It wasn't so long ago that the idea of biped or quadruped robots delivering pizzas seemed like a real possibility. Such speculation was fuelled by Google's acquisition of Boston Dynamics—a company more associated with potential military applications, which earned notoriety for its scarily nimble Big Dog robots.

Google, and then its parent company Alphabet, had to work out how to bring this technology to civvy street—a problem that certainly gnawed at the development team. The vision was perhaps too grandiose even for Alphabet and, earlier this year, it was reported that Boston Dynamics had been off the leash so it could sniff around for potential buyers.

With that short-lived episode over, the roadmap for robotic deliveries is now back under debate, at least if you were expecting arms and legs. But how about an autonomous delivery box on wheels or an airborne drone instead? These are all at the prototype stage but they’re definitely coming; in fact, there's a wide range of innovative technology under investigation by retailers to achieve a competitive edge, from drones to chatbots to redesigned Mars rovers and slasher robots.

Exploring Amazon

When it comes to delivery, robotics are already in use but mostly out of sight, unless of course you’re working in a customer fulfilment centre—a distribution warehouse to you and me.

Amazon’s acquisition of Kiva Systems in 2012 was a rather less dramatic move than Alphabet buying Boston Dynamics. In 2015 it was rebranded as Amazon Robotics, and its operation has retreated in-house, much to the chagrin of those who had a business model built around its machines. As a consequence, Quiet Logistics, previously a poster child for Kiva robots, decided that the only way around the problem would be to design its own. It formed Locus Robotics in 2014 and has since developed its own LocusBot warehouse picking assistant. It’s work in progress and demonstrates yet another approach to warehouse automation.

Amazon paid an eye-watering $775 million (£630 million) for its warehouse robotics company and was last month awarded patents for its “system and method for coordinating movement of mobile drive units,” which describes the cleverness that enables multiple bots to identify and select stacks of goods, and then move them around a warehouse floor without collision. The floor has a grid embedded into it with specified rotation areas that ensure the bots don’t stray.

What they actually transport are described as "magic shelves"—tall storage units that contain a range of goods. Compact orange robots slide underneath these structures and lift them from below. Then, by motoring along at a sober pace, they transport them to individual packing stations where human operatives pick items from the magic shelves to prepare an order. As the video shows around the 1:13 mark, the bots line up for a picker who never moves from her station.

Old news perhaps, but at least this is a robotics technology that is actually being deployed to deliver increased efficiency. Admittedly, these bots aren’t covering the last mile to your doorstep, but they’re covering thousands of miles a year in warehouses, overseen by some tricky optimisation tasks to maximise route efficiency.

Indeed, it’s the work of analytics and machine-learning algorithms that are determining just how effective robotics and automation can be at accelerating delivery, whether within a warehouse or out on the road.

Ocado: From warehouse to table

For online grocery retailer Ocado, the use of big data analytics infiltrates just about every part of the business from customer profiling on the website, to analysing product demand, delivery routes and, of course, providing the customer with delivery slots to choose from. To the user, clicking on a delivery time won’t involve a great deal of thought but it’s actually a fantastically complex offering, as Ocado's CTO Paul Clarke explains.

“In that click, a lot happens in the background. Our systems are looking at your geography and all around your geography. They’re looking at existing orders that have been placed. They are working out—between 6am and 10.30pm, in half-hour increments—which slot we could serve you that day. This is based on existing orders and what we think you will have in your order, if you haven’t already filled your basket. It’s also based on the capacity of vans. And that has to happen in about 500ms.

“If you ask that same question five seconds later, the answer will be different. Other customers will have placed an order and some people will have added more to their order. That takes up capacity in the van. It’s a real-time optimisation where the problem spec is changing under our feet all the time.”

Fulfilling timed delivery slots certainly adds a layer of complexity that typical courier firms don’t experience. For them, the batch-optimisation problem is simply in working out a delivery order and choosing the vans. If a customer is out, just put a card through the door.

