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'Rudimentary' flapping robots move together for the greater good

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Close-up of a 'smarticle' showing two 3D-printed arms, a light sensor and motor (Credit: Rob Felt, Georgia Tech)
Close-up of a 'smarticle' showing two 3D-printed arms, a light sensor and motor (Credit: Rob Felt, Georgia Tech)

Small, immobile robots only capable of flapping their arms might not sound very useful – but when combined, they form something greater than the sum of their parts.

Known as smarticles – smart active particles – the “very rudimentary” robots are capable of moving through mazes, and could eventually lead to robotic ‘swarms’ for military or disaster-response applications.

The devices were created by researchers at the Georgia Institute of Technology and Northwestern University in the US. The 3D-printed machines just have motors, simple sensors and limited computing power.

Although the smarticles can only flap their two arms, when five are confined in a circle they begin to nudge one another and move together in a ‘supersmarticle’.

The researchers realised that the group moves in a definite direction if one smarticle stops working, with the other devices moving in the direction of the stalled unit. To exploit this, they added light sensors that stopped the flapping, letting them control the direction of the group.

“These are very rudimentary robots whose behaviour is dominated by mechanics and the laws of physics,” said principal investigator Dan Goldman. “We are not looking to put sophisticated control, sensing and computation on them all. As robots become smaller and smaller, we'll have to use mechanics and physics principles to control them because they won't have the level of computation and sensing we would need for conventional control.”

The research could lead to robotic systems capable of changing their shapes, modalities and functions, the team said. Potential applications could include robotic swarms that move to rivers and autonomously form structures to span the gap. Small robotic swarms could also enhance military situational awareness in difficult-to-manoeuvre environments such as cities, forests, caves and other rugged terrains.

The work was published in Science Robotics.

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