This communication addresses the issue of concurrent map building and localization (CML) for a mobile robot in an unknown environment. The proposed solution extends over previous contributions in that the environment must not be static, nor the landmarks be uniquely identifiable. To this aim we introduce a map model that includes not only the robot and landmark locations in a reference frame, b...

For the mobile robot Simultaneous Localization and Mapping (SLAM),a new algorithm is proposed, and named Adaptive Iterated Square-Root Cubature Kalman Filter based SLAM algorithm (AISRCKF-SLAM). The main contribution of the algorithm is that the numerical integration method based on cubature rule is directly used to calculate the SLAM posterior probability density. To improve innovation covaria...

A method is provided for determining necessary conditions on sample size or signal to noise ratio (SNR) to obtain accurate parameter estimates from remote sensing measurements in fluctuating environments. These conditions are derived by expanding the bias and covariance of maximum likelihood estimates (MLEs) in inverse orders of sample size or SNR, where the first-order covariance term is the C...

Abstract. Integrating the hybrid and multiscale analyses parallel computation is necessary for current data assimilation schemes. A local method, Local DA, designed to fulfill these needs. This algorithm follows grid-independent framework of ensemble transform Kalman filter (LETKF) more flexible in analysis than LETKF. DA employs an explicitly computed background error correlation matrix model ...

wireless sensor networks attracting a great deal of research interest. accurate localization of sensor nodes is a strong requirement in a wide area of applications. in recent years, several techniques have been proposed for localization in wireless sensor networks. in this paper we present a localization scheme with using only one mobile anchor station and received signal strength indicator tec...

In classical mechanics, Galilean covariance and the principle of relativity are completely equivalent and hold for all possible dynamical processes. In contrast, in relativistic physics the situation is much more complex. It will be shown that Lorentz covariance and the principle of relativity are not completely equivalent. The reason is that the principle of relativity actually only holds for ...

This paper introduces a “weighted” matching algorithm to estimate a robot’s planar displacement by matching dense twodimensional range scans. Based on models of expected sensor uncertainty, our algorithm weights the contribution of each scan point to the overall matching error according to its uncertainty. A general maximum likelihood formulation is used to optimally estimate the displacement b...

In subspace-based method for direction-of-arrival (DOA) estimation of signal wavefronts, the additive noise term is often assumed to be spatially white or known to within a multiplicative scalar. When the noise is nonwhite but has a known covariance matrix, we can still handle the problem through prewhitening. However, the problem turns to be complex when the noise field is completely unknown. ...

This paper introduces a new algorithm to estimate a robot’s planar displacement by weighted matching of dense twodimensional range scans. Based on models of expected sensor uncertainty, our algorithm weights the contribution of each scan point to the overall matching error according to its uncertainty. A general maximum likelihood formulation is used to optimally estimate the displacement betwe...

We study the ability of a sensor array to blindly separate and localize broadband traveling waves impinging on the array, with additive sensor noise. We consider arrays smaller than the shortest wavelength in the sources, such as MEMS acoustic arrays or VLSI arrays of RF receivers. A series expansion about the center of the array of the time-delayed signals emanating from the sources reduces th...