The tiny robots are a breakthrough development in the field of biotechnology and robotics that is promising for regenerative medicine
It is well known that all organisms on Earth – be it plants, animals, humans and even microorganisms such as bacteria and viruses reproduce for survival and carry forward their genes to the next generation.
This is impossible for robotic machines as they are developed, controlled and operated by humans.
Now scientists at the University of Vermont (UVM) in collaboration with Tufts University and Harvard University have identified an exceptional technique for biological reproduction that can be applied to tiny robots, allowing them to replicate themselves.
Enhancing the past discovery
Building upon their research from last year on developing living robots called Xenobots, the research team at UVM has discovered that these computer-designed and hand-assembled organisms can swim out into their tiny dish, find single cells, gather hundreds of them together and create miniature Xenobots inside their Pac-Man-shaped “mouth” — that, a few days later, become new Xenobots that look and move just like themselves.
“With the right design — they will spontaneously self-replicate,” says Joshua Bongard, a computer scientist and robotics expert, and professor in the College of Engineering and Mathematical Sciences, University of Vermont.
The reproduction technique used is based on the numerous embryonic cells of the Xenopus laevis frog that over time evolve into skin.
“These cells have the genome of a frog, but, freed from becoming tadpoles, they use their collective intelligence, a plasticity, to do something astounding,” said Michael Levin, a professor of biology and director of the Allen Discovery Center at Tufts University.
“These are frog cells replicating in a way that is very different from how frogs do it. No animal or plant known to science replicates in this way,” said Sam Kriegman, a post-doctoral researcher at Tuft’s Allen Center and Harvard University’s Wyss Institute for Biologically Inspired Engineering, who did his PhD at the Morphology, Evolution & Cognition Laboratory at the University of Vermont.
He further adds, “These (Xenobots) can make children but then the system normally dies out after that. It’s very hard to get the system to keep reproducing.”
A little AI help
The above challenge was overcome with the help of an artificial intelligence (AI) program by the Deep Green supercomputer at UVM’s Vermont Advanced Computing Core.
The evolutionary AI algorithm tested and simulated billions of body shapes including triangles, squares, pyramids and starfish to come up with the ones that allowed the cells to be more dynamic in motion known as kinematic replication.
Kinematic replication is a familiar occurrence at a molecular level for living organisms. But this was the first time that this phenomenon materialised at a whole cell or organism scale.
“We asked the supercomputer at UVM to figure out how to adjust the shape of the initial parents, and the AI came up with some strange designs after months of chugging away, including one that resembled Pac-Man,” said Sam Kriegman.
“It looks very simple, but it’s not something a human engineer would come up with.”
In other words, the right design greatly extended the number of generations.
Deeper goal
While the above development for proponents of robotics will come across as highly appealing, for some it will be a cause of concern, mainly arising due to fear of humans manipulating biotechnology for their use.
But for the team of scientists, the goal is to expand their understanding.
“The world and technologies are rapidly changing. It’s important, for society as a whole, that we study and understand how this works,” says Joshua Bongard.
“This is an ideal system in which to study self-replicating systems. We have a moral imperative to understand the conditions under which we can control it, direct it, douse it, exaggerate it.”
To combat the rising concerns over climate change and the future possibility of a new pandemic, developing technologies on the lines of Xenobots may provide viable solutions to these problems.
“The speed at which we can produce solutions matters deeply. If we can develop technologies, learning from Xenobots, where we can quickly tell the AI,: ‘We need a biological tool that does X and Y and suppresses Z,’ —that could be very beneficial. Today, that takes an exceedingly long time,” said Joshua Bongard.
“We need to create technological solutions that grow at the same rate as the challenges we face.”
With respect to regenerative medicine, the advancement is a great promise.
“If we knew how to tell collections of cells to do what we wanted them to do, ultimately, that’s regenerative medicine—that’s the solution to traumatic injury, birth defects, cancer and ageing,” said Michael Levin.
“All of these different problems are here because we don’t know how to predict and control what groups of cells are going to build. Xenobots are a new platform for teaching us.”
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