Computer system will need to posses specific conversational skills similar to those learned by those humans who have successfully mastered the conventions governing the way that we talk to one another. The soundtracks will then be stored in a full-text information retrieval system developed at the university's Center for Machine Translation. The system allows for rapid retrieval of individual video sequences based on key words in the sound track. Users will be able to rapidly scan video without a loss of perception, as they might when skimming written material. Vision technology developed at Carnegie Mellon's Robotics Institute can segment the videotape into meaningful units called video paragraphs.
Users can also search the video for similarity of the visual content.
The Learning Robots Laboratory at Carnegie Mellon University focuses on combining perceptual reasoning, learning and planning for autonomous mobile robots. In order to be successful, a mobile robot has to be able to deal with incomplete and incorrect state descriptions caused by limited and noisy sensors. It must be able to learn from a limited number of examples, because a robot can not execute millions of trials before getting it right. A robot must robustly interact with the environment both for efficient exploration and to exploit the information it has learned. The planning for the robot must take into account the robot's expected performance characteristics and its limited computation.