A radial basis function (RBF) neural network approach with a fusion of multiple signal candidates in precision motion control is studied in this paper. Sensor weightages are assigned to sensor measurements according to the selector attributes and are approximated using RBF neural network in multi-sensor fusion. A specific application towards precision motion control of a linear motor system usi...

An improvement method for the pose accuracy of a robot manipulator by using a multiple-sensor combination measuring system (MCMS) is presented. It is composed of a visual sensor, an angle sensor and a series robot. The visual sensor is utilized to measure the position of the manipulator in real time, and the angle sensor is rigidly attached to the manipulator to obtain its orientation. Due to t...

Motivated by the resource management problem in nonlinear multi-sensor tracking networks, the paper derives online, distributed estimation algorithms for computing the posterior Cramér-Rao lower bound (PCRLB) for full-order and reduced-order distributed Bayesian estimators without requiring a fusion centre and with nodal communications limited to local neighborhoods. For both cases, Riccati-typ...

In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods...

Multi-modal data fusion has gained popularity due to its diverse applications, leading an increased demand for external sensor calibration. Despite several proven calibration solutions, they fail fully satisfy all the evaluation criteria, including accuracy, automation, and robustness. Thus, this review aims contribute growing field by examining recent research on multi-modal imaging proposing ...

In real applications, how to measure the uncertain degree of sensor reports before applying sensor data fusion is a big challenge. In this paper, in the frame of Dempster-Shafer evidence theory, a weighted belief entropy based on Deng entropy is proposed to quantify the uncertainty of uncertain information. The weight of the proposed belief entropy is based on the relative scale of a propositio...

The principle of target tracking and data fusion techniques are discussed. To resolve high uncertainty that exists in sensors of mobile robots, one multi-sensor data fusion algorithm is presented. The algorithm is based on particle filter techniques, fuses the information coming from multiple sensors and merges different state space models. So it can be used to eliminate system and measurement ...

In order to solve effectively the issue of remote online detection and fault diagnosis of hydroelectric generating units in FengMan hydropower plant, a kind integrated project of combining embedded network fusion with multi-sensor consistency information fusion algorithm and fuzzy comprehensive assessment algorithm is proposed based on distributed and embedded architecture. Multi-sensor consist...

Multi-sensor management concerns the control of environment perception activities by managing or coordinating the usage of multiple sensor resources. It is an emerging research area, which has become increasingly important in research and development of modern multi-sensor systems. This paper presents a comprehensive review of multi-sensor management in relation to multi-sensor information fusi...