Events

Navigation in Unstructured Environments

Date: 26 Feb 2004 - 26 Feb 2004

Venue: Auditorium, Tower Block, SIMTech, 71 Nanyang Drive

Abstract

Some of the most challenging applications for robotics lie outdoors in harsh and unstructured environments. These include land applications such as mining, construction and agriculture, maritime applications such as search and rescue, sub-sea mining, and environment monitoring, and in air applications such as mineral exploration, meteorology and defence. Autonomous navigation of robotic vehicles in unstructured environments is probably the single most important problem in enabling commercial exploitation of robotics in these applications.

This presentation will describe the current state-of-the-art in autonomous navigation for field robotics: The advent of reliable GPS and low-cost inertial sensing has had a substantial impact on navigation in many outdoor applications. Integrated GPS/INS systems of sufficient integrity and of a price appropriate for automation now allow high-speed precision navigation of autonomous vehicles in land and air applications. However, in many situations, GPS is of limited value and terrain-aided navigation using exteroperceptive sensors is required. The huge progress that has been made in simultaneous localisation and map building (SLAM) in the past five years has had a major impact on what is now achievable in terrain-aided navigation. In particular, Kalman-filter based SLAM methods have now been demonstrated in a number of high-speed long-range land and air applications. New methods employing full Bayesian SLAM techniques have addressed structured terrain navigation problems in applications such as sub-sea mapping and land-vehicle operations. There is promise that such methods will also aid in the general area of map-building for motion planning and control. 

The maturity of many navigation methods, together with our knowledge of appropriate systems engineering, now suggests that we are on the eve of many new and exciting field automation opportunities.

Biography

Hugh Durrant-Whyte received the B.Sc. (Eng.) degree (1st class honours) in Mechanical and Nuclear Engineering from the University of London, U.K., in 1983, the M.S.E. and Ph.D. degrees, both in Systems Engineering, from the University of Pennsylvania, U.S.A., in 1985 and 1986, respectively. From 1987 to 1995, he was a Senior Lecturer in Engineering Science, the University of Oxford, U.K. and a Fellow of Oriel College Oxford. Since July 1995 he has been Professor of Mechatronic Engineering at the Department of Mechanical and Mechatronic Engineering, the University of Sydney, Australia, where he leads the Australian Centre for Field Robotics (ACFR), a Commonwealth Key Centre of Teaching and Research and a team of 50 researchers working in the area of autonomous systems in land, sea and air applications. 

His research work focuses on autonomous vehicle navigation and decentralised data fusion methods. His work in applications includes automation in cargo handling, surface and underground mining, defence, unmanned flight vehicles and autonomous sub-sea vehicles. He has published over 250 technical papers and four books in the area of data fusion and autonomous systems, graduate over 40 Ph.D. students, and won numerous awards for his research and industrial work including three IEEE best paper prizes, UK Engineer of the year (1994), and the BHERT (2000) award for innovation in collaborative R&D. He has held a large number of industry grants and consultancies with companies in Australian, the US , and in Europe . Recognised internationally as one of the most innovative researchers in field robotics, Professor Hugh Durrant-Whyte was awarded Australian Research Council (ARC) Federation Fellowship in October 2002 for the project: “Information fusion in autonomous systems”.