Robots! (5/5): Self-assembling robots and the potential of artificial evolution | Emma Hart

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1:14This episode is brought to you by Planet Visionaries, a podcast in partnership with the Rolex Perpetual Planet Initiative. What connects a hidden laboratory in the Amazon, giant pandas in China's mountain forests, research relating to the ocean, and communities living alongside wildlife in India. That's what you'll hear on season six of Planet Visionaries, stories from the explorers, scientists, and conservation leaders whose work addresses research, biodiversity, and conservation issues in specific locations. Planet Visionaries, hosted by environmental advocate and professional climber Alex Honnold, brings you real stories of discovery, determination, and research and initiatives relating to environmental change.

1:54In partnership with the Rolex Perpetual Planet Initiative, this is Planet Visionaries. Listen or watch wherever you get your podcasts.

2:07From Roombas to surgical technology, robots are already solving some of our everyday problems. But it's one thing to design a robot for a task we know a lot about, like vacuuming, and quite another to design a robot for a place where humans have never been, like another planet or the bottom of an ocean trench. But if we've never been to such a place, how do we anticipate what kinds of situations might arise? And how do you build a robot to navigate problems that we can't plan for or imagine? Computer scientist Emma Hart says the answer is something called artificial evolution, and she explains how it works in her 2021 talk at TED Women.

2:59Emma Hart: Imagine a scientist who wants to send a robot to explore in a faraway place, a place whose geography might be completely unknown and perhaps inhospitable. Now imagine that instead of first designing that robot and sending it off in the hope that it might be suitable, instead she sends a robot-producing technology that figures out what kind of robot is needed once it arrives, builds it, and then enables it to continue to evolve to adapt to its new surroundings. It's exactly what my collaborators and I are working on. A radical new technology which enables robots to be created, reproduce, and evolve over long periods of time.

3:42Emma Hart: A technology where robot design and fabrication becomes a task for machines rather than humans. Robots are already all around us, in factories, in hospitals, in our home. But from an engineer's perspective, designing a shelf-stacking robot or a Roomba to clean our home is relatively straightforward. We know exactly what they need to do, and we can imagine the kind of situations they might find themselves in. So we design with this in mind. But what if we want to send that robot to operate in a place that we have little or even no knowledge about? For example, cleaning up legacy waste inside a nuclear reactor where it's unsafe to send humans, mining for minerals deep in a trench at the bottom of the ocean, or exploring a faraway asteroid.

4:32Emma Hart: How frustrating would it be if the human-designed robot that had taken years to get to the asteroid suddenly found it needed to drill a hole to collect a sample or clamber up a cliff, but it didn't have the right tools or the right means of locomotion to do so? If instead we had a technology that enabled the robots to be designed and optimized in situ in the environment in which they need to live and work, then we could potentially save years of wasted effort and produce robots that are uniquely adapted to the environments that they find themselves in. So to realize this technology, we've been turning to nature for help.

5:14Emma Hart: All around us, we see examples of biological species that have evolved smart adaptations that enable them to thrive in a given environment. For example, in the Cuban rainforest, we find vines that have evolved leaves that are shaped like human-designed satellite dishes. These leaves direct bats to their flowers by amplifying the signals that the bats send out, therefore improving pollination. What if we could create an artificial version of evolution that would enable robots to evolve in a similar manner as biological organisms? I'm not talking about biomimicry, a technology which simply copies what's observed in nature.

6:00Emma Hart: What we're hoping to harness is the creativity of evolution, to discover designs that are not observed here on Earth, that a human engineer might not have thought of, or even be capable of conceiving. In theory, this evolutionary design technology could operate completely autonomously in a faraway place. But equally, it could be guided by humans. Just as we breed plants for qualities such as drought resistance or taste, the human robot breeder could guide artificial evolution to producing robots with specific qualities. For example, the ability to squeeze through a narrow gap or perhaps operate at low energy.

6:45Emma Hart: This idea of artificial evolution, imitating biological evolution using a computer program to breed better and better solutions to problems over time, isn't actually new. In fact, artificial evolution, algorithms operating inside a computer, have been used to design everything from tables to turbine blades. Back in 2006, NASA even sent a satellite into space with a communication antenna that had been designed by artificial evolution. But evolving robots is actually much harder than evolving passive objects such as tables, because robots need brains as well as bodies in order to make sense of the information in the world around them and translate that into appropriate behaviors.

