CSAIL Event Calendar: Previous Series
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.