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A Multi-Sensor Fusion System for a Laboratory Based Autonomous Vehicle

Walker, R.J. and Harris, C.J. (1993) A Multi-Sensor Fusion System for a Laboratory Based Autonomous Vehicle At 1st Int. Workshop on Intelligent Autonomous Vehicles. , 107--112.

Record type: Conference or Workshop Item (Other)

Abstract

Motivated by the desire to generate richer descriptions of world state from disparate information sources the research area of Multi Sensor Data Fusion (MSDF) based upon a distributed Kalman Filter is addressed in this paper. To demonstrate the approach the MSDF system is applied i) in simulation to a second order plant and ii) to a laboratory based robot. MSDF research has demonstrated greater accuracy of state estimation which leads to greater system robustness with respect to sensor failure/sensor error. In addition the applicataion of MSDF to systems with zero mean noise processes generates a Kalman filtered state estimate that is less sensitive to poor choices of system and process noise models.

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More information

Published date: September 1993
Additional Information: Organisation: IFAC Address: Southampton, UK
Venue - Dates: 1st Int. Workshop on Intelligent Autonomous Vehicles, 1993-09-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250371
URI: http://eprints.soton.ac.uk/id/eprint/250371
PURE UUID: 8d561549-e120-47cd-b411-5eacb248a116

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:42

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Contributors

Author: R.J. Walker
Author: C.J. Harris

University divisions

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