Localization forms the heart of various autonomous mobile robots. For efficient navigation,
these robots need to adopt effective localization strategy. This paper, presents a …

For more than two decades, the issue of simultaneous localization and mapping (SLAM) has
gained more attention from researchers and remains an influential topic in robotics …

Localization is the problem of determining the position of a mobile robot from sensor data.
Most existing localization approaches are passive, ie, they do not exploit the opportunity to …

Accurate and robust localization is essential for the successful navigation of autonomous
mobile robots. The majority of existing localization approaches, however, is based on the …

A robot navigating in an unstructured outdoor environment must determine its own location
in spite of problems due to environmental conditions, sensor limitations and map …

Intelligent unmanned systems have important applications, such as pesticide-spraying in
agriculture, robot-based warehouse management systems, and missile-firing drones. The …

To operate successfully in indoor environments, mobile robots must be able to localize
themselves. Most current localization algorithms lack flexibility, autonomy, and often …

For robot swarm applications, accurate positioning is one of the most important requirements
for avoiding collisions and keeping formations and cooperation between individuals …

As mobile robots become more common in general knowledge and practices, as opposed to
simply in research labs, there is an increased need for the introduction and methods to …

This paper presents a novel method of integrating fuzzy logic (FL) and genetic algorithm
(GA) to solve the simultaneous localization and mapping (SLAM) problem of mobile robots …