Mobile picking robots are increasingly marketed as a flexible and scalable automation solution for warehouses. However, a closer analysis reveals that they often fail to address the core inefficiencies of manual picking processes. Instead of eliminating the non-value-adding task of walking, as in goods-to-person (GtP) systems, mobile robots automate that very task\u2014at lower speed and higher cost.<\/p>\n\n\n\n
The key problem: mobile picking robots replace expensive human labor with expensive, limited-capability machines, without improving the ratio of productive to unproductive movements. They add complexity, require ongoing maintenance and fleet orchestration, and still depend on human intervention for error handling and replenishment. While their visual appeal and modularity make them attractive for pilots or innovation showcases, they rarely deliver significant gains in throughput or ROI in full-scale operations.<\/p>\n\n\n\n
There are niche applications where mobile picking robots can add value\u2014particularly in brownfield warehouses, labor-constrained environments, or temporary setups. But for most operations, especially those seeking long-term efficiency, they represent a technological detour rather than a strategic solution.<\/p>\n\n\n\n
Decision-makers should scrutinize automation proposals not based on novelty, but based on structural process improvement.<\/p>\n\n\n\n
During some team management meeting back in 2016, our VP said that we were given the task of evaluating the addition of mobile picking robots to our corporate product portfolio. Most of my peers were quick to conclude that mobile picking robots would be \u201cnice\u201d or \u201cgood to have\u201d. In my mind, however, I felt significant resistance against the idea. Initially, I could not quite articulate why I felt mobile picking robots are not something we should have. This bothered me, so I sat down in an effort to hyper-caffeinate myself and put my thoughts on paper. This worked.<\/p>\n\n\n\n
Next day, in the continuation of the meeting, I ask my peers and my boss: \u201cWhy do we automate?\u201d The replies revolved around cost savings and productivity and were generally sensible, though a little vague. I wanted to express the reasoning differently: \u201cWe automate because in warehouse operations, there are very costly assets \u2013 humans \u2013 spending much of their time performing non-value adding tasks \u2013 walking around. We want to improve the ratio of productive to unproductive movements of this expensive asset.\u201d This, in a nutshell, is why there are goods-to-person picking systems: we eliminate the most time-consuming non-value adding task (walking around) and instead have storage totes do the travel task for us.<\/p>\n\n\n\n
So far, so good.<\/p>\n\n\n\n
Let\u2019s take that very explanation and build on it to explain why mobile picking robots do not make an awful lot of economic sense: \u201cWe automate because we want to improve the ratio of productive to non-productive movements of our most expensive assets. With mobile picking robots, however, we merely replace one expensive asset with another expensive (and far less capable) asset performing the same poor ratio of productive to unproductive movements.\u201d Accordingly, we won\u2019t win anything. And because the new asset is so much less capable \u2013 much slower and much less versatile \u2013 we probably end up spending more AND we will still need humans to complement the robots.<\/p>\n\n\n\n
A mobile picking robot, in its most common form, navigates somewhat autonomously through warehouse aisles and stops at pick locations. The fundamental task of moving between picks is still performed \u2013 only now by a machine that moves slowly, is limited in its perception, and is prone to interruptions. Safety regulations cap the maximum speed of mobile robots to a level far slower than a trained picker walking with purpose. They wait at intersections, recalculate routes, stop for obstacles, and get bogged down in aisle congestion. While impressive from an engineering perspective, they are operationally underwhelming.<\/p>\n\n\n\n
We are not reducing the number of travel movements \u2013 we are just automating them inefficiently.<\/p>\n\n\n\n
Cost is another major concern. A single mobile picking robot costs between \u20ac30,000 and \u20ac80,000 depending on vendor and capabilities. This does not include:<\/p>\n\n\n\n
