Autonomous Systems
 

Education

 


KC-3S Introduction to Data Fusion
Leader: Prof Hugh Durrant-Whyte

Aim
This is a one day course on data fusion given at ICARCV, December 2002 in Singapore. It is essentially a cut-down version of a three day intensive course on Multi-Sensor Data Fusion given by ACFR staff. The course is aimed at professional engineers and research scientists wishing to acquire a practical knowledge of data fusion methods. The course covers essential methods in multi-sensor estimation, identification, distributed and decentralised data fusion methods. The course emphasizes applications in multi-sensor tracking, distributed sensor systems and multi-sensor navigation.

Description
Part 1: Probabilistic models, discrete and continuous Bayesian and information fusion methods. Laboratory: Data fusion with Bayes theorem.

Part 2: The multisensor Kalman filter, non-linear Multisensor methods, multisensor multi-target tracking. Laboratory: Multisensor multi-target tracking.

Part 3: Distributed and decentralised data fusion methods, multi-person decision theory. Laboratory: Distributed and decentralised data fusion.

The Centre for Autonomous Systems finished at the end of 2010. This web site is kept as an example of the work undertaken by the Centre between 2003 and 2010.

This web site is hosted by the Australian Centre for Field Robotics. Please check the ACFR web site for the latest work in this and similar fields of research.