Parameter estimation is considered to be one of the greatest challenges in computational systems biology. Biological experiments can measure only a fraction of the kinetic parameters and the rest has to be estimated in silico. Recently parameter estimation problems have been addressed in the framework of control theory. One of the most successful and widely used methods in control theory for es...

In this paper, we present the practical application of an Unscented Kalman Filter (UKF) for an Indoor Mobile Localization System using ultrasonic sensors. It is true that many kinds of localization techniques have been researched for several years in order to contribute to the realization of a ubiquitous system; particularly, such a ubiquitous system needs a high degree of accuracy to be practi...

NI-13. RESOLVING THE CHALLENGES OF PERITUMORAL EDEMA IN TRACING ARCUATE FASCICULUS FOR SURGICAL PLANNING USING TWO-TENSOR UNSCENTED KALMAN FILTER TRACTOGRAPHY Zhenrui Chen1,4, Yanmei Tie1, Lauren O’Donnell1,2, Laura Rigolo1, Alireza Mehrtash1,2, Olutayo Olubiyi1, Isaiah Norton1, Ofer Pasternak3, Yogesh Rathi3, and Alexandra Golby1,2; Department of Neurosurgery, Brigham and Women’s Hospital, Har...

We study the effect of anisotropic noise on target registration error (TRE) by using a tracked and calibrated stylus tip as the fiducial registration application. We present a simple, efficient unscented Kalman filter algorithm that is suitable for fiducial registration even with a small number of fiducials. We also derive an equation that predicts TRE under anisotropic noise. The predicted TRE...

A description of a Solid Oxide Fuel Cell (SOFC) combined Gas Turbine (GT) hybrid system is given. Modeling of all the components of the hybrid system is briefly presented. A decentralized control structure using PI controllers is designed and is considered as a part of the system. An Unscented Kalman Filter (UKF) is applied to estimate the state vector and the simulation results are presented. ...

For parameter estimations, we have developed a extended kalman filter(EKF) and unscented kalman filter(UKF) for linear as well as non-linear spacecraft systems. We have described the differences of two approaches mathematical equation for modeling of the system value of mean square error, error covariance and For state estimation of satellite, two different type of filters has been described i....

This paper presents an online sensor fusion algorithm for state estimation of a remotely operated underwater vehicle for aquaculture inspection. The algorithm is based on an Unscented Kalman Filer (UKF) and uses information from several sources including an onboard inertial sensor, an onboard camera combined with line lasers and a priory knowledge about the aquaculture geometry. The performance...

In-motion alignment of a SDINS/GPS integrated system, determining the angular relationship between the navigation frame and the body frame is a necessary process. This paper describes the in-motion alignment procedure for a low-cost GPS/INS integrated system using the Unscented Kalman Filter (UKF) and Central Difference Kalman Filter (CDKF). The UKF and CDKF are used to implement the in-motion ...

SLAM (Simultaneous Localization and Mapping) is a fundamental problem when an autonomous mobile robot explores an unknown environment by constructing/updating the environment map and localizing itself in this built map. The all-important problem of SLAM is revisited in this paper and a solution based on Adaptive Unscented Kalman Filter (AUKF) is presented. We will explain the detailed algorithm...

Outdoor positioning for Unmanned Aerial Vehicles (UAVs) commonly relies on GPS signals, which might be reflected or blocked in urban areas. In such cases, additional on-board sensors such as Light Detection and Ranging (LiDAR) are desirable. To fuse GPS and LiDAR measurements, it is important, yet challenging, to accurately characterize the error covariance of the sensor measurements. In this p...