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Mobile Robot Positioning - Sensors and Techniques

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TLDR
This paper provides a review of relevant mobile robot positioning technologies and defines seven categories for positioning systems: Odometry, Inertial Navigation, Magnetic Compasses, Active Beacons, Global Positioning Systems, Landmark Navigation, and Model Matching.
Abstract
: Exact knowledge of the position of a vehicle is a fundamental problem in mobile robot applications. In the search for a solution, researchers and engineers have developed a variety of systems, sensors, and techniques for mobile robot positioning. This paper provides a review of relevant mobile robot positioning technologies. The paper defines seven categories for positioning systems: (1) Odometry, (2) Inertial Navigation, (3) Magnetic Compasses, (4) Active Beacons, (5) Global Positioning Systems, (6) Landmark Navigation, and (7) Model Matching. The characteristics of each category are discussed and examples of existing technologies are given for each category. The field of mobile robot navigation is active and vibrant, with more great systems and ideas being developed continuously. For this reason the examples presented in this paper serve only to represent their respective categories; they do not represent a judgment by the authors. Many ingenious approaches can be found in the literature, although, for reasons of brevity, not all could be cited in this paper. The appendix contains a tabular comparison of the positioning systems discussed in this review that includes system and description, features, accuracy (position), accuracy (orientation), effective range, and source of information. (47 refs.)

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Research Advance in Swarm Robotics

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References
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Book

An introduction to the mathematics and methods of astrodynamics

TL;DR: The Problem of Two Bodies and the Initial-Value Problem Solving Kepler's Equation Two-Body Orbital Boundary Value Problem solving Lambert's Problem Appendices Part 2 Non-Keplerian Motion: Patched-Conic Orbits and Perturbation Methods Variation of Parameters Two Body Orbital Transfer Numerical Integration of Differential Equations.
Journal ArticleDOI

Measurement and correction of systematic odometry errors in mobile robots

TL;DR: Experimental results are presented that show a consistent improvement of at least one order of magnitude in odometric accuracy (with respect to systematic errors) for a mobile robot calibrated with the method described.
Journal ArticleDOI

Inertial navigation systems for mobile robots

TL;DR: A low-cost solid-state inertial navigation system for mobile robotics applications is described and error models for the inertial sensors are generated and included in an extended Kalman filter for estimating the position and orientation of a moving robot vehicle.
Book

Navigating Mobile Robots: Systems and Techniques

TL;DR: This is a survey of the state-of-the-art in sensors, systems, methods and technologies utilized by a mobile robot to determine its position in the environment.
Proceedings ArticleDOI

Position estimation for a mobile robot using vision and odometry

TL;DR: A method for locating a mobile robot moving in a known environment that combines position estimation from odometry with observations of the environment from a mobile camera is described.