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. 1st Int. Workshop on Intelligent Autonomous Vehicles , 107--112.
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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.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
|Additional Information:||Organisation: IFAC Address: Southampton, UK|
|Divisions:||Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||04 May 1999|
|Last Modified:||27 Mar 2014 19:51|
|Further Information:||Google Scholar|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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