Walker, R.J. and Harris, C.J.
A Multi-Sensor Fusion System for a Laboratory Based Autonomous Vehicle
At 1st Int. Workshop on Intelligent Autonomous Vehicles.
Full text not available from this repository.
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.
Conference or Workshop Item
||Organisation: IFAC Address: Southampton, UK
|Venue - Dates:
||1st Int. Workshop on Intelligent Autonomous Vehicles, 1993-09-01
||Southampton Wireless Group
||04 May 1999
||18 Apr 2017 00:22
|Further Information:||Google Scholar|
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