The team in the Sheffield Centre for Robotics, jointly established by Sheffield University and Sheffield Hallam University, have been working to program a group of 40 robots, and claim the ability to control robot swarms could prove hugely beneficial in a range of contexts, from military to medical.
The researchers have demonstrated that the swarm can carry out simple fetching and carrying tasks, by grouping around an object and working together to push it across a surface.
The robots can also group themselves together into a single cluster after being scattered across a room, and organize themselves by order of priority.
Dr Roderich Gross, head of the Natural Robotics Lab, in the Department of Automatic Control and Systems Engineering at Sheffield University said swarming robots could have important roles to play in the future of micromedicine, as ‘nanobots’ are developed for non-invasive treatment of humans.
On a larger scale, they could play a part in military, or search and rescue operations, acting together in areas where it would be too dangerous or impractical for humans to go. In industry too, robot swarms could be put to use, improving manufacturing processes and workplace safety.
The programming that the Sheffield University team has developed to control the robots is claimed to be simple. For example, if the robots are being asked to group together, each robot only needs to be able to work out if there is another robot in front of it. If there is, it turns on the spot; if there isn’t, it moves in a wider circle until it finds one.
‘We are developing Artificial Intelligence to control robots in a variety of ways,’ said Dr Gross in a statement. ‘The key is to work out what is the minimum amount of information needed by the robot to accomplish its task. That’s important because it means the robot may not need any memory, and possibly not even a processing unit, so this technology could work for nanoscale robots, for example in medical applications.’
This research is funded by a Marie Curie European Reintegration Grant within the 7th European Community Framework Programme. Additional support has been provided by the Engineering and Physical Sciences Research Council.
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