AI Designs Unique Walking Robot in Seconds

Summary: Pioneering artificial intelligence (AI) has astoundingly synthesized the design of a functional walking robot in a matter of seconds, illustrating a rapid-fire evolution in stark contrast to nature’s billion-year journey.

This AI, operational on a modest personal computer, crafts entirely innovative structures from scratch, distinguishing it from other AI models reliant on colossal data and high-power computing. The robot, emerging from a straightforward “design a walker” prompt, evolved from an immobile block to a bizarre, porously-holed, three-legged entity, capable of slow, steady locomotion.

Representing more than mere mechanical achievement, this AI-designed organism may mark a paradigm shift, offering a novel, unconstrained perspective on design, innovation, and potential applications in fields ranging from search-and-rescue to medical nanotechnology.

Key Facts:

  1. Speedy Design: The AI created a functional walking robot, evolving its design from a static block to a mobile entity in just 26 seconds on a basic laptop, showcasing an unprecedented speed in robotic design and evolution.
  2. Innovative Structures: Unlike conventional AI, which tends to mimic existing designs, this system crafted a wholly novel, oddly-shaped, and effective robot with three legs and a porous body, uncovering solutions devoid of human design biases.
  3. Practical and Futuristic Applications: The implications and applications of such AI-driven designs are vast, spanning potential future developments in diverse areas such as crisis response robots capable of navigating through debris to locate survivors or nanorobots designed to traverse the human body for medical diagnoses and treatments.

Source: Northwestern University

A team led by Northwestern University researchers has developed the first artificial intelligence (AI) to date that can intelligently design robots from scratch.

To test the new AI, the researchers gave the system a simple prompt: Design a robot that can walk across a flat surface. While it took nature billions of years to evolve the first walking species, the new algorithm compressed evolution to lightning speed — designing a successfully walking robot in mere seconds.

Credit: Northwestern University

But the AI program is not just fast. It also runs on a lightweight personal computer and designs wholly novel structures from scratch. This stands in sharp contrast to other AI systems, which often require energy-hungry supercomputers and colossally large datasets. And even after crunching all that data, those systems are tethered to the constraints of human creativity — only mimicking humans’ past works without an ability to generate new ideas.

The study will be published on Oct. 3 in the Proceedings of the National Academy of Sciences.

“We discovered a very fast AI-driven design algorithm that bypasses the traffic jams of evolution, without falling back on the bias of human designers,” said Northwestern’s Sam Kriegman, who led the work.

“We told the AI that we wanted a robot that could walk across land. Then we simply pressed a button and presto! It generated a blueprint for a robot in the blink of an eye that looks nothing like any animal that has ever walked the earth. I call this process ‘instant evolution.’”

Kriegman is an assistant professor of computer science, mechanical engineering and chemical and biological engineering at Northwestern’s McCormick School of Engineering, where he is a member of the Center for Robotics and Biosystems. David Matthews, a scientist in Kriegman’s laboratory, is the paper’s first author. Kriegman and Matthews worked closely with co-authors Andrew Spielberg and Daniela Rus (Massachusetts Institute of Technology) and Josh Bongard (University of Vermont) for several years before their breakthrough discovery. 

From xenobots to new organisms

In early 2020, Kriegman garnered widespread media attention for developing xenobots, the first living robots made entirely from biological cells. Now, Kriegman and his team view their new AI as the next advance in their quest to explore the potential of artificial life. The robot itself is unassuming — small, squishy and misshapen. And, for now, it is made of inorganic materials. But Kriegman says it represents the first step in a new era of AI-designed tools that, like animals, can act directly on the world.

“When people look at this robot, they might see a useless gadget,” Kriegman said. “I see the birth of a brand-new organism.”

Zero to walking within seconds

While the AI program can start with any prompt, Kriegman and his team began with a simple request to design a physical machine capable of walking on land. That’s where the researchers’ input ended and the AI took over.

The computer started with a block about the size of a bar of soap. It could jiggle but definitely not walk. Knowing that it had not yet achieved its goal, AI quickly iterated on the design. With each iteration, the AI assessed its design, identified flaws and whittled away at the simulated block to update its structure.

This shows a robot.
New AI algorithm compresses billions of years of evolution into seconds. Credit: Neuroscience News

Eventually, the simulated robot could bounce in place, then hop forward and then shuffle. Finally, after just nine tries, it generated a robot that could walk half its body length per second — about half the speed of an average human stride.

The entire design process — from a shapeless block with zero movement to a full-on walking robot — took just 26 seconds on a laptop.

