Leonardo (robot)

Leonardo is a 2.5 foot social robot, the first created by the Personal Robots Group of the Massachusetts Institute of Technology. Its development is credited to Cynthia Breazeal. The body is by Stan Winston Studios, leaders in animatronics. Its body was completed in 2002. It was the most complex robot the studio had ever attempted as of 2001. Other contributors to the project include NevenVision, Inc., Toyota, NASA’s Lyndon B. Johnson Space Center, and the Navy Research Lab. It was created to facilitate the study of human–robot interaction and collaboration. A DARPA Mobile Autonomous Robot Software (MARS) grant, Office of Naval Research Young Investigators Program grant, Digital Life, and Things that Think consortia have partially funded the project. The MIT Media Lab Robotic Life Group, who also studied Robonaut 1, set out to create a more sophisticated social-robot in Leonardo. They gave Leonardo a different visual tracking system and programs based on infant psychology that they hope will make for better human-robot collaboration. One of the goals of the project was to make it possible for untrained humans to interact with and teach the robot much more quickly with fewer repetitions. Leonardo was awarded a spot in Wired Magazine’s 50 Best Robots Ever list in 2006.

There are approximately sixty motors in the small space of the robot body that make the expressive movement of the robot possible. The Personal Robot Group developed the motor control systems (with both 8-axis and 16-axis control packages) that they’ve used for Leonardo. Leonardo does not resemble any real creature, but instead has the appearance of a fanciful being. Its face was designed to be expressive and communicative since it is a social robot. The fanciful, purposefully young look is supposed to encourage humans to interact with it in the same way they would with a child or pet.

A camera mounted in the robot’s right eye captures faces. A facial feature tracker developed by the Neven Vision corporation isolates the faces from the captures. A buffer of up to 200 views of the face is used to create a model of the person whenever they introduce themself via speech. Additionally, Leonardo can track objects and faces visually using a collection of visual feature detectors that include color, skin tone, shape, and motion.

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