An intelligent environment employing multiple vision sensors labeled with identification features is proposed. The union of the sensing ranges of these vision sensors covers a large unknown workspace where a mobile robot can proceed to explore. The goal of this research is to accomplish mobile robot localization and navigation based on such a calibration-free sensor network. Specifically, stati...

Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not provide the expected per...

Measurements in the macro-tidal Daly Estuary show that the presence of an undular tidal bore contributed negligibly to the dissipation of tidal energy. No recirculation bubble was observed between a trough and the following wave crest in the lee waves following the undular bore. This differs to stationary undular bores in laboratory experiments at larger Froude numbers where a recirculation bub...

This paper discusses multi robot localization (MRL) assisted by teammate robots and dynamic objects. We specifically relate our research to the robot soccer environment. We basically use a particle filter based localization scheme and further improve its accuracy by using information from teammate robots regarding their relative position and the relative position of dynamic objects in the envir...

We consider continuous-time Markov chains representing queueing systems in random environment and we obtain necessary and sufficient conditions for having product-form stationary distributions. The related topics of partial balance and the ESTA property are also studied. As an illustration, we apply the results to study the stationary distributions of Jackson networks in random environment. For...

in this paper we focus on the tracking performance of incremental adaptive LMS algorithm in an adaptive network. For this reason we consider the unknown weight vector to be a time varying sequence. First we analyze the performance of network in tracking a time varying weight vector and then we explain the estimation of Rayleigh fading channel through a random walk model. Closed form relations a...

Adaptive control is challenging in real-world applications such as robotics. Learning has to be rapid enough to be performed in real time and to avoid damage to the robot. Models using linear function approximation are interesting in such tasks because they offer rapid learning and have small memory and processing requirements. This makes them suitable as adaptive controllers in nonstationary e...

We study the stationary solution to the recursion Xn+1 = γXn+ξn, where γ ∈ (0, 1) is a constant and ξn are Gaussian variables with random parameters. Specifically, we assume that ξn = μn + σnεn, where (ε)n∈Z is an i.i.d. sequence of standard normal variables and (μn, σn)n∈Z is a stationary and ergodic process independent of (εn)n∈Z, which serves as an exogenous dynamic environment for the model...

A random walk on a lattice is one of the most fundamental models in probability theory. When the random walk is inhomogenous and its inhomogeniety comes from an ergodic stationary process, the walk is called a random walk in a random environment (RWRE). The basic questions such as the law of large numbers (LLN), the central limit theorem (CLT), and the large deviation principle (LDP) are ...

Let ? act on a countable set V with only nitely many orbits. Given a ?-invariant random environment for a Markov chain on V and a random scenery, we exhibit, under certain conditions, an equivalent stationary measure for the environment and scenery from the viewpoint of the random walker. Such theorems have been very useful in investigations of percolation on quasi-transitive graphs.