Global Urban Localization of an Outdoor Mobile Robot with Genetic Algorithms

Abstract

Summary. The localization of mobile robots has been studied rigorously in the past. However, only a few studies have focused on developing specific Genetic Algorithms (GAs) to address the localization problem effectively. In this study; the global urban localization of an outdoor mobile platform is considered with the utilization of the odometer, the laser-rangeq finder measurements and the digital maps created from the relevant satellite images on the Internet. The localization issue is formulated as a constrained optimization problem. The study proposes a GA-based technique to solve the problem at hand efficiently.

C-LOG: A Chamfer Distance based method for localisation in occupancy grid-maps

“…In [17] a genetic optimisation algorithm (GA) is used to localise a mobile robot on a geometric beacon based a-priori map. This algorithm was also used in [18] for localising on a satellite image geo-map of an outdoor environment using a laser range finder sensor. Another example of the use of evolutionary computing for feature based localisation is [19].…”

Outdoor mapping and localization using satellite images

“…Following this approach, the SLAM problem is avoided and localization is performed in mutually independent steps; first the map of the region of interest is obtained by making use of satellite images, second localization is achieved by using the maps obtained from these images. The scenario of the operating conditions of the mobile robot can be summarized with the Global Urban Localization (GUL) problem: 16 "A robot with a Wi-Fi enabled device (such as a laptop, a PDA or a cell phone) wakes up in an unfamiliar urban setting. In the mobile robot's foremost task is to determine its location.…”