Warehouse automation has long been a story of trade-offs. For years, operators had to choose between fixed automation that delivers high throughput but lacks flexibility, or autonomous mobile robots (AMRs) that offer flexibility but often only handle transport, not the actual picking of items. The source material points to a significant shift in this landscape: the emergence of mobile manipulation as a new system architecture. This is not a single robot design but a category of systems where robots can both move through a facility and manipulate individual items. When evaluating automation for your warehouse, this architectural change is the first thing to understand.
The key capability to look for is whether a robot can pick individual items directly inside the storage area. Traditional systems often require robots to travel back and forth between storage racks and a separate picking station. The source material describes a different approach: robots that can pick items fully autonomously right where they are stored. This eliminates the constant travel between storage and picking, which in turn leads to shorter travel distances, less congestion in the aisles, fewer handoffs of goods between different machines or workers, and lower labor costs. The source also notes that this approach can potentially deliver much higher throughput, even exceeding that of shuttle-based systems.
Another critical factor is the scope of automation. The source material emphasizes that the solution is not just about picking. It covers the full order fulfillment cycle: order picking, buffering, consolidation, dispatch, and stock replenishment. When you look at a robotic system, check whether it can handle these multiple stages or whether it only addresses one piece of the puzzle. A system that can manage the entire flow from storage to dispatch reduces the need for manual intervention at multiple points, which is where labor costs and errors typically accumulate.
Deployment speed is another practical consideration. The source material states that the solution takes just weeks to deploy. This is a significant advantage compared to traditional automation projects that can take months or even years to design, install, and commission. For a warehouse operator, this means less disruption to ongoing operations and a faster return on investment. However, the source does not specify the exact number of weeks, so you should ask vendors for a concrete timeline based on your facility's size and complexity.
Scalability is also worth examining. The source material mentions that the robots are suitable for warehouses of any size. This suggests a modular approach where you can start with a small number of units and expand as your order volumes grow. Look for systems that allow you to add robots incrementally without having to redesign the entire layout or software architecture.
The source material also highlights the distinction between two types of mobile manipulators. One type, exemplified by the Autopicker, is an AMR-style system where robots move freely through the warehouse. The other, like the Gridpicker, is a high-density grid-based system optimized for maximum performance and throughput. When evaluating options, consider which architecture fits your warehouse layout and order profile. A free-moving system may be better for irregular layouts or facilities with narrow aisles, while a grid-based system might be superior for high-density storage where space is at a premium.
Finally, consider the vendor's track record. The source material states that the company has more than 250 employees and hundreds of AI robots deployed with customers. It also notes that the Autopicker robot was unveiled in 2023 and that more than 500 units are now deployed on multi-year contracts. This scale of deployment suggests that the technology has moved beyond pilot projects and is operating in production environments. When talking to vendors, ask for references from customers with similar order profiles and throughput requirements. The source does not disclose specific customer names or performance metrics, so you will need to request those directly.
Practical steps
If you are considering mobile manipulation for your warehouse, the first step is to conduct a thorough analysis of your item profile. The source material notes that mobile manipulation is only effective when a meaningful share of a warehouse's items can be picked robotically. This means you need to assess what percentage of your SKUs have the right characteristics for robotic picking—size, weight, shape, and packaging. The source does not define what constitutes a "meaningful share," so you will need to work with vendors to determine if your mix qualifies. Be prepared to provide data on your top-selling items and their physical attributes.
Next, map your current fulfillment process from receiving to dispatch. Identify every point where items are handled manually. The source material lists five key functions: order picking, buffering, consolidation, dispatch, and stock replenishment. For each of these, document the current labor hours, error rates, and travel distances. This baseline will help you quantify the potential savings from automation. The source material claims that the robots reduce the need for warehouse labor, but it does not provide specific percentages. You will need to calculate your own baseline and compare it to vendor projections.
Once you have your baseline, engage with vendors who offer mobile manipulation systems. The source material describes Brightpick as a leader in this space, with offices in the US and Europe. When you contact vendors, ask for a demonstration or a pilot deployment. The source states that deployment takes just weeks, which suggests that a pilot is feasible without a long commitment. During the pilot, measure the actual picking rates, error rates, and labor savings against your baseline. Also, observe how the robots handle your specific items, especially any that are fragile, oddly shaped, or have unusual packaging.
Consider the integration with your existing warehouse management system (WMS). The source material does not specify the software interfaces, so you will need to ask vendors about their API capabilities and whether they support standard integration protocols. The robots need to receive order data and report inventory status in real time. If your WMS is older or custom-built, factor in additional time and cost for integration. The source does not disclose any integration challenges, so treat this as an area to investigate thoroughly during the evaluation process.
Plan for a phased rollout. The source material emphasizes that the solution can be deployed in weeks, but that does not mean you should automate your entire warehouse at once. Start with a single zone or a specific product category. This allows you to train your staff, refine the robot's picking parameters, and measure performance in a controlled setting. Once the pilot zone is operating smoothly, expand to other areas. The modular nature of the robots, as described in the source, should support this incremental approach.
Staff training is another practical step. Even though the robots reduce the need for labor, you will still need workers to oversee the system, handle exceptions, and perform maintenance. The source material does not specify the required skill level, but you should plan for training programs that cover basic troubleshooting and system monitoring. Also, consider how the robots will interact with your existing workforce. The source mentions fewer handoffs and less congestion, which should reduce the physical strain on workers, but you will need to communicate these benefits to your team to gain their buy-in.
