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We investigate how a humanoid robot with a randomly initialized binocular vision system can learn to improve judgments about egocentric distances using limited action and interaction that might be available to human infants. First, we show how distance estimation can be improved autonomously. We consider our approach to be autonomous because the robot learns to accurately estimate distance without...
As we move along the scale of adjustable autonomy for the control of robots from direct teleoperation at one extreme to full automation at the other, several opportunities for improvement in control quality, user feedback and machine learning suggest themselves. We describe three experiments, in telerobotics, the provision of situational awareness, and the acquisition of knowledge for automation from...
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