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The interactive museum tour-guide robot

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TLDR
In this paper, the authors describe the software architecture of an autonomous tour-guideltutor robot, which was recently deployed in the "Deutsches Museum Bonn," were it guided hundreds of visitors through the museum during a six-day deployment period.
Abstract
This paper describes the software architecture of an autonomous tour-guideltutor robot. This robot was recently deployed in the "Deutsches Museum Bonn," were it guided hundreds of visitors through the museum during a six-day deployment period. The robot's control software integrates low-level probabilistic reasoning with high-level problem solving embedded in first order logic. A collection of software innovations, described in this paper, enabled the robot to navigate at high speeds through dense crowds, while reliably avoiding collisions with obstacles--some of which could not even be perceived. Also described in this paper is a user interface tailored towards non-expert users, which was essential for the robot's success in the museum. Based on these experiences, this paper argues that time is ripe for the development of AI-based commercial service robots that assist people in everyday life.

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References
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Proceedings ArticleDOI

Combining labeled and unlabeled data with co-training

TL;DR: A PAC-style analysis is provided for a problem setting motivated by the task of learning to classify web pages, in which the description of each example can be partitioned into two distinct views, to allow inexpensive unlabeled data to augment, a much smaller set of labeled examples.
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