Professor Peter Stone of The University of Texas at Austin started using the NAO when it was selected as the standard platform for international RoboCup competitions in 2008. His team participates in the annual RoboCup robot soccer competitions, and uses the event as a platform for evaluating and testing their ongoing research in machine learning, multiagent systems, and robotics.
“[NAO] is a great, affordable platform for research on all aspects of humanoid robotics, from locomotion, to localization, to visual processing, to multiagent collaboration. I also use it as the main platform for a graduate course on autonomous robots.”, says Professor Stone.
During his time using NAO, he has also noted that the students find the robots very appealing to work with - often choosing to work long hours trying to perfect NAO’s behaviors. Visitors to the lab are always immediately engaged and captivated by the robots as well.
“When we do open house demonstrations for the general public, seeing the robots working is always a captivating demonstration of the interest and promise of autonomous robotics.”
Professor Stone’s main interest has been in understanding how we can create “complete intelligent agents.” In order to create these agents, they would need adaptation and natural interaction abilities, so he has focused his research on machine learning, robotics, and multiagent systems.
“To me, the most exciting research topics are those inspired by challenging real-world problems.”
For his purposes, Professor Stone has found NAO to be a great platform. In particular, one of his team’s main research advances was creating a more efficient framework for visual recognition of the soccer ball used in the RoboCup. They are also working on a project to transfer learned behaviors and movements (motions) to robots from a simulator. The possibilities are very exciting!
You can see an example of NAO performing in the RoboCup here:
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