Special issue "Sensor Fusion". A Perspective on Multisensor Fusion and Integration.
نویسندگان
چکیده
منابع مشابه
Multisensor Fusion and Integration
Multisensor fusion and integration is a rapidly evolving research area and requires interdisciplinary knowledge in control theory, signal processing, artificial intelligence, probability and statistics, etc. The advantages gained through the use of redundant, complementary, or more timely information in a system can provide more reliable and accurate information. This paper provides an overview...
متن کاملA Tutorial on Multisensor Integration and Fusion
ion. Symbol-level fusion may be the only means by which sensory information can be fused if the information provided by the sensors is very dissimilar or refers to different regions in the environment. The symbols used for fusion can originate either from the processing of the information provided by the sensors in the system, or through symbolic reasoning processes that may make we of a priori...
متن کاملMultisensor integration and fusion in intelligent systems
Interest has been growing in the use of multiple sensors to increase the capabilities of intelligent systems. The issues involved in integrating multiple sensorsinto the operation of a system are presented in the context of the type of information these sensors can uniquely provide. The advantages gained through the synergistic use of multisensory information can be decomposed into a combinatio...
متن کاملAlgorithms for Sensor Validation and Multisensor Fusion
Doctor of Philosophy ALGORITHMS FOR SENSOR VALIDATION AND MULTISENSOR FUSION by Sean James Wellington Existing techniques for sensor validation and sensor fusion are often based on analytical sensor models. Such models can be arbitrarily complex and consequently Gaussian distributions are often assumed, generally with a detrimental effect on overall system performance. A holistic approach has t...
متن کاملA New Method for Multisensor Data Fusion Based on Wavelet Transform in a Chemical Plant
This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...
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ژورنال
عنوان ژورنال: Journal of the Robotics Society of Japan
سال: 1994
ISSN: 0289-1824,1884-7145
DOI: 10.7210/jrsj.12.646