In this article, a fast and reliable map-merging algorithm is proposed to produce a global two dimensional map of an indoor environment in a multi-robot simultaneous localization and mapping (SLAM) process. In SLAM process, to find its way in this environment, a robot should be able to determine its position relative to a map formed from its observations. To solve this complex problem, simultan...

In this paper we present parallel implementation of genetic algorithm using map/reduce programming paradigm. Hadoop implementation of map/reduce library is used for this purpose. We compare our implementation with implementation presented in [1]. These two implementations are compared in solving One Max (Bit counting) problem. The comparison criteria between implementations are fitness converge...

at first, ground-based circular strip-map synthetic aperture radar (gb-csmsar) and its capabilities is introduced and the received signal model, 2-d frequency spectrum and the azimuth and range resolutions are derived and compared with the linear motion strip-map sar resolutions. because of the stability of the path and speed of antenna in gb-csmsar a frequency domain imaging algorithm is sugge...

We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that allows for incremental training with an automated adaptation of lattice size to achieve a prescribed quantization error and (ii) an approximate best match search that utilizes the special structure of the hyperbolic latti...

Within local areas, buses plays an important role, therefore the bus network design is important. Bus network design problem consists of the bus stop number decision problem and the bus stop location decision problem. In this paper, the bus stop number decision problem is determined based on map information. The bus stop location decision problem is determined by a genetic algorithm. Genetic al...

We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that allows for incremental training with an automated adaptation of lattice size to achieve a prescribed quantization error and (ii) an approximate best match search that utilizes the special structure of the hyperbolic latti...