Credit: Soft Robotic Matter Group, AMOLF
Researchers from AMOLF's Soft Robotic Matter group have shown that a group of small autonomous, self-learning robots can adapt easily to changing circumstances. They connected these simple robots in a line, after which each individual robot taught itself to move forward as quickly as possible. The results were published today in the scientific journal
PNAS.
Robots are ingenious devices that can do an awful lot. There are robots that can dance and walk up and down stairs, and swarms of drones that can independently fly in a formation, just to name a few. However, all of those robots are programmed to a considerable extent - different situations or patterns have been planted in their brain in advance, they are centrally controlled, or a complex computer network teaches them behavior through machine learning. Bas Overvelde, Principal Investigator of the Soft Robotic Matter group at AMOLF, wanted to go back to the basics: a self-learning robot that is as simple as possible. "Ultimately, we want to be able to use self-learning systems constructed from simple building blocks, which for example only consist of a material like a polymer. We would also refer to these as robotic materials."