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Robotics Institute Seminar, November 13, 1998
Robotics Institute
Carnegie Mellon University
Pittsburgh PA 15213-3891
412/268-8525 . 412/268-5576 (fax)

This page is provided for historical and archival purposes only. While the seminar dates are correct, we offer no guarantee of informational accuracy or link validity. Contact information for the speakers, hosts and seminar committee are certainly out of date.

Concurrent Mapping and Localization for Autonomous Underwater Vehicles

John J. Leonard, Assistant Professor
Department of Ocean Engineering
The Massachusetts Institute of Technology

Place and Time
Adamson Wing, Baker Hall
Refreshments 3:15 pm
Talk 3:30 pm

The goal of concurrent mapping and localization (CML) is to enable a mobile robot to build a map of an unknown environment, while simultaneously using this map to navigate. CML has been a popular topic in the robotics research community, due to its theoretical challenges and critical importance for many mobile robot applications. The objective of our research is to develop new methods for CML that can provide improved navigation capabilities to autonomous underwater vehicles (AUVs). The primary obstacle for AUV navigation and mapping in unknown environments is the difficulty of effectively incorporating measurement data to aid in navigation. State of the art CML approaches fail because they do not fully account for data association, navigation, and prior model uncertainties. This talk will describe an integrated mapping and navigation (IMAN) algorithm that accounts for these uncertainties within a general, unified framework. The first half of the talk will review the current state-of-the-art in AUV navigation technology and will define the concurrent mapping and localization problem. The merits of a feature-based approach to CML will be illustrated using real data from a US Navy high resolution forward-look imaging sonar system. The second half of the talk will describe the IMAN algorithm and analyze its performance using Monte Carlo simulations of an AUV equipped with a forward look sonar. Although further research is required to provide robust recovery from highly ambiguous situations, IMAN is shown to be a valid generalized approach to CML.

Speaker Biography
John J. Leonard is Assistant Professor of Ocean Engineering at MIT. His research addresses sensor data fusion in marine robotics, with emphasis on the problems of sonar perception and navigation for autonomous underwater vehicles. He teaches several undergraduate courses that include the topics of acoustics, oceanography, and design of ocean systems, and is developing a new graduate course in marine robotics. He received the degree of B.S.E. in Electrical Engineering and Science from the University of Pennsylvania in 1987 and the D.Phil. in Engineering Science at the University of Oxford in 1991. His thesis research at Oxford addressed the problems of localization and map building for land robots using ultrasonic range sensing. In 1990 and 1991, he was a Visiting Scientist at NEC Research Institute in Princeton, NJ. From 1991 to 1996, he was a Postdoctoral Fellow and Research Engineer in the Autonomous Underwater Vehicles Laboratory at the MIT Sea Grant College Program. He currently holds the Henry L. and Grace Doherty Assistant Professorship in Ocean Utilization and an NSF CAREER award.

Speaker Appointments
For appointments, please contact the host, Tony Stentz, at axs@ri.cmu.edu.

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