By Abby Burns Correspondent
The schools of Engineering and Science recently co-sponsored a presentation by Columbia University mechanical engineering Professor Hod Lipson in Mayo Concert Hall. On Wednesday, April 20, Lipson spoke to a group of students and faculty at the College about his research on self-aware and self-replicating robots.
He started his lecture with a story of how he got to where he is now at Columbia University, saying that it took years and “a lot of serendipity and research.” He co-authored the award-winning book “Fabricated: The New World of 3-D Printing” and directs the Creative Machines Lab at Columbia University, where he discovers new ways to make machines that are creative and innovative.
Lipson focuses his research on evolutionary robotics, a branch of robotics that uses processes inspired by biological evolution to “breed” new robots, rather than design them manually.
While researching robotics, Lipson learned the one major weakness of all robots — their inability to adapt to change. From then on, he made it his main goal to create robots that are self-aware and able to adapt to the world around them.
The first two approaches Lipson discussed to building these self-aware robots were the “adapting in simulation approach,” in which the robotics scientists evolve the controller in a virtual simulation before trying it in reality, and the “adapting in reality approach,” where the scientists evolve the controller in reality with no virtual simulation. After trying both of these approaches to building new robots, Lipson found problems with each — the first resulted in a “simulation-reality gap,” as the virtual simulations did not perform the same in reality, and the second approach took too much time and resulted in worn-out robots.
Instead, Lipson combined the approaches to make the “simulation and reality approach,” which is essentially a cycle of evolving and collecting data. The first step is to evolve the virtual simulator, then evolve the robots and try it in reality to collect sensor data — what the robot does and feels. The data is used to breed better simulators and the cycle continues until all of the necessary data is collected.
Lipson used this approach to build a four-legged robot, which had to be self-aware and figure out how to move on its own. It took a few days of trial and error for the robot to learn about itself.
“It does not know what it looks like. It wouldn’t even know if it was a snake or a tree,” Lipson said.
However, after four days, it figured out that it had four legs. Lipson played a video of the robot forming a self-image — learning what it looked like without being programed to do so. The audience watched in amazement as the robot learned how to move forward on its own.
Next in the video, Lipson decided to test how the robot performed with damage recovery by removing one its four legs. Remarkably, the robot’s dynamics changed and it adapted to find a new way to move forward without the leg.
In an interview on columbia.edu, Lipson discussed what it felt like to watch a robot he built be self-aware.
“It’s always surprising to see new systems evolve or learn on their own,” Lipson said. “Seeing a robot learn to do something you didn’t program it to do is a pretty amazing experience.”
During the lecture, Lipson also discussed the artificial intelligence software he created called Eureqa, which finds equations and mathematical relationships in data. The software is available for anyone to download on nutonian.com — the Website aimed at professionals looking to accomplish the work of data scientists — and is used by thousands to detect difficult calculations in large amounts of data. Machines with this software can formulate hypotheses, design experiments and interpret the results to discover new scientific laws.
Robots and machines that can model themselves have huge practical implications in the real world, Lipson said, and he hopes to continue to evolve self-aware robots over time. He believes that he is on his way to creating the holy grail of robotics, which would be a robot that is self-aware right out of a 3-D printer.
“I don’t know if we’ll get there in my lifetime, but we’re on the path that will eventually lead there,” Lipson said.