouse floor for other projects, reached production six to eight weeks after project start, and led to an order for a second station after performance testing. These are results from one German customer deployment, not a forecast for another building. Conrad CEO Ralf Bühler is quoted in the 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 independent market finding.
Costs, labor and return on investment
Public sources reviewed for these alternatives do not provide directly comparable current prices or an independently validated payback period. Do not insert an unsourced “months to pay back” number into a capital request. Compare proposals using the same scope and geography.
For manual picking, count recruiting, wages, overtime, turnover, training, carts, scanners and the cost of missed service windows. For AMRs, include robots or subscription fees, fleet software, stations, charging, network upgrades, safety work, integration, training, support, spare parts and downtime during deployment. For fixed or GTP systems, add storage machinery, conveyors or shuttles, controls, structural and fire changes, commissioning, maintenance contracts, software licenses, building works and contingency for outages.
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Model at least three demand cases: normal, sustained peak and a lower-volume scenario. A system that meets an annual average may fail during the service window that determines customer satisfaction. Include replenishment labor and exception handling; quoted pick rates generally describe the pick face, not every activity in the order lifecycle.
A practical decision process
- Establish the workload. Record order lines, units, lines per order and service windows by hour, shift, day and peak season. Separate normal demand from promotions and special events.
- Characterize the inventory. List SKU count, dimensions, weight, velocity, lot or expiry rules, security constraints, packaging, replenishment frequency and the proportion of slow movers.
- Measure the current process. Time walking, searching, picking, scanning, replenishment and exception work. Record accuracy, touches, congestion, ergonomic incidents, overtime, turnover and unfilled shifts.
- Survey the building. Document rack type, aisle width, floor condition, clear height, usable floor area, fire and building requirements, pedestrian routes, charging locations and planned expansion.
- Check digital readiness. Map WMS, WES or WCS interfaces, item and location data quality, wireless coverage, device standards, fleet orchestration and exception workflows.
- Shortlist the operating pattern. Keep manual picking as the baseline. Test an AMR-assisted design if walking is the dominant waste and existing racks are valuable. Evaluate GTP when stationary-pick ergonomics, density or sustained peak rate justify larger change.
- Request comparable designs. Give every supplier the same order history, SKU file, peak definition, labor assumptions and building drawings. Ask each to state assumptions behind every throughput or savings figure.
- Pilot or visit a reference site. Use a workload with similar SKU dimensions, order profiles and service promises. Measure the complete process, not a demonstration cycle.
- Write acceptance criteria before signing. Define sustained peak lines per hour, accuracy, uptime, labor per line, replenishment performance, recovery time after faults and the method for adding capacity.
Integration and operating requirements
Automation is only as reliable as the data and handoffs around it. Confirm that the WMS can send unambiguous mission and inventory data, that the WES or fleet manager can prioritize work, and that scanners or put-to-light systems capture every pick. Design for replenishment, short picks, damaged goods, cycle counts, returns, blocked aisles, robot faults and network outages.
- Safety: define pedestrian segregation, speed limits, emergency stops, fire egress, training and inspection responsibilities.
- Availability: specify charging or battery-swap capacity, preventive maintenance, spare parts and a manual fallback for critical orders.
- Change management: train supervisors and associates on exception handling, not just normal picks.
- Cybersecurity and connectivity: document network segmentation, access controls, software-update procedures and what happens when connectivity is lost.
- Replenishment: size reserve storage and labor so the pick face does not starve during the same peak that stresses picking.
Common mistakes and how to avoid them
Choosing from a headline rate
“400 lines per hour” or “more than 600” may describe a particular station, product mix and definition of a line. Ask for sustained rates with your order profile, including replenishment, replenishment travel, exceptions and breaks.
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Racks may remain in place, but robots still need clear aisles, safe interfaces, suitable floors, reliable wireless coverage and stations with enough buffer. Survey the physical site before accepting a short deployment timeline.
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Ignoring variability
Cube and shuttle systems can be excellent for stable, repeatable profiles yet harder to adapt when product dimensions or order patterns change. Compare the cost and lead time of re-slotting, adding capacity and handling nonconforming items.
Counting only pick labor
A successful design may shift work to replenishment, exception resolution, maintenance, software support or quality control. Include those roles in the future-state labor model.
Treating a vendor case study as a forecast
The Conrad figures reported by NEO and the productivity claims from Actel and Dematic are useful examples of what suppliers say is possible. They do not establish a universal result. Validate with a pilot, a comparable reference and contractual acceptance tests.
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Bottom-line selection guide
- Choose manual picking when volume is modest or highly changeable, capital is constrained, and labor can meet service requirements after basic slotting and process improvements.
- Add AMRs when walking and transport consume capacity, existing racks are worth retaining, demand is growing or variable, and you want a staged path with human selection still in the workflow.
- Invest in GTP when order volume and peaks are sufficiently stable to support engineered stations, inventory density or ergonomic gains justify the investment, and your building, data and integration teams can support the system.
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