Uses of Contextual Knowledge in Mobile Robots
Daniele Calisi, Alessandro Farinelli, Giorgio Grisetti, Luca Iocchi, Daniele Nardi, Stefano Pellegrini, Gian Diego Tipaldi and Vittorio Amos Ziparo
The 10th Congress of the Italian Association for Artificial Intelligence - Special Track on AI and Robotics
Roma, Italy, September 10-13, 2007
Abstract
In this paper, we analyze some work on mobile robotics with the goal of highlighting the uses of contextual knowledge aiming at a flexible and robust performance of the system. In particular, we analyze different robotic tasks, ranging from robot behavior to perception, and then propose to characterize "contextualization" as a design pattern. As a result we argue that many different tasks indeed can exploit con- textual information and, therefore, a single explicit representation of this information may lead to significant advantages both in the design and in the performance of mobile robots.