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First, by broadening our conception of what constitutes a robot, I argue that we have already accepted many non-humanoid robots, and that even robotic entities without a visual presence can be compelling and engaging.
The model overcomes perceptual aliasing and robot localization by recalling the encoded episodes with a new anticipation function and generates sensorimotor map to connect episodes together to execute tasks continuously with little to no human intervention.
When the subjects do behave naturally, the rhythm and its variations truly reflects how well the interaction is going and helps the robot learn efficiently.
Experimental results for a mobile robot indicate that EEM-ART can process multiple sensory sources for learning events and encoding episodes simultaneously.
It is argued here that people base their expectations and perceptions of a robot on its form and attribute functions which do not necessarily mirror the true functions of the robot.
Open accessProceedings ArticleDOI
30 Aug 2011
79 Citations
There were indications that these were associated with episodes where the robot malfunctioned, so this raises the possibility of users trust in the robot affecting HRP distance.

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