Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder. Abstract Ships often use the coasts of continents for navigation in the absence of better tools such as GPS, since being close to land allows sailors to determine with high accuracy where they are. Similarly for mobile robots, in many environments global and accurate localization is not always feasible.
Environments can lack features, and dynamic obstacles such as people can confuse and block sensors.
In this paper, we demonstrate a technique for generating trajectories that take into account both the information content of the environment, and the density of the people in the environment. These trajectories reduce the average positional certainty as the robot moves, reducing the likelihood the robot will become lost at any point. Our method was successfully implemented and used by the mobile robot Minerva, a museum tourguide robot, for a 2 week period in the Smithsonian National Museum of American History. Proc. IEEE Conf. For updates and comments, please see these instructions .