In this paper, we describe a Continuously Adaptive Mean Shift (CAMshift) algorithm with a Kalman filter. A CAMshift algorithm does not consider an object’s direction vectors and velocity. In addition, sometimes, CAMshift loses the tracked object when the color of the background is similar to that of the object. However, using a Kalman filter with the CAMshift algorithm can overcome these disadv...

This paper proposes an adaptive two-stage extended Kalman filter (ATEKF) for estimation of unknown fault bias in an INS-GPS loosely coupled system. The Kalman filtering technique requires complete specifications of both dynamical and statistical model parameters of the system. However, in a number of practical situations, these models may contain parameters, which may deviate from their nominal...

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. ...

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...

The present work proposes a control parameter adjustment technique using Kalman filter applied to an adaptive control strategy. The control algorithm is based on neural networks with on-line learning to compute the next action of the manipulated process variables. The penalization parameters of the control actions are on-line optimised by the Kalman filter. The control strategy was tested on an...

Skid‐steered mobile robots have been widely used in exploring unknown environments and in military applications. In this paper, the tuning fuzzy Vector Field Orientation (FVFO) feedback control method is proposed for a four track wheel skid‐steered mobile robot (4‐TW SSMR) using flexible fuzzy logic control (FLC). The extended Kalman filter is utilized to e...

This paper elaborates how the time update of the continuous-discrete extended Kalman-Filter (EKF) can be computed in the most efficient way. The specific structure of the EKF-moment differential equations leads to a new Taylor-Heun-approximation of the nonlinear vector field. Furthermore, the order of consistency and stability behavior of the outlined procedure is investigated. The results are ...

Road sign detection and tracking is one of the major tasks in a visual driver-assistance system. This paper describes an approach to detecting and tracking road signs appearing in complex traffic scenes. In the detecting phase, two neural networks are developed to extract color and shape features of traffic signs, respectively, from scenes images. A process characterized by fuzzy-set discipline...