CSAIL Event Calendar: Previous Series
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Autonomous Large-Scale Mapping and Navigation Speaker: John J. Leonard , MIT The problem of simultaneous mapping and localization (SLAM) is stated as follows: starting from an initial position, a mobile robot travels through a sequence of positions and obtains a set of sensor measurements at each position. The goal is for the mobile robot to process the sensor data to compute an estimate of its position while concurrently building a map of the environment. The motivation for our work is to develop new SLAM algorithms for autonomous underwater vehicles (AUVs). This talk will describe a number of recent contributions to the state-of-the-art in SLAM, including: (1) methods for robust feature-based mapping with wide-beam sonar data, (2) a framework for very large-scale mapping, (3) the integration of autonomous exploration with SLAM, and (4) cooperative mapping by multiple vehicles. Numerous experimental results will be shown, including large-scale mapping of part of the MIT campus, participation in the AAAI 2002 challenge competition, and the implementation of SLAM with ocean data from an Odyssey III AUV.
See other events that are part of AI Colloquium Series Spring 2003 |