Finally, establish key performance indicators (KPIs) before you deploy. The source material highlights shorter travel distances, less congestion, fewer handoffs, and lower labor costs as benefits. Quantify each of these for your facility. For example, measure the average travel distance per order before and after deployment. Track the number of handoffs per order. Monitor labor hours per order. The source also mentions cost per pick as a metric that should decrease. Set targets for each KPI and review them monthly. The source does not provide benchmark numbers, so your targets should be based on your own baseline and the vendor's projections.
Common mistakes to avoid
One of the most common mistakes is assuming that all robotic picking systems are the same. The source material makes it clear that mobile manipulation is a new system architecture, not a single robot design. There are AMR-style systems where robots move freely, and there are grid-based systems optimized for high-density storage. Choosing the wrong architecture for your warehouse layout can lead to poor performance and wasted investment. For example, a grid-based system may not be suitable for a facility with irregular column spacing or low ceiling heights, while a free-moving system might struggle in very narrow aisles. Evaluate both options against your physical constraints before making a decision.
Another mistake is underestimating the importance of the item mix. The source material explicitly states that mobile manipulation is only effective when a meaningful share of a warehouse's items can be picked robotically. If you have a high proportion of items that are too large, too heavy, or too irregular for robotic picking, the system will not deliver the expected labor savings. Do not rely on the vendor's claims alone. Conduct your own analysis of your SKU profile and test the robot with your actual items during a pilot. The source does not define the threshold for a "meaningful share," so you need to establish this for your own operation.
A third mistake is focusing only on the picking function and ignoring the other stages of fulfillment. The source material lists order picking, buffering, consolidation, dispatch, and stock replenishment as functions that can be automated. If you only automate picking and leave the other stages manual, you will still have labor costs and potential errors at those points. The full benefit comes from automating the entire flow. When evaluating a system, ask how it handles each of these functions. If the vendor's solution only covers picking, you may need to integrate it with other automation or accept that you will not achieve the full labor reduction described in the source.
Many operators also make the mistake of neglecting the software integration. The source material does not disclose the specifics of the software stack, but it is clear that the robots are AI-powered and rely on computer vision. These systems generate large amounts of data about item locations, picking success rates, and inventory levels. If your WMS cannot handle this data or if the integration is poorly executed, you will not get the real-time visibility needed to optimize the system. Before signing a contract, ask for a detailed integration plan and references from customers who have integrated the system with a WMS similar to yours.
Another common error is underestimating the change management required. The source material states that the robots reduce the need for warehouse labor, which can be a sensitive issue for your workforce. If you do not communicate clearly about how the robots will change job roles, you may face resistance and low morale. The source mentions fewer handoffs and less congestion, which should make the work easier, but you need to articulate these benefits. Also, plan for new roles such as system monitors and exception handlers. The source does not specify the number of staff required to oversee the robots, so you will need to plan for this based on your own observations during the pilot.
A fifth mistake is ignoring the total cost of ownership. The source material mentions lower labor costs and lower cost per pick, but it does not disclose the capital cost of the robots or the maintenance costs. Multi-year contracts are mentioned, which suggests that the robots are typically leased or purchased with a service agreement. Make sure you understand the full cost structure, including any per-pick fees, software licensing, and maintenance. The source does not provide any pricing information, so you must obtain detailed quotes from the vendor and compare them against your labor savings projections. Also, consider the residual value of the robots at the end of the contract term.
Finally, do not assume that deployment in weeks means zero disruption. The source material states that deployment takes just weeks, but that does not mean the system is plug-and-play. You will need to reconfigure your storage layout, install any necessary infrastructure such as charging stations or grid structures, and train your staff. During the deployment period, your normal operations may be disrupted. Plan for this by scheduling the deployment during a slower period or by running the robots in a separate zone initially. The source does not provide details on the deployment process, so ask the vendor for a step-by-step plan and a timeline that accounts for your specific facility.
Another mistake to avoid is selecting a system based solely on throughput claims. The source material states that mobile manipulation can potentially achieve much higher throughput that exceeds even shuttle systems. However, this potential depends on your specific order profile and warehouse layout. A system that achieves high throughput in a vendor's demonstration may not perform the same way with your items. Insist on a pilot with your own orders and measure the throughput under realistic conditions. The source does not provide specific throughput numbers, so you cannot rely on published figures. Your pilot data will be the most reliable basis for your decision.
Lastly, do not overlook the importance of vendor stability and support. The source material notes that Brightpick has more than 250 employees and hundreds of robots deployed, which suggests a stable company. However, the source does not disclose the financial health of the company or its long-term support commitments. When you sign a multi-year contract, you are relying on the vendor to maintain the robots, provide software updates, and supply spare parts. The source does not specify service-level agreements, response times, or spare-part lead times, so you must negotiate these terms explicitly in your contract. Ask for guarantees on uptime and penalties for non-performance.
In summary, mobile manipulation represents a genuine shift in warehouse automation, but it is not a one-size-fits-all solution. The source material highlights the benefits of shorter travel distances, less congestion, fewer handoffs, and lower labor costs, but these benefits are only realized when the system is matched to your specific operation. Take the time to analyze your item mix, map your processes, pilot the system, and negotiate a contract that protects your interests. The technology is proven at scale, with more than 500 robots deployed, but your success depends on how well you plan and execute the implementation.
Sources
Reaching new heights: How Brightpick’s Giraffe can lift warehouse efficiency
Published by Vigla Media OÜ (Estonia).