Researchers led by the University of Cambridge have built a mother robot that can independently design and test its own ‘children.’ By analyzing the data it collects from observing the child, the mother robot ensures that preferential traits are passed down to the next iteration, while letting weaknesses fall by the wayside, without depending on computer simulation or human intervention. “We developed a robot that creates robots. And basically we have a mother robot that combines active and passive modules using glue to make other children robots. And these robots, as the mother creates them and puts them to work, she evaluates how they’re behaving and she uses the data from this behavior to create the next generation of robots,” explained Andre Rosendo, who worked on the project at the University’s Department of Engineering. Without any human intervention or computer simulation beyond the initial command to build a robot capable of movement, the mother created children between one and 5 plastic cubes that are stuck together using glue. Each cube has a small motor inside, so when they are attached to each other in slightly varying formations it produces a different rate of locomotion when the motors are activated. Each robot child is tested on how far it moves from a starting position in a given amount of time, with the best individuals’ traits carried over into the next generation. In each of 5 separate experiments, the mother robot designed, built and tested generations of 10 children, using the information gathered from one generation to inform the design of the next. “The mother robot can actually build hundreds of child robots and see the performance of these child robots and, if their performance is good, keep their design for the next generation. And if bad, just let it go. And just repeating this iterative design improvement processes, the mother robot can actually gradually improve the performance of the child robot,” said lead researcher Dr Fumiya Iida. “Natural selection is basically reproduction, assessment, reproduction, assessment and so on. That’s essentially what this robot is doing — we can actually watch the improvement and diversification of the species.” This does not apply to robots. In fact, researchers hope that insights garnered from these experiments may further inform how humans themselves have evolved and how natural selection takes place. “One of the big questions in biology is how intelligence came about – we’re using robotics to explore this mystery,” Dr Iida added.
“We think of robots as performing repetitive tasks, and they’re typically designed for mass production instead of mass customization, but we want to see robots that are capable of innovation and creativity.” This might also eventually help us create robots that can improve themselves without any input from humans at all. At the moment, robots require us to fix them, as they wouldn’t themselves begin to stand up on their hind legs, which may eventually change in the future. Iida’s research looks at how robotics can be improved by taking inspiration from nature, whether that’s learning about intelligence, or finding ways to improve robotic locomotion. “It’s still a long way to go before we’ll have robots that look, act and think like us,” said Iida. “But what we do have are a lot of enabling technologies that will help us import some aspects of biology to the engineering world.” While the naysayers will predict doomsday for humans if allow AI to evolve, there is not denying that a future where AI can do complex type of work is the need of the hour.
