In a chemistry lab at the University of Liverpool, five mobile robots known as KUKA Mobile Robots carry out and support a range of laboratory experiments.

Each unit is built on a wheeled base with an articulated robotic arm.

This design means it can navigate between benches, approach workstations, pick up materials such as vials or cases of samples, and place them with millimetre precision into different pieces of equipment.

The robots are part of a connected automation system.

Other machines in the lab are responsible for preparing chemical reactions, running them under controlled conditions, and analysing the results using techniques such as liquid chromatography, mass spectrometry, and Nuclear Magnetic Resonance (NMR) spectroscopy.

The mobile robots link these separate stages, transporting samples between instruments and ensuring experiments can run without constant human presence.

They are programmed and given specific instructions by researchers.

Once a task list is set, the robots can carry it out without supervision, moving autonomously along pre-mapped routes and communicating with other equipment to complete each stage.

This allows scientists to run complex workflows that would be too time consuming to manage manually.

Ram Vijayakrishnan, postdoctoral researcher at the University of Liverpool, says: “So the robot behind me over here is called the KUKA Mobile Robot. It’s primarily used to transport samples around. Inside this workshop, we also have different robots that are there to synthesise, to perform reactions, to synthesise them. And we also analysis robots, such as liquid chromatography, mass spectrometry, and NMR spectroscopy as well.”

The lab is arranged so that the robots can operate in the same space as human researchers, avoiding obstacles and navigating safely between benches.

The aim is not to replace scientists but to integrate the machines into everyday laboratory work.

Vijayakrishnan continues: “These robots are really designed to be modular automation. They’re designed to work alongside human chemists in a standard organic laboratory. And they’re designed to conduct experiments that we wouldn’t normally do ourselves, for example.”

As part of a workflow, the robots can collect data from analytical machines, pass it to processing software, and use the results to decide which samples to run next from a pre-defined set. This enables faster decision making during experiments.

Vijayakrishnan adds: “Here in our lab, they transport samples back and forth, they analyse the data, and they decide what to do next based on the results that they’ve been given, similar to how a human chemist would work.”

The mobile bases are equipped with sensors for navigation and positioning, while the robotic arms can grip, lift, and place items accurately.

They are also capable of interacting directly with workstations by pressing buttons, moving valves, or loading containers into reaction chambers.

Yeow Qi Jie, PhD student at the University of Liverpool, says: “So effectively, it’s a mobile base, which I’m sure you’ve seen somewhere in the Amazon warehouses, with a mobile robotic arm. So effectively the mobile arm is able to pick up and then place items that’s on the base itself. And the base is able drive around and then able to load chemicals into various stations. And it’s also able to even partake in parts of the stations to help move valves within the station.”

Because they can operate continuously, the robots make it possible to run sequences of experiments without interruptions, even overnight or over weekends, freeing researchers from having to return to the lab at regular intervals.

Yeow continues: “It’s great, it’s a really huge time saver. So my reactions can take up to three and a half hours, two and a half hours. But if I’m doing it from back to back with the amount of reactions I need to do, every two and half hours I need to come back and then I need to do more reactions, whereas in this case I can set up multiple reactions to run and then, I can do other stuff. I’m free up, the time is freed up. But it’s also… When I’m at home at night, I don’t need to be back every two and a half hours to make sure that it continues running because it’s able to run throughout the night.”

To decide the order of experiments, the system uses artificial intelligence.

This allows it to select the most promising tests from a large set of possibilities, based on the data it receives from earlier runs.

Abdoulatif Cisse, PhD student at the University of Liverpool, says: “These robots are used to try to optimise some type of chemistry experiment. So that could be a chemistry experiment with a bunch of different inputs and we’re trying to maximise one output that we would measure. So the possible combinations of that is just a lot, sometimes millions and millions of different combinations, reactions that we could try. But since we don’t have time to try all of them, we need some type intelligent way to decide which experiments we will try next. So that’s where the AI part comes into play.”

Experts say this approach is part of a wider shift in research, where robotic platforms and AI are combined to work through chemical possibilities far more quickly than manual methods allow.

Lauren Ye Seol Lee, lecturer in chemical engineering at UCL, says: “When COVID happened, everyone realised that accelerating discovery of a new drug is actually really important. And since then, and the development of AI and maturity in the robotics area, putting it all together, it becomes possible to explore large chemical space using integrated AI and robotics platforms.”

Lee adds: “Robots excel every bit at repeating well defined tasks, but real experiments often surprise you because a protocol might run perfectly well with common conditions, but even when you need to deal with multi different chemicals, actually it can behave very differently. So at that point, human need to make decisions. Human need to design experiments, human need to interpret unexpected or even expected results and making creative leaps.”

Researchers here say the aim is to make laboratory work more efficient, handling repetitive processes so scientists can focus on analysis and design.

They hope that in the future, this combination of AI and automation will lead to faster breakthroughs, not only in academic research but in industrial laboratories around the world.

AP video by Mustakim Hasnath.