7:35Emma Hart: So how do we do it? Surprisingly, evolution only needs three ingredients. A population of individuals, which exhibits some physical variations. A method of reproduction, in which offspring inherit some traits from their parents and occasionally acquire new ones via mutation. And finally, a means of natural selection. So we can replicate these three ingredients to evolve robots using a mixture of hardware and software. The first task is to design a digital version of DNA. That is, a digital blueprint that describes the robot's brain, its body, its sensory mechanisms, and its means of locomotion.

8:23Emma Hart: Using a randomly generated set of these blueprints, we can create an initial population of 10 or more robots to kickstart this evolutionary process. We've designed a technology that can take the digital blueprint and turn it into a physical robot without any need for human assistance. For example, it uses a 3D printer to print the skeleton of the robot, and then an automated assembly arm, like you might find in a factory, to add any electronics and moving parts, including a small computer that acts as a brain. And to enable this brain to adapt to the new body of the robot, we send every robot produced to an equivalent of a kindergarten, a place where the newborn robot can refine its motor skills, almost like a small child would.

9:16Emma Hart: To mimic natural selection, we score these robots on the ability to conduct a task. And then we use these scores to selectively decide which robots get to reproduce. The reproduction mechanism mixes the digital DNA of the chosen parent robots to create a new blueprint for a child robot that inherits some of the characteristics from its parents, but occasionally also exhibits some new ones. And by repeating this cycle of selection and reproduction over and over again, we hope that we can breed successive generations of robots where, just like as often observed in biological evolution, each generation gets better than the last, with the robots gradually optimizing their form and the behavior to their task and the environment that they find themselves in.

10:09Emma Hart: Now, although this can all take place in a time frame that's much faster than biological evolution, which sometimes takes thousands of years, it's still relatively slow in terms of the time frames we might expect in our modern world to design and produce an artifact. It's mainly due to the 3D printing process, which can take more than four hours per robot, depending on the complexity and the shape of the robot. But we can give our artificial evolutionary process a helping hand to reduce the number of physical robots that we actually need to make. We create a digital copy of every robot produced inside a simulation in a computer.

10:49Emma Hart: And we allow this virtual population of robots to evolve. Now, it's quite likely that the simulation isn't a very accurate representation of the real world. But it has an advantage that it enables models of robots to be created and tested in seconds rather than hours. So using this simulated technology, we can quickly explore the potential of a wide range of robot types, of different shapes and sizes, of different sensory configurations, and quickly get a rough estimate of how useful each robot may be before we physically make it. And we predict that by allowing a novel form of breeding in which a physical robot can breed with one of its virtual cousins, then the useful traits that have been discovered in simulation will quickly spread into the physical robot population, where they can be further refined in situ.

11:46It might sound like science fiction, but actually there's a serious point.

11:54Emma Hart: While we expect the technology that I've just described to be useful in designing robots, for example, to work in situations where it's unsafe to send humans, or to help us pursue our scientific quest for exoplanetary exploration, there's some more pragmatic reasons why we should consider artificial evolution. As climate change gathers pace, it's clear that we need a radical rethink to our approach to robotic design here on Earth in order to reduce that ecological footprint. For example, creating new designs of robots built from sustainable materials that operate at low energy that are repairable and recyclable.

12:38Emma Hart: It's quite likely that this new generation of robots won't look anything like the robots that we see around us today. But that's exactly why artificial evolution might help. discovering novel designs by processes that are unfettered by the constraints that our own understanding of engineering science imposes on the design process. Thank you.

13:06This episode is brought to you by Capital One. Capital One's tech team isn't just talking about multi-agentic AI. They already deployed one. It's called Chat Concierge and it's simplifying car shopping. Using self-reflection and layered reasoning with live API checks, it doesn't just help buyers find a car they love. It helps schedule a test drive, get pre-approved for financing, and estimate trade-in value. Advanced, intuitive, and deployed. That's how they stack. That's technology at Capital One. Hey, we're Nick and Jack, hosts of The Best One Yet. Behind every episode, there's research, email, spreadsheets, and our shared Google Doc, the headline hammer.

13:43With Google Workspace with Gemini, Google's AI is built right into the premium versions of tools we already use, like Gmail, Docs, and Sheets. No new tools or extra logins, just personalized AI for the way we work. That means less time on the work around the work and more time finding the stories worth talking about. Get AI tools for work. Upgrade to Google Workspace with Gemini at goo.gle slash workspace with Gemini. That's goo.gle slash workspace with Gemini. Hi there, it's Adam Grant from Ted's Rethinking Podcast, and this episode is brought to you by ServiceNow. I get to spend my days studying how people think and what it actually takes to change our minds.

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