Wireless Noodle Episode 5: Machines of Loving Grace

The idea of the autonomous robot has captured the imagination of writers, movie-makers and intellectuals for decades. In Episode 5 of the Wireless Noodle we examine the reality of deployments of autonomous robotic systems in factories, hospitals, on the streets, and in the air. We look at the roll outs today and likely evolution over the next ten years, with particular interest in the degree to which we will see true autonomy.  

You can access it here, or via Google or Apple.

The full transcript of the podcast is available below.   

From the utopian view of Richard Brautigan’s poem All Watched Over by Machines of Loving Grace, to the dystopian perspectives of Martin Ford’s Rise of the Robots or the Terminator, the concept of the autonomous robot has captured the imagination like few other technology concepts. What’s the reality today?

A week or two ago I saw a news item that caught my eye. It was about a tie-up between IT Service vendor and systems integrator T-Systems and KUKA, the robot manufacturer. They make the general purpose robot arms that are the quintessential poster child for automated processes in factories. On the face of it this item seems fairly innocuous, but I think it’s interesting for two reasons. Firstly because robotics is one of those sectors that’s on the cusp of realising some of the innovation benefits from separating software from hardware, as I was discussing back in episode 3. Secondly because it’s squarely focused on the manufacturing requirements of small and medium-sized businesses. This isn’t just about the gigantic Industry 4.0 initiatives of Airbus, BMW or ThyssenKrupp, exciting though those are. This is democratisation of the use of autonomous systems in factory production. That, for me, is very exciting. It’s also illustrative, perhaps, of the impact of COVID-19. In Episode 2 I was talking about how lock down had created greater demand for a lot of Internet of Things use cases, albeit with challenges for supply. T-Systems and KUKA are clearly gearing up to ride that wave of demand when it’s unleashed.

The news also reminded me of a session I ran at the Automation & Robotics Online Conference back in June where I delved into some interesting trends in the market. I want to share some of those with you in this week’s episode to give my perspective on where we are today and where we are headed in the near future.

At Transforma Insights as a category we talk about ‘Autonomous Robotic Systems’, which perhaps needs a little definition. In this category we consider any distributed physical machines (like industrial robots, drones and autonomous vehicles) that are able to operate autonomously and potentially collectively. They can be defined, more or less, on two axes. One is the extent to which they move (with surgical robots being virtually static and military drones having range of hundreds of km). The other is their deployment environment: ranging from consumer-grade such as domestic robots and consumer drones through commercial grade like delivery robots and autonomous vehicles, through to industrial grade such as autonomous mining equipment, surgical equipment and factory robots.

Today the market for autonomous systems tends to focus on machines that are largely static, and that are industrial grade. According to the International Federation of Robotics, in 2018 about half of the USD33bn spent on robotics went on industrial robots, and a further 9% on medical. Autonomous vehicles was 12%, and another 12% went on the ‘entertainment’ category which today is mostly consumer drones, but in the future who knows! In fact, in terms of volumes of devices, consumer drones and personal/domestic devices massively dominate the numbers of units. But, with industrial and surgical robots costing in the region of $40k (and more) compared to around $200 for a Roomba, the reason for the dominance of industrial as a proportion of spend is obvious.

In our own investment forecasts published back at the start of the year, the lion’s share, over 90%, of investment in robotic systems will be from the manufacturing sector, specifically for manipulation robots. Transport, construction, health and agriculture/forestry all feature but at much lower levels, typically involving drones and personal assistance robots.

I haven’t mentioned warehousing yet, but that’s also a very interesting space. I don’t dwell on it much in this podcast, but the advent of COVID-19 has stimulated a lot of interest in automating elements of the supply chain, including warehousing. One really interesting example is Ocado Technology which has developed the Ocado Smart Platform warehouse automation solution in collaboration with Ocado Engineering. It picks and packs customer shopping using machine vision, natural language processing and warehouse optimisation. I thoroughly recommend you track down the video on YouTube.

