Details of Grant 

EPSRC Reference:	GR/S62215/01
Title:	Multi-Vehicle Field Based SLAM
Principal Investigator:	Newman, Professor PM
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department:	Engineering Science
Organisation:	University of Oxford
Scheme:	First Grant Scheme Pre-FEC
Starts:	01 October 2003	Ends:	30 September 2006	Value (£):	123,937
EPSRC Research Topic Classifications:	Image & Vision Computing Robotics & Autonomy
EPSRC Industrial Sector Classifications:	No relevance to Underpinning Sectors
Related Grants:
Panel History:
Summary on Grant Application Form
The SLAM problem is of fundamental importance in the quest for autonomous mobile machines. It binds aspects of machine leaming,uncertainty management, perception, sensing and control to enable a machine to discover and understand its surroundings with no prior knowledge or external assistance. An interesting, timely and compelling extension of the SLAM problem is into the domain of multiple vehicles. Instead of having just one vehicle performing SLAM, several vehicles share either sensor measurements or entire maps. The research proposed here seeks to answer key multivehicle SLAM questions. How can vehicles execute collaborative manoeuvres to maximise various criteria such as localisation accuracy, map accuracy, mapping speed? How should information be gathered, processed and shared across the fleet as a whole? An information theoretic standpoint will be taken. Each vehicle will be considered as a mobile sensor capable of publishing a spectrum of data from raw measurements to complete maps. The data fusion architecture, vehicle trajectory planning and sensor control policies are driven by information and performance metrics of the multi-vehicle SLAM algorithm and mission criteria. The most troublesome yet inspiring arena (in terms of applications) for autonomy is the unstructured outdoor field environment. With this ultimate goal in mind.the algorithms will be tested and devolved on two small outdoor mobile vehicles.
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Organisation Website:	http://www.ox.ac.uk