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locked locations and one of them has switched the locations, Leonardo can watch the first human trying to get to where he thinks the cookies are and open a box with cookies, helping him achieve his goal. All of
Leonardo's social skills work together so it can work alongside humans. When a human asks it to do a task, it can indicate what it knows or doesn't know and what it can and cannot do. Communicating through expression and gesture and through perceiving expression, gesture, and speech, the robot is able to work as part of a team.
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about to discuss or do something with. The
Personal Robots Group has used Leonardo's tracking ability and programmed the robot so it can act human-like, bringing its gaze to an object the human is paying attention to. Matching the human's gaze is one way Leonardo seems to exhibit more natural behavior. Sharing attention like this is one of the ways that allows the robot to learn from a human. The robot's expressions, being able to give feedback on its “understanding” is also vital.
147:, however, by examining the data it gets from mimicking human facial expressions, body language, and speech. In a similar way, humans can understand what other humans might be feeling based on the same data, Leonardo has been programmed according to the rules of simulation theory, allowing it to render something like empathy. In these ways, social interaction with Leonardo seems more human-like, making it more likely humans will be able to work with the robot in a team.
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other's perspectives, and it's the same for a social robot. Being able to understand that “others” don't have the same knowledge it has lets the robot view its environment more accurately and make better decisions based in its programming of what to do in a given situation. It also allows the robot to distinguish between a human's intentions and their actual actions, since humans are not exact. This would allow a human without special training to teach the robot.
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Leonardo can work together with a human to solve a common problem as much as his body allows. He's more effective at working shoulder-to-shoulder with a human because of the theory of mind work that is blended with his programming. In a task where one human wants cookies and another crackers from two
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Leonardo can also track what a human is looking at. This allows the robot to interact with a human and objects in the environment. Naturally, humans will follow a pointing gesture and/or gaze and understand that what is being pointed at or looked at is the object the other human is concerned with and
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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,
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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
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Leonardo can explore on its own, in addition to being trained with a human, which saves time and is a key factor in the success of a personal robot. It must be able to learn quickly using the mechanisms humans already use (like spatial scaffolding, shared attention, mimicry, and perspective taking).
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Leonardo learns through spatial scaffolding. One of the ways a teacher teaches is by positioning objects near to the student that they expect the student to use. This same technique, spatial scaffolding, can be used with
Leonardo, who is taught to build a sailboat from virtual blocks, using only the
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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
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Another way that Leo learns is by mimicry. The same way infants learn to understand and manipulate their world is helpful for the social robot. By mimicking human facial expressions and body movement, Leo can distinguish between self and other. This ability is important for humans in taking each
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The goal of creating
Leonardo was to make a social robot. Its motors, sensors, and cameras allow it to mimic human expression, interact with limited objects, and track objects. This helps humans react to the robot in a more familiar way. Through this reaction, humans can engage the robot in more
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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.
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red and blue blocks. Whenever it tries to use a green block, the teacher pulls the “forbidden” color away and moves the red and blue blocks into the robot's space. Leonardo learns, in this way, to build the boat using red and blue blocks only.
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It also cannot require an extensive amount of time. And finally, it should be a pleasure to interact with, which is why aesthetics and expression are so important. These are all important steps in bringing the robot into a home.
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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
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Andrew Brooks and
Cynthia Breazeal (2006). "Working with Robots and Objects: Revisiting Deictic Reference for Achieving Spatial Common Ground". Salt Lake City: Human Robot Interaction.
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naturally social ways. Leonardo's programming blends with psychological theory so that he learns more naturally, interacts more naturally, and collaborates more naturally with humans.
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Shared attention and perspective taking are two mechanisms
Leonardo has access to that help it interact naturally with humans. Leonardo also can achieve something like
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Breazeal, Cynthia; Cory Kidd; Andrea Thomaz; Guy
Hoffman; Matt Berlin. "Effects of Nonverbal Communication on Efficiency and Robustness in Human-Robot Teamwork".
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Breazeal, Cynthia; Matt Berlin; Andrew Brooks; Jesse Gray; Andrea Thomaz (2006). "Using perspective taking to learn from ambiguous demonstrations".
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The group plans that
Leonardo will have skin that can detect temperature, proximity, and pressure. To accomplish this, they are experimenting with
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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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Brooks, Andrew; Cynthia Breazeal (2006). "Working with Robots and Objects: Revisiting Deictic Reference for Achieving Spatial Common Ground".