Geographically, there are also some interesting things happening. According to our forecasts, despite China being the workshop of the world, it will be more or less matched for investment in this space by North America (which is in #1 spot) and Europe (which is just behind China). Robotic systems will be used as part of an on-shoring process, which is more relevant to Europe and North America than to China. Japan and S Korea also score high, for exactly the same reasons.

The benefits of on-shoring are obvious: reduced transport cost and improved responsiveness to market conditions. Intuitively it makes sense to put your manufacturing nearer to the customer, assuming that those benefits aren’t outweighed by those of scale and lower wage costs. The latest strides in additive manufacturing and autonomy mean that I expect lots more localised manufacturing. 

In the last episode I talked about the characteristics of various digital transformation projects in the real-world. It’s interesting to dig in to the characteristics of the use of autonomous robotic systems. 

Almost all of the projects that are worth considering fit into two categories: drones and factory robots. These have very different profiles. Drones are very quick to deploy and pay back, typically a matter of a few months for each. The use of manipulation robots in contrast typically take a year to deploy and multiple years to pay back. 

Considering the impact, we rated over 95% of applications across both categories as having a significant or transformational effect on process efficiency, and much lower impact on the company’s value propositions. These technologies are about efficiency savings. At least today they are. It’s perhaps not surprising that the earliest adoption of autonomous systems are where they can do the least harm. In drones for mapping tree growth, in medical for suturing and in manufacturing for packing and labelling. 

Unlike the adoption of most other techs, like AI or distributed ledger, they’re about de-risking. Most other techs are considered to have some inherent risk, but on balance autonomous robotic systems are considered to reduce risk for the implementing organisation. But that doesn’t mean they’re not important. Over a quarter are considered to be mission critical or highly mission critical, slightly above the average for other techs. 

Another interesting characteristic we found is that over 90% of implementations are based on fully productised solutions bought off the shelf. This is a good sign for scale benefits cascading through lots of smaller organisations. The democratisation idea I spoke about in relation to T-Systems and KUKA. 

Another characteristic that we dig into for robotic systems is degree of automation. There is a standard well established six-level hierarchy developed by SAE International which ranges from level 0, i.e. no automation up to level 5, full automation. In between there are diminishing requirements for operator assistance. Manipulation robots have over 75% in the top category and  over 95% in the top 2 categories. These are largely or completely automated systems. Mobile robotic systems, however, i.e. predominantly drones, have a much more mixed profile, with <10% in the top two categories and 40% in the bottom two. Partially this is due to regulation. You just can’t fully automate a lot of drones today, particularly Unmanned Aerial Vehicles. But, the direction of travel is towards that.

It is noticeable that the degree of autonomy is closely related to the extent to which the device might move into a public space. On private land, owners can more-or-less do as they please, for instance with enormous autonomous dump trucks in mines or combine harvesters in agriculture. But, once you stray into the public sphere, e.g. with delivery robots, either UAVs or pavement, or with autonomous passenger cars, it becomes quite a minefield. The conclusion I draw is that organisations will use and prefer autonomy to an extent only limited by the law. And the law is heading in only one direction: more roll outs. 

I mentioned in the intro about the separation of software and hardware layers in robotic systems. It feels like we are just on the cusp of something interesting. Take drones, for instance. The dominant world player is DJI, but increasingly there are intelligence providers such as DreamHammer, DroneDeploy and Picterra, providing an intelligence overlay on top of the hardware platform. There are also fully integrated providers such as Delair that, while they do make the hardware, are more focused on the drone intelligence space. There are also, of course, a whole load of application providers such as Aerodyne and Cyberhawk, supporting specific use cases. 

