While it's a common fear that robots will one day rise up and turn against us, there's currently a major obstacle standing in the way - they're too fragile.
New research is hoping to make robots more resilient by equipping them with special software that can help them learn how to bounce back from an injury in two minutes or less.
The hope is that these learning algorithms will help produce more effective autonomous robots that require less human intervention and can last longer in critical situations like the workplace or search and rescue scenarios.
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A team of scientists equipped robots with special software that can help them learn how to bounce back from injuries in two minutes or less, by taking a page from real animals
For the study, scientists from the Pierre and Marie Curie Universit and the University of Wyoming, took a page from real animals.
When an animal is injured, they're able to compensate by limping, shifting their weight or some other strategy.
Many three-legged dogs can catch frisbees, for example, or if someone sprains their ankle, they can still figure out how to walk even with an injury.
'When injured, animals do not start learning from scratch,' Jean-Baptiste Mouret, a co-author of the study, said in a statement.
'Instead, they have intuitions about different ways to behave.
'These intuitions allow them to intelligently select a few, different behaviors to try out, and after these tests, they choose one that works in spite of the injury.
'We made robots that can do the same,' he explained.
Before the robot is deployed, it uses a novel algorithm to create a detailed map of the space. This allows it to develop certain intuitions about what behaviors it can perform and their value
Before the robot is deployed, it uses a novel algorithm to create a detailed map of the space.
According to the researchers, this map represents the robot's 'intuitions' about what behaviors it can perform and their corresponding value.
Essentially, the robot can build a library of different motions and establish which body parts it can rely on if it becomes injured, even if it has a broken or missing leg.
Requiring a robot to map all these scenarios would take too long and could potentially damage the device, so the scientists mapped them out in a computer simulation.
In doing so, they were able to test and map over 13,000 different ways of walking, including with 'damaged, broken and missing legs, and for a