I’ve spent most of the past year discussing generative AI and large-scale language models with robotics experts. It is becoming increasingly clear that this type of technology is poised to revolutionize the way robots communicate, learn, look, and program.
Therefore, many leading universities, research institutes, and companies are exploring the best ways to leverage these artificial intelligence platforms. Agility, a well-funded Oregon-based startup, has been experimenting with the technology for some time with its bipedal robot Digit.
Today, the company is showcasing some of its accomplishments in a short video shared across its social channels.
“[W]We were curious to see what we could accomplish by integrating this technology into Digit,” the company said. “The physical embodiment of artificial intelligence created a demonstration space with a series of numbered towers of several heights and three boxes with multiple features. Digit has We were given information about the environment, but we were not given any specific information about the task, just to see if we could execute natural language commands of varying complexity.”
In the video example, Digit is instructed to pick up a box colored “Darth Vader’s Lightsaber” and move it to the tallest tower. As you might expect from early demos, the process is not instantaneous, but rather slow and methodical. However, the robot performs the task as described.
Agility says: “Our innovation team developed this interactive demo to show how LLM can make robots more versatile and faster to deploy. In this demo, people can use natural language to communicate with Digit. You can talk to it and ask it to perform tasks, giving you a glimpse into the future.”
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Natural language communication is an important potential application of this technology, along with the ability to program systems through low-code and no-code technologies.
On my Disrupt panel, Gill Pratt explained how Toyota Research Institute is using generative AI to accelerate robot learning.
We figured out how to do something. It uses the latest generative AI techniques that allow humans to demonstrate both position and force, essentially teaching the robot from just a handful of examples. The code hasn’t changed at all. What is this based on? There is a popularization policy. This is a study we conducted in collaboration with Columbia and MIT. We have taught 60 different skills so far.
MIT CSAIL’s Daniela Russ also told me recently: “Generative AI turns out to be very powerful in solving even motion planning problems. It provides much faster solutions and more fluid and human-like control solutions than using model prediction solutions. I think this is very powerful because the robots of the future will be much less robotic. Their movements will be more fluid and human-like.”
The potential applications here are wide and exciting. And Digit, as an advanced commercial robotic system being piloted in Amazon fulfillment centers and other real-world locations, seems like a prime candidate. If robots are to work alongside humans, they will also need to learn to listen to us.
Source: techcrunch.com