In total cost of ownership (TCO) terms, a fleet of mobile robots can quickly become a sizeable investment with significant running cost. And still: your warehouse throughput will likely not exceed that of a lean, manual pick team operating in a warehouse with optimized SKU slotting under an wave-picking strategy.<\/p>\n\n\n\n
Worse still, these robots cannot handle exceptions, errors, or ambiguous product situations. Their sensors are not perfect, and their ability to work with irregular goods, barcodes, or visual identification is limited. As a result, humans remain in the loop \u2013 to troubleshoot, assist, restock, or correct.<\/p>\n\n\n\n
You also inherit a subtle shift in process responsibility: Instead of giving a task to a human who solves it end-to-end, you split the task across robot and human, creating more interfaces and handoffs. As always, every interface adds potential failure points and operational fragility.<\/p>\n\n\n\n
If the above is true, why is there so much interest? I believe the reason is not operational \u2013 it’s psychological and political.<\/p>\n\n\n\n
In my view, it is because mobile picking robots provide a lower-barrier narrative <\/em>to automation. Mobile robots are tangible. They are \u201cvisible innovation.\u201d They give the impression of progress without requiring the same fundamental process changes as a full GtP setup. They are easy to explain to management. A VP can walk into a warehouse with robots moving around and say: \u201cWe are automating.\u201d It\u2019s a convenient narrative.<\/p>\n\n\n\n From a CAPEX standpoint, mobile robots also present a more digestible investment: you can start with 5 or 10 units. You don\u2019t need to redesign your warehouse entirely. You don\u2019t need a mezzanine or structural modifications or a radically different fire safety concept. This makes them attractive in brownfield environments and for pilot projects. They feel like a \u201cbridge\u201d between manual operations and automation \u2013 and that\u2019s an attractive pitch.<\/p>\n\n\n\n But this is a dangerous illusion. We risk falling into a technological dead-end where we incur the cost and complexity<\/em> of automation without the performance benefits<\/em>. And this, frankly, is worse than staying manual, because we lose both flexibility and efficiency. Moreover, the logic in favor of mobile picking robots only holds if the deployment is viewed in isolation \u2013 not in comparison to better alternatives.<\/p>\n\n\n\n I must admit this isn\u2019t going to be simple.<\/p>\n\n\n\n Before I try to steelman the case for mobile picking robots, I\u2019d like to point out that there is a natural way out of the economic problem I outlined: if these things were really, really low-cost, I wouldn\u2019t have a problem with the fact that they automate inefficient processes. If a resource is truly cheap and abundant, there\u2019s little need to worry about process design and efficiency. That\u2019s precisely why companies relocate production to low-cost countries where worker productivity may be lower, but wages are so low that it doesn\u2019t matter. We\u2019ll eventually get to that point with mobile picking robots as well, but we\u2019re not quite there yet.<\/p>\n\n\n\n Okay, now back to my attempt at steelmanning.<\/p>\n\n\n\n If you normally operate only one shift but run mobile picking robots 24\/7 to pick orders that are already in the system, the continuity can compensate for their lack of efficiency. This requires a significant time offset between when orders are received and when they need to be picked, which is a situation that is quite common for online retailers operating a single shift and relatively low customer expectations in terms of delivery time. Furthermore, it requires that a sufficient number of orders can be fully completed by the robots. An order structure with very few orderlines per order greatly facilitates this.<\/p>\n\n\n\n Another viable scenario might<\/em> be one in which the alternative automated solution is excessively expensive. Enter automated case picking system. Automated case picking systems, as engineered and built by Witron (most of the time), SSI Sch\u00e4fer (sometimes), and some others (almost never) <\/a>are very expensive, require tons of space, and a total makeover of just about everything. These systems start at \u20ac50M (just logistics hardware and software, excluding building and everything else) and can reach \u20ac250M or more. At the same time, manual case picking is no walk in the park: it is dull, physically demanding, often even highly unergonomic, and companies frequently face labor shortages.