Abstract:
This paper presents the iRobot corporation's Roomba vacuum as a low-cost resource for robotics research and education. Sensor and actuation models for unmodified Roombas ...Show MoreMetadata
Abstract:
This paper presents the iRobot corporation's Roomba vacuum as a low-cost resource for robotics research and education. Sensor and actuation models for unmodified Roombas are presented in the context of both special- and general-purpose spatial-reasoning algorithms, including Monte Carlo Localization and FastSLAM. Further tests probe the feasibility of sensor extensions to the platform. Results demonstrate that, with some caveats, the Roomba is a viable foundation for both classroom and laboratory use, especially for work seeking to leverage robots to other ends, as well as robotics per se with a computational focus.
Date of Conference: 10-14 April 2007
Date Added to IEEE Xplore: 21 May 2007
ISBN Information:
Print ISSN: 1050-4729