Sensor Action Planning driven by Uncertainty : Application to Object Location with Robust Local Sensors in a Nuclear Environment
p. 115-131
Abstract
This paper presents an integrated Bayesian solution to the problem of object location estimation, object recognition and sensor action planning under uncertainty. The emphasis is on finding the best next sensing action.
The method uses elementary notions from Bayesian decision theory. The best action is found as the one that optimises the expected value of a utility function, which is the logarithm of the volume of the uncertainty ellipsoid around the estimate of a target position.
An example shows that this method is capable of controlling the sensing actions of an ultrasonic sensor mounted on a robot, where the target is to accurately position a drill on a cylinder before drilling a hole.
The presented algorithm is easy to apply and computationally tractable.
Index
Text
References
Bibliographical reference
J. De Geeter, J. De Schutter, M. Decréton and H. Van Brussel, « Sensor Action Planning driven by Uncertainty : Application to Object Location with Robust Local Sensors in a Nuclear Environment », CASYS, 2 | 1998, 115-131.
Electronic reference
J. De Geeter, J. De Schutter, M. Decréton and H. Van Brussel, « Sensor Action Planning driven by Uncertainty : Application to Object Location with Robust Local Sensors in a Nuclear Environment », CASYS [Online], 2 | 1998, Online since 28 June 2024, connection on 10 January 2025. URL : http://popups.lib.uliege.be/1373-5411/index.php?id=402
Authors
J. De Geeter
SCK-CEN Belgian Research Centre for Nuclear Energy,
Teleoperation Project, Boeretang 200, B-24A0 Mol, Belgium
J. De Schutter
K.U.Leuven, Dept. of Mechanical Engineering, Div. PMA, Celestijnenlaan 3008, 3001 Heverlee, Belgium
M. Decréton
SCK-CEN Belgian Research Centre for Nuclear Energy, Teleoperation Project, Boeretang 200, B-24A0 Mol, Belgium
H. Van Brussel
K.U.Leuven, Dept. of Mechanical Engineering, Div. PMA, Celestijnenlaan 3008, 3001 Heverlee, Belgium