<\/p>\n\n\n\n This is where the Linde MH\u2019s RoCaP[1]<\/a> and Solwr\u2019s Grab[2]<\/a> come in. These are AGVs equipped with robotic arms for fully automated case picking in brownfield environments. Linde\u2019s RoCap has been under development for many years, the last four of which have been part of a joint research and development project with THWS (which happens to be the university where I teach). Admittedly, I was very skeptical of RoCap when I first heard about it \u2013 for all the reasons outlined above, and a few more. But given the enormous cost of conventional fully automated case picking systems, it might have been worthwhile to explore the idea. Whether it actually is worthwhile, I don\u2019t know, as I\u2019m not familiar with the cost structure of that machine. I could ask, but it doesn\u2019t matter for the general point I\u2019m making here: the alternatives are a manual process that is known to be terrible, and an automated process that is known to be excessively costly.[3]<\/a><\/p>\n\n\n\n I should add that I\u2019m very familiar with case picking in food retail warehouses\u2014this was my daily business for several years. And that\u2019s precisely why I\u2019m skeptical that case picking can be a process reliably operated by a mobile robot at a useful pace. The process is messy, variable, and sensitive to disruptions. But fast-forward 15 years, factoring in the technological progress we\u2019re likely to see and some process adaptations that retailers would need to make to accommodate such systems, then perhaps it will work.<\/p>\n\n\n\n That\u2019s as much as I can do in terms of steelmanning.<\/p>\n\n\n\n For a client project, I was looking for an affordable solution for the replenishment of flow racks in a zone picking system. I also knew that several automotive companies were looking for a similar solution for the replenishment of flow racks at assembly lines, with some of them even building their own prototypes. The market was huge, and there wasn\u2019t a single viable solution on the market.<\/p>\n\n\n\n Sometime right before COVID, I had a Zoom call with the CTO of a mobile picking robot company that was well known in Germany (it was impossible to find a conference in Germany where their leadership team wouldn\u2019t be among the speakers), but mostly unknown elsewhere. I told him something along the lines of: \u201cYou\u2019ve got great technology, but you\u2019re wasting your time with the wrong application. Why don\u2019t you replenish flow racks with your system?\u201d He responded that this was precisely what they were piloting. This was great news. Checking their website today, five years later, line feeding is the first application presented to me.<\/p>\n\n\n\n If you are good with AGV technology, and you are good with vision and picking technology, pushing standardized plastic boxes into flow channels should be a much simpler task to accomplish. <\/em>And there is a real market for it. Basically, any company operating an assembly line and having their line supply in flow racks could benefit from such a system. And many have explicitly demanded such a solution for years.<\/p>\n\n\n\n Mobile picking robots are a great example of a solution in search of a problem, while a real market was left unattended for most of the time, and for most companies out there, still is.<\/p>\n\n\n\n Mobile picking robots are a fascinating and often well-engineered technology. But in many warehouses, they solve the wrong problem. Instead of eliminating non-productive movement, they automate it \u2013 slowly and at high cost. It is not a sign of engineering ingenuity to automate a process that shouldn\u2019t exist in the first place, or to replace one costly asset operating inefficiently with another costly asset that operates in the same manner but is far less capable.<\/p>\n\n\n\n As with all warehouse technologies, the key question is not can it be done, but should it be done, and in what context. Blind automation leads to fragile, expensive, and low-performance systems. Any attempt at automation should start with a clear diagnosis of the underlying process problem<\/a>.<\/p>\n\n\n\n [1]<\/a> https:\/\/www.kiongroup.com\/en\/News-Stories\/Stories\/Innovation\/Innovative-Robotic-Truck-Successfully-Tested-with-ROSSMANN.html?storyid=59328<\/a> (last access: 2025-09-30)<\/p>\n\n\n\n [2]<\/a> https:\/\/solwr.com\/products\/grab<\/a> (last access: 2025-09-30)<\/p>\n\n\n\nSteelmanning the Case for Mobile Picking Robots<\/h2>\n\n\n\n
Pivoting to New Applications<\/h2>\n\n\n\n
Concluding Thoughts<\/h2>\n\n\n\n
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