Digital Life
Teaching Robots to Move Like Humans
Atlanta, GA (March 7, 2011) — When people communicate, the way they move has as much to do with what they’re saying as the words that come out of their mouths. But what about when robots communicate with people? How can robots use non-verbal communication to interact more naturally with humans? Researchers at the Georgia Institute of Technology found that when robots move in a more human-like fashion, with one movement leading into the next, that people can not only better recognize what the robot is doing, but they can also better mimic it themselves. The research is being presented today at the Human-Robot Interaction conference in Lausanne, Switzerland.
“It’s important to build robots that meet people’s social expectations because we think that will make it easier for people to understand how to approach them and how to interact with them,” said Andrea Thomaz, assistant professor in the School of Interactive Computing at Georgia Tech’s College of Computing.
Thomaz, along with Ph.D. student Michael Gielniak, conducted a study in which they asked how easily people can recognize what a robot is doing by watching its movements.
“Robot motion is typically characterized by jerky movements, with a lot of stops and starts, unlike human movement which is more fluid and dynamic,” said Gielniak. “We want humans to interact with robots just as they might interact with other humans, so that it’s intuitive.”
Using a series of human movements taken in a motion-capture lab, they programmed the robot, Simon, to perform the movements. They also optimized that motion to allow for more joints to move at the same time and for the movements to flow into each other in an attempt to be more human-like. They asked their human subjects to watch Simon and identify the movements he made.
“When the motion was more human-like, human beings were able to watch the motion and perceive what the robot was doing more easily,” said Gielniak.
In addition, they tested the algorithm they used to create the optimized motion by asking humans to perform the movements they saw Simon making. The thinking was that if the movement created by the algorithm was indeed more human-like, then the subjects should have an easier time mimicking it. Turns out they did.
“We found that this optimization we do to create more life-like motion allows people to identify the motion more easily and mimic it more exactly,” said Thomaz.
The research that Thomaz and Gielniak are doing is part of a theme in getting robots to move more like humans move. In future work, the pair plan on looking at how to get Simon to perform the same movements in various ways.
“So, instead of having the robot move the exact same way every single time you want the robot to perform a similar action like waving, you always want to see a different wave so that people forget that this is a robot they’re interacting with,” said Gielniak.
For more information contact:
David Terraso
Communications and Marketing
404-385-2966
Photos
Click on an image below to see the full photo
Media
Click on an image to launch a media file.
Video Clip
Faculty
-
Associate Professor
School of Interactive Computing, College of ComputingAreas of Expertise:
Educational Technology, Social Networking/Online Communities, Wikipedia, Twitter, Facebook, Internet Research Ethics, Human Computer Interaction, Human Computer Interaction for Kids -
Assistant Professor
School of Literature, Communication and Culture, Ivan Allen College of Liberal ArtsAreas of Expertise:
Participatory Design, Critical Design, Design Studies, Robotics and Sensing in Art and Community Settings -
Associate Professor
School of Interactive Computing, College of ComputingAreas of Expertise:
Social Impacts of Technology, Home Network Security, Home Networking, Human-Computer Interaction -
Professor
School of Interactive Computing, College of Computing
School of Electrical and Computer Engineering, College of EngineeringAreas of Expertise:
Computational Video, Computational Photography, Computational Journalism, Computational Media, Computational Perception -
Associate Professor
School of Interactive Computing, College of ComputingAreas of Expertise:
Societal Impacts of Technology, Human-Computer Interaction, Computer Supported Cooperative Work -
Executive Director, FutureMedia
Areas of Expertise:
Convergence of digital, social, mobile and multimedia industries, Strategic Alliances, Industry Partnerships, Open Innovation Practices -
Associate Professor
School of Interactive Computing, College of Computing
School of Literature Communication and Culture, Ivan Allen College of Liberal ArtsAreas of Expertise:
Augmented Reality, Virtual Reality, Mobile Games, Social Games, Augmented Reality Games, Video Game Design, Video Game Architecture -
Assistant Professor
School of Literature, Communication and Culture, Ivan Allen College of Liberal ArtsAreas of Expertise:
Tangible Interfaces, Experimental Media, Media Arts, Interaction Design, Emerging Technologies -
Ivan Allen College Dean's Professor
School of Literature, Communication and Culture, Ivan Allen College of Liberal ArtsAreas of Expertise:
Game Design, Interactive Narrative, Interactive Television, Media Convergence, Information Design, Digital Media and Education -
Director, GVU Center
Professor, School of Interactive Computing
Associate Dean for Strategic Planning and Initiatives
College of ComputingAreas of Expertise:
Human-Computer Interaction, Human-Centered Computing, Health Informatics, Ubiquitous Computing, Assistive Technologies -
Associate Professor
School of Interactive Computing, College of ComputingAreas of Expertise:
Artificial Intelligence (AI) (Case-Based Reasoning, Natural Language, & Game/Entertainment AI), Human-Centered Computing - Cognitive Science, Healthcare Informatics -
Associate Professor
School of Psychology, College of Sciences School of Interactive Computing, College of ComputingAreas of Expertise:
Interactive Music, Mobile Music, Human-Computer Interaction, Auditory Perception, Psychology