The same is also true for land vehicles. The old model of the hardware manufacturer dominating the whole of the technology landscape is giving way to something very different. With the advent of both electric vehicles and autonomous driving new disruptive players are spotting an opportunity to wrestle control from the old guard. We’ve seen this to an extent in electric vehicles, with Tesla gaining a strong foothold. With autonomous vehicles I expect it to be even more pronounced. Assuming, of course, that we can ever really get to proper autonomy. It’s likely that the makers of the cars will be the same companies. VW, Toyota etc. have the infrastructure. But an autonomous vehicle world is likely to be equally dominated by a new set of service providers managing the application and the intelligence of the system. Those might include Uber, the aforementioned Tesla, Google, Amazon, Zipcar and Enterprise, all of whom are making significant bets on autonomous vehicles.

Finally, with factory robots, we see a similar model. The old hardware players such as ABB, KUKA and Kawasaki Robotics will continue to dominate the hardware market but we also see a new generation of intelligence and application providers such as Altizon, Bright Machines and MTEK riding on top of the hardware. Interestingly, in part this is because the on-device processing is not up to snuff. These are often years-old machines, with underpowered processors on-board. If you want to run the latest automation software, by definition you need to go beyond the closed system of the robot itself, using edge gateways. This creates an opportunity for someone else to create the software. Some of the robotics manufacturers, most notably ABB, KUKA and Yaskawa have been working on beefing up their full service offering including intelligence and applications. 

This brings me on to a particularly interesting area of development for manipulation robots: programming by demonstration. In the world of Robotic Process Automation, bots which sit on PCs are shown a repetitive IT-based task that is fulfilled by an person. Examples might be copying information out of an email and putting it into a spreadsheet. Or it might be logging invoices on an accounts system. The RPA bot is shown how the task is performed and then set to imitate the human activity. It can be spectacularly more efficient, although never quite the plug-and-play miracle that the vendors might have you believe. It’s also quite primitive, if you think about it. Literally getting a bot to do what a human would do. Better, surely, to find a more native way of automating the system. Nevertheless, very effective. 

Programming by Demonstration uses machine vision and machine learning to analyse a human’s physical actions and replicate them using a manipulation robot. I would expect this to be equally more efficient to the RPA methods, but also, somehow primitive. Surely there are more efficient ways to achieve the goals rather than just using robotic arms to imitate a human. It’s not hard to see that there is a mental hurdle that needs to be overcome somewhere.  

There are obvious benefits to companies in using robotics, particularly in performing tasks more cheaply. For instance a drone is much cheaper than hiring a helicopter. And it’s also a great way to knock out the impact of wage differentials and allow for on-shoring of more manufacturing. But there are risks. Most importantly two things: Firstly the cost. Fitting out a factory can cost millions. Secondly flexibility. Elon Musk rolled back on some of Tesla’s automation, saying “Humans are underrated” because of the flexibility they give you. There’s hope for people still. 

Ultimately, for the utopian and dystopian views of the rise of the machines to be realised we need a radical shift in artificial intelligence. Almost by definition Artificial General Intelligence is needed for us to have truly autonomous systems. But it is almost impossible to tell whether we are on the cusp of unleashing artificial general intelligence, or it will remain forever out of our grasp. That’s a topic for a future podcast if ever I heard one. 

Next week’s podcast is a special one, focused on the results of our Communications Service Provider IoT Peer Benchmarking report. As I’ve shared before, I’m ostensibly a telecoms guy for all my professional (and a big chunk of my academic) life, and I combine that with being an IoT guy for the last decade. So the point at which they overlap is tremendous for me. In the report we dig into the strategies of the likes of AT&T, Telefonica and Vodafone as they pertain to IoT, to provide enterprises with recommendations on who they should be working with and CSPs with the opportunity to see how they compare with the competition. 

Links to some of the research that I’ve refered to in this week’s show, as well as a transcript of the recording, will be available on the podcast website at WirelessNoodle.com

Thank you for listening to The Wireless Noodle. If you would like to learn more about the research that I do on IoT, AI and more, you can follow me on Twitter at MattyHatton and you can check out TransformaInsights.com

Thanks for joining me. I’ve been Matt Hatton and you’ve been listening to the Wireless Noodle.