Where are we in the physical AI revolution?
28 November 2024 
Artificial intelligence has the potential to change the way that we automate our factories. Anders Billesø Beck, vice-president for strategy and innovation at Universal Robots, considers some of the far-reaching implications of AI and suggests how it might affect robotics in the future.
In 10, 20 or 50 years’ time, we might look back at November 30 2022, and remember it as a historic turning-point. The launch of ChatGPT on that day may come to be seen as having started an era of the widespread use of artificial intelligence. Since then, AI and ML (machine learning) have been hot topics of conversation.
AI and ML are not new technologies. We have known them for decades, but the recent revolution is basically down to advances in computing power that are allowing us finally to handle the enormous amounts of data needed to take on the complex tasks we’re starting to use AI for.
The companies behind all this, such as Nvidia, are enjoying extraordinary growth – and rightly so.
Before this year’s Computex technology conference, Nvidia founder and CEO Jensen Huang highlighted the transformative power of generative AI, predicting a major shift in computing. “The intersection of AI and accelerated computing is set to redefine the future,” he stated, setting the stage for discussions on cutting-edge innovations, including the emerging field of physical AI which is posed to revolutionise robotic automation.
But here, in late 2024, what progress have we made in the physical AI revolution – on a scale from 1 to 5, say?
To be honest, we haven’t really got that far. I like to compare robotics to the development of self-driving cars. The automotive industry has defined five stages for the transition from manual to fully autonomous driving. Currently, the industry is not yet on level 5, as recent experiments in the US have shown, but the upside is that there are already a lot of level 2, 3 or 4 technologies that can have a major impact – such as adaptive cruise control in cars, which has turned a manual activity into a semi-automated process, making driving smoother, easier and safer.
The same goes for robotics. One day, AI will certainly lead to humanoid robots that can think and figure out how to solve problems by themselves without prior programming – that would be level 5. But, as with self-driving cars, we will see, and are already seeing, plenty of breakthroughs on level 2, 3 and 4 that are providing true value to businesses.
One of these breakthroughs, for example, can be seen in the field of logistics. In partnership with Siemens and Zivid, Universal Robots has developed a cobot that can perform order-picking with total autonomy, based on Siemens’ Simatic Robot Pick AI software and Zivid’s vision technology. Compared to manual processes, this enhances the speed and accuracy of order fulfilment significantly in warehouses, and helps logistics centres to meet growing global demand, while also dealing with the increasing difficulty of attracting labour for this kind of manual work.
Getting to a level 5 humanoid robot will rely heavily, among many things, on having outstanding vision technology and software at a level we are yet to see. But intermediate-stage technological innovations are delivering a lot of value on the way.
Three impacts
Getting a group of robotics experts to agree on where we currently are on the above scale could start a lengthy discussion. But it’s obvious that, when looking at the disruptive potential of physical AI, we still have much ground to cover – despite the great advances that have been made in the past couple of years.
Looking forward, let me highlight three of the impacts that I believe physical AI will have on robotics:
- AI will largely eliminate the need for experts We will, of course, still need robotics engineers, integrators and other skilled experts in the future, and plenty of them. But the potential of robotic automation is so large that there cannot be an expert on every factory floor (cobots have only reached about 2% of the current potential market). Many tasks in robotics today still require an expert. With AI, we will soon be able to remove some of the current hurdles, and this will accelerate the introduction of robots in many areas.
- Generative AI can help us standardise solutions The challenges we face in the automation industry are very similar in many companies. With generative AI, we are increasingly able to standardise both problems and solutions and thus create more re-usable robot behaviours. There is no need to reinvent the wheel every time a new robot is installed, and AI can help with that, making integration as well as return-on-investment much faster.
- AI enhances robots’ abilities to navigate in unpredictable environments As with the logistics solution mentioned earlier, vision technology with real-time feedback from 3D cameras is a huge enabler, not just of autonomous navigation, but also of obstacle detection. This capability opens the potential to introduce robots outside of the structured environment of a factory floor – for example, in the construction industry, where robots must handle project variations while working side-by-side with workers.
At Universal Robots, we already have numerous partners in our ecosystem making great advances with AI-based applications, in construction and beyond. And like so many of the other automation trends we will experience in the coming years across applications and industries, AI will very much be at the centre of future progress.