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Applying a “Somatic Alphabet” Approach to Inferring Orientation, Motion, and Direction in Clusters of Force Sensing Resistors
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Learning From and About Others: Towards Using Imitation to Bootstrap the Social Understanding of Others by Robots
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Sensitive Skins and Somatic Processing for Affective and Sociable Robots Based upon a Somatic Alphabet Approach
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to interact with and teach the robot much more quickly with fewer repetitions. Leonardo was awarded a spot in
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A “Sensitive Skin” for Robotic Companions Featuring Temperature, Force, and Electric Field Sensors
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An Embodied Cognition Approach to Mindreading Skills for Socially Intelligent Robots
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Perspective Taking: An Organizing Principle for Learning in Human-Robot Interaction
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Understanding the Embodied Teacher: Nonverbal Cues for Sociable Robot Learning
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Robot Science Meets Social Science: An Embodied Model of Social Referencing
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429:"Furry Robots, Foldable Cars and More Innovations from MIT's Media Lab"
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Learning from Human Teachers with Socially Guided Exploration
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Action parsing and goal inference using self as simulator
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Robot’s Play: Interactive Games With Sociable Machines
666:. MIT Media Lab Personal Robots Group. Archived from
641:. MIT Media Lab Personal Robots Group. Archived from
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556:. MIT Media Lab Personal Robots Group. Archived from
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506:. MIT Media Lab Personal Robots Group. Archived from
456:. MIT Media Lab Personal Robots Group. Archived from
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An Embodied Computational Model of Social Referencing
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Teaching and Working with Robots as a Collaboration
317:A “Somatic Alphabet” Approach to “Sensitive Skin”
68:consortia have partially funded the project. The
384:Spatial Scaffolding for Sociable Robot Learning
56:Mobile Autonomous Robot Software (MARS) grant,
369:Robot Learning via Socially Guided Exploration
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409:Working Collaboratively with Humanoid Robots
399:Tutelage and Socially Guided Robot Learning
394:The dynamic lift of developmental process
751:. Massachusetts Institute of Technology.
639:"Leonardo Project Social Cognition Page"
582:"Leonardo Project Social Learning Page"
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20:Leonardo's body by Stan Winston Studios
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72:Robotic Life Group, who also studied
33:Massachusetts Institute of Technology
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60:Young Investigators Program grant,
342:Collaboration in Human-Robot Teams
81:50 Best Robots Ever list in 2006.
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431:. PBS. 2011-05-20. Archived from
35:. Its development is credited to
664:"Project Leonardo Teamwork Page"
176:Lindsay MacGowan (Artistic Lead)
719:Robotics and Autonomous Systems
179:Richard Landon (Technical Lead)
529:"Leonardo Project Vision Page"
182:The Stan Winston Studios Team
46:Lyndon B. Johnson Space Center
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481:Robert Capps (January 2006).
103:quantum tunnelling composites
554:"Leonardo Project Skin Page"
504:"Leonardo Project Body Page"
454:"Leonardo Project Home Page"
812:Robots of the United States
747:Stiehl, Walter Dan (2005).
731:10.1016/j.robot.2006.02.004
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769:TED Talk: Cynthia Breazeal
483:"The 50 Best Robots Ever"
783:(New York Times article)
235:Fardad Faridi (Animator)
58:Office of Naval Research
702:10.1145/1121241.1121292
694:Human Robot Interaction
99:force-sensing resistors
50:human–robot interaction
619:Cite journal requires
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781:The Real transformers
763:Personal Robots Group
266:Matt Hancher (Alumni)
258:Andrea Lockerd Thomaz
218:Rodrick Khachatoorian
52:and collaboration. A
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765:(Leonardo home page)
244:Andrew “Zoz” Brooks
774:2020-11-09 at the
352:2017-08-08 at the
238:Graduate Students
230:Annabelle Troukens
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66:Things that Think
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172:Stan Winston
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139:Interacting
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415:References
261:Dan Stiehl
247:Jesse Gray
206:Joe Reader
165:Professor
772:Archived
350:Archived
300:Robotics
290:Robonaut
274:See also
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185:Jon Dawe
118:Learning
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25:Leonardo
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