“Now anyone can watch evolution in action as AI generates better and better robot bodies in real time,” Kriegman said.

“Evolving robots previously required weeks of trial and error on a supercomputer, and of course before any animals could run, swim or fly around our world, there were billions upon billions of years of trial and error. This is because evolution has no foresight. It cannot see into the future to know if a specific mutation will be beneficial or catastrophic. We found a way to remove this blindfold, thereby compressing billions of years of evolution into an instant.”

Rediscovering legs

All on its own, AI surprisingly came up with the same solution for walking as nature: Legs. But unlike nature’s decidedly symmetrical designs, AI took a different approach. The resulting robot has three legs, fins along its back, a flat face and is riddled with holes.

“It’s interesting because we didn’t tell the AI that a robot should have legs,” Kriegman said. “It rediscovered that legs are a good way to move around on land. Legged locomotion is, in fact, the most efficient form of terrestrial movement.”

To see if the simulated robot could work in real life, Kriegman and his team used the AI-designed robot as a blueprint. First, they 3D printed a mold of the negative space around the robot’s body. Then, they filled the mold with liquid silicone rubber and let it cure for a couple hours. When the team popped the solidified silicone out of the mold, it was squishy and flexible.

Now, it was time to see if the robot’s simulated behavior — walking — was retained in the physical world. The researchers filled the rubber robot body with air, making its three legs expand. When the air deflated from the robot’s body, the legs contracted. By continually pumping air into the robot, it repeatedly expanded then contracted — causing slow but steady locomotion.

Unfamiliar design

While the evolution of legs makes sense, the holes are a curious addition. AI punched holes throughout the robot’s body in seemingly random places. Kriegman hypothesizes that porosity removes weight and adds flexibility, enabling the robot to bend its legs for walking.

“We don’t really know what these holes do, but we know that they are important,” he said. “Because when we take them away, the robot either can’t walk anymore or can’t walk as well.”

Overall, Kriegman is surprised and fascinated by the robot’s design, noting that most human-designed robots either look like humans, dogs or hockey pucks.

“When humans design robots, we tend to design them to look like familiar objects,” Kriegman said. “But AI can create new possibilities and new paths forward that humans have never even considered. It could help us think and dream differently. And this might help us solve some of the most difficult problems we face.”

Potential future applications

Although the AI’s first robot can do little more than shuffle forward, Kriegman imagines a world of possibilities for tools designed by the same program.

Someday, similar robots might be able to navigate the rubble of a collapsed building, following thermal and vibrational signatures to search for trapped people and animals, or they might traverse sewer systems to diagnose problems, unclog pipes and repair damage.

The AI also might be able to design nano-robots that enter the human body and steer through the blood stream to unclog arteries, diagnose illnesses or kill cancer cells.

“The only thing standing in our way of these new tools and therapies is that we have no idea how to design them,” Kriegman said. “Lucky for us, AI has ideas of its own.”

Funding: The study, “Efficient automatic design of robots,” was supported by Schmidt Futures (grant number G-22-64506, the Intelligence Advanced Research Projects Activity (grant number 2019-19020100001, the Defense Advanced Research Projects Agency (grant number HR001-18-2-0022) and the National Science Foundation (grant number 2020247).

About this AI and robotics research news

Author: Amanda Morris
Source: Northwestern University
Contact: Amanda Morris – Northwestern University
Image: The image is credited to Neuroscience News

Original Research: Open access.
Efficient automatic design of robots” by Sam Kriegman et al. PNAS


Efficient automatic design of robots

Robots are notoriously difficult to design because of complex interdependencies between their physical structure, sensory and motor layouts, and behavior.

Despite this, almost every detail of every robot built to date has been manually determined by a human designer after several months or years of iterative ideation, prototyping, and testing.

Inspired by evolutionary design in nature, the automated design of robots using evolutionary algorithms has been attempted for two decades, but it too remains inefficient: days of supercomputing are required to design robots in simulation that, when manufactured, exhibit desired behavior.

Here we show de novo optimization of a robot’s structure to exhibit a desired behavior, within seconds on a single consumer-grade computer, and the manufactured robot’s retention of that behavior.

Unlike other gradient-based robot design methods, this algorithm does not presuppose any particular anatomical form; starting instead from a randomly-generated apodous body plan, it consistently discovers legged locomotion, the most efficient known form of terrestrial movement.

If combined with automated fabrication and scaled up to more challenging tasks, this advance promises near-instantaneous design, manufacture, and deployment of unique and useful machines for medical, environmental, vehicular, and space-based tasks.

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