Swarms of robots work better with fewer opinions

Swarms of robots could tackle forest fires and other hazards more efficiently if decision making in the group is undertaken by a smaller number of machines, a study has found.

Led by Dr Andreagiovanni Reina from Sheffield University’s Department of Computer Science, the study published in Science Robotics could improve how swarms of robots work together, adapt to changes in their environment and make sophisticated decisions more quickly.

The study is said to disprove the widely accepted theory that more connections between robots leads to more effective information exchange.

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The team, which included researchers from UCL and IRIDIA, Université Libre de Bruxelles, Belgium, discovered their findings by studying how a swarm of tiny robots moved around and reached a consensus on the best area they should gather in and explore.

According to the study, each robot assessed the environment individually, made its own decision on the best area and broadcast its opinion to the rest of the swarm. Every robot in the swarm then periodically selected a random assessment that had been broadcast by another robot in the swarm and used it to update its opinion on the best area – a protocol dubbed the voter model. Once every robot had gone through this process the swarm reached a consensus on the best area to gather and explore based on the opinion of each robot.

The team found that by using this protocol the robot swarm was slow to adapt to changes in the environment when a better site appeared.

Swarms of robots
More connections between robots doesn’t always lead to more effective information exchange (Image: Sheffield University)

The researchers then discovered that when robots communicated to other robots that were within a 10cm range – rather than broadcasting their message to the whole group – the swarm was able to adapt to changes in their environment much quicker and select the best available area.

In a statement, Dr Reina said: “Swarms of robots have huge potential to help us access places that are either too hazardous or simply inaccessible to humans. For example, they could fly over a forest fire that is too vast or dangerous for humans to tackle alone, monitor how the fire spreads and decide where help is needed the most.

“However, what happens if the fire suddenly changes direction and support is urgently needed elsewhere – the swarm of robots needs to be able to quickly adapt to this change and identify where the urgent support is needed. This is what our research is helping to do – our findings could be used to develop swarms of robots that are more responsive and able to make the right decisions much quicker than they currently can do.”