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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Roy, D. |
| Copyright Year | 2009 |
| Description | Author affiliation: Board of Research in Nuclear Sciences Department of Atomic Energy, INDIA (Roy, D.) |
| Abstract | Rule-based data fusion for heterogeneous field sensory system is a challenging research paradigm till date, primarily due to the inherent characteristics in quantifying the output response of the system. The problem gets even critical when we need to deal with a limited number of elemental sensor-units in field, in contrast to traditional theories dealing with denser agglomeration of (identical) sensor units. In fact, field fusion models used hitherto have been found to be somewhat inappropriate for online detection of target-object(s), unless those are in a pre-assigned layout. Besides, the effect due to zonal distribution of the field-sensors was largely unattended. In answering those lacunas, the present paper dwells on the modeling, algorithm and theoretical analysis of a novel fusion rule-base, in its refined form, centering on the zone-based relative dependency of the finite numbered field sensor-units. Besides, a new proposition is developed for assessing the decision threshold-band, signaling the activation of the field robotic gripper, using a stochastic model. |
| Starting Page | 1871 |
| Ending Page | 1876 |
| File Size | 771043 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424447947 |
| DOI | 10.1109/ICAL.2009.5262650 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-08-05 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Automation Nuclear and plasma sciences Sensor fusion Sensor phenomena and characterization Sensor systems Field Robot Grippers Algorithm Heterogeneous Sensor Hypothesis Data Fusion Bayesian methods Gripper Robot sensing systems Testing Logistics |
| Content Type | Text |
| Resource Type | Article |
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