The aim of this paper is to investigate the methods of maintaining desired flow conditions in the reaches of the ecologically valuable upper reaches of the River Narew taking into account the uncertainty in modelling process. The study is based on Global Sensitivity Analysis (GSA) and Generalised Likelihood Uncertainty Estimation (GLUE) techniques applied to a 1-D river flow model. We compare s...

This paper analyses the properties of the full covariance simultaneous map building problem (SLAM). We prove that, for the special case of a stationary vehicle (with no process noise) which uses a range-bearing sensor and has non-zero angular uncertainty, the fullcovariance SLAM algorithm always yields an inconsistent map. We also show, through simulations, that these conclusions appear to exte...

A design of mobile robot for robust lifelong navigation in oce environment is proposed and evaluated. The key idea is combining probabilistic map and dialog with humans for reducing the location uncertainty. Bayesian inference with the map represented by proba-bilistic automata is used in order to reduce the number of queries and to evaluate the success rate of planned paths. We experimentally ...

This paper analyses the properties of the full covariance simultaneous map building problem (SLAM). We prove that, for the special case of a stationary vehicle (with no process noise) which uses a range-bearing sensor and has non-zero angular uncertainty, the fullcovariance SLAM algorithm always yields an inconsistent map. We also show, through simulations, that these conclusions appear to exte...

Mapping geochemical anomaly is essential for prospecting. Kriging is often used to characterize the spatial variability of geochemistry. However, due to its smooth effects, it is incapable of detecting multi-location uncertainty of geochemistry estimate. Sequential gaussian simulation (SGS) can model the spatial uncertainty through generation of several equally probable stochastic realizations....

Our mobile robot system uses scale-invariant visual landmarks to localize itself and build a 3D map of the environment simultaneously. As image features are not noise-free, we carry out error analysis and use Kalman Filters to track the 3D landmarks, resulting in a database map with landmark positional uncertainty. By matching a set of landmarks as a whole, our robot can localize itself globall...

This paper analyzes the consistency of the classical extended Kalman filter (EKF) solution to the simultaneous localization and map building (SLAM) problem. Our results show that in large environments the map quickly becomes inconsistent due to linearization errors. We propose a new EKF-based SLAM algorithm, robocentric mapping, that greatly reduces linearization errors, improving map consisten...