Selective Use of Multiple Sources of Robot Sensory Information
Speaker: Manuela M. Veloso , Carnegie Mellon University
Date: Thursday, May 24 2007
An autonomous robot needs to assess the state of the environment, make decisions towards achieving its goals, and execute the selected actions. In teams of autonomous robots, robots have individually limited perception, but can communicate state information to each other creating therefore multiple perceptual inputs. We present an algorithm for selectively merging and using the own perceptual data combined with the communicated data from teammate robots. In general, robots face the challenge of combining multiple sources of sensory information. We illustrate different concrete instances of this problem and discuss a prioritized approach to effectively merge multi-modal information. The talk will be organized as an explanation of the algorithms underlying a series of different robot videos, including robot soccer players, humanoid robot soccer commentators, and machine visual object recognition.
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