Surveys the developments of the last 20 years in the area of vision for mobile robot
navigation. Two major components of the paper deal with indoor navigation and outdoor …

Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot
applications. In search of a solution, researchers and engineers have developed a variety of …

Semantic navigation is necessary to deploy mobile robots in uncontrolled environments
such as homes or hospitals. Many learning-based approaches have been proposed in …

Matching 2D range scans is a basic component of many localization and mapping
algorithms. Most scan match algorithms require finding correspondences between the used …

Mobile robot localization is the problem of determining a robot's pose from sensor data. This
article presents a family of probabilistic localization algorithms known as Monte Carlo …

A robot exploring an unknown environment may need to build a worldmodel from sensor
measurements. In order to integrate all the framesof sensor data, it is essential to align the …

This paper presents a new algorithm for mobile robot localization, called Monte Carlo
Localization (MCL). MCL is a version of Markov localization, a family of probabilistic …

This article describes the software architecture of an autonomous, interactive tour-guide
robot. It presents a modular and distributed software architecture, which integrates …

Autonomous robots must be able to learn and maintain models of their environments.
Research on mobile robot navigation has produced two major paradigms for mapping …

Now in its third edition, this textbook is a comprehensive introduction to the multidisciplinary
field of mobile robotics, which lies at the intersection of artificial intelligence, computational …