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Clustering Latent Sensor Distribution on Body Map for Generating Body Schema Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Localization Issues for an Autonomous Robot Moving in a Potentially Adverse Environment

Authors : Antonio D’Angelo, Dante Degl’Innocenti

Published in: Intelligent Autonomous Systems 14

Publisher: Springer International Publishing

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Abstract

The aim of this paper is to face with the problem of localizing a robot during the navigation in a partially unknown environment. This feature becomes particularly noteworthy especially in the case of a colony of robots, possibly working with humans, inside a scenario where motion issues are crucial. Within this context the focus on self-localization through GPS and INS/SINS integration overtakes merely questions about algorithm efficiency because self-localization is a relevant part of the task. Thus, unlike other approaches, we have focalised on this behavior as an attitude an autonomous system should enhance during the task execution. The tight coupling of GPS and INS sensors is understood as a mechanism which provides the autonomous robot with a refinement of INS use by comparing and/or adjusting the INS performance by exploiting the GPS-INS integration.

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previous chapter A Simple and Efficient Path Following Algorithm for Wheeled Mobile Robots
next chapter Vector-AMCL: Vector Based Adaptive Monte Carlo Localization for Indoor Maps
Footnotes
1
Strapdown Inertial Navigation System.
 
2
Micro- electro-mechanical systems.
 
3
Unscented Kalman filter.
 
4
Military applications, rescue, hazardous environments such as demining places, pivotal constraints of various nature, and so on.
 
5
Diluition of Precision.
 
6
5 m in our case.
 
7
Lost due to lack of GPS signal.
 
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Metadata
Title
Localization Issues for an Autonomous Robot Moving in a Potentially Adverse Environment
Authors
Antonio D’Angelo
Dante Degl’Innocenti
Copyright Year
2017
Book
Intelligent Autonomous Systems 14

Print ISBN: 978-3-319-48035-0

Electronic ISBN: 978-3-319-48036-7

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-48036-7_28

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