Moreover, the courier won’t be putting the items in the boxes for distribution either. Lest we forget the CFC warehouse that’s having to manage deliveries from suppliers and, of course, the pick-and-pack needed to satisfy individual orders before they even set off in a van with an assigned time slot.

To deal with these variables Ocado looks to the cloud, with AWS and Google providing the muscle for its Ocado Smart Platform (OSP) offering. Besides marketing a delivery solution that other retailers can buy into, Morrison’s being the latest example, the Ocado Smart Platform is being revamped with robots designed in-house. These are currently being tested at its Andover facility and have already processed full orders, although Clarke wants to do more larger-scale tests before “pushing the button.”

The new robots operate on a grid which Clarke confesses is not an exactly new concept, dating back to container ports, where cranes on a frame roam over boxes and move them around. Companies such as Swisslog utilise a similar approach with their grid bots and it has had success with Asda deploying its AutoStore Small Parts Storage System at its warehouses. Ocado’s technology is another variation on the space-efficient grid theme.

Still, there was a fleeting glimpse of these new bots in action on Twitter recently, and the technology behind them suggests that this really could be an interesting development in terms of robotic efficiencies. The autonomy bottleneck, as discussed in a recent Ars article, is that robots are merely shuffling bins around that humans have to pick from, as we’re just a bit too clever for the pick-and-pack side of things to be replaced by automation just yet.

Just like Amazon’s Kiva bots, the Ocado system is designed to improve access to the goods in the warehouse, but this is being refined at every level. In essence, it’s a four-dimensional optimisation problem. There’s the two-dimensional motion of the robots, the third-dimensional optimisation of the grid that has the storage bins underneath, and the fourth dimension—achieving that process efficiently by shifting these bins of goods over time.

As orders continuously arrive from customers, the system not only has to consider the best place to store a bin back on the grid after picking but also has to look ahead to future orders that will be processed, which may have a bearing on that location. At the same time, the best route-optimisation at a 2D level needs to be calculated as the robots whizz around, which adds to the complexity.

“There are a load of algorithms and machine-learning from doing route optimisation,” says Clarke “but that’s slightly different from the analytics that sits on top, which is almost independent. Its aim is to detect things, like a modification to a piece of firmware that has changed the physics model of a bot, or if an individual bot has an issue that’s going out of spec. You’re trying to pick that up. Like everything else, our first port of call is to put everything into a data lake in the cloud, and then perform smart analytics on top of it.”

A further aspect to route optimisation is the underlying system that monitors more routine conditions, like when a particular isn't accelerating as fast as expected or if its battery doesn't last as long. Such symptoms can impact the effectiveness of the whole grid, and so poorly performing bots need to be identified and called in for a service or battery replacement. Indeed, any robot can take over tasks from another and, as they’re battery powered, the setup as a whole is designed to be more tolerant to power loss or brownouts.

While customer orders influence the storage locations of the bins of goods zooming around in the grid, there are other factors that have a significant bearing on their “velocity.” In short: the speed that goods move out of the warehouse. Milk and bread shift quickly, but an exotic scented candle will be a slow burn. Demand alters with the weather, time of year, or a festive period—just watch the candles and pumpkins fly during Halloween. Even a TV chef can make a difference.

“We saw the speed of a vanilla pod—which typically has a spike only at Christmas time—as a result of some celebrity chef recipe,” says Clarke.

Yet rather be taken by surprise, analytics and predictive algorithms for customer buying patterns are routinely performed. The ideal is no empty shelves and no overstock either, as Clarke explains.

“We run multiple forecasting models that compete with each other for accuracy. Based on which one wins, a particular forecasting model is chosen for each product and if that changes over time, then we will pick a different forecasting model. That’s an important of part of us predicting how we get goods into our warehouse just in time; minimise stock cover and maximise freshness, while at the same time, giving uniquely high availability to our customers.”