The University of Southampton
University of Southampton Institutional Repository

Improving the mobility performance of autonomous unmanned ground vehicles by adding the ability to ‘sense/feel‘ their local environment

Improving the mobility performance of autonomous unmanned ground vehicles by adding the ability to ‘sense/feel‘ their local environment
Improving the mobility performance of autonomous unmanned ground vehicles by adding the ability to ‘sense/feel‘ their local environment
This paper explores how a ‘learning‘ algorithm can be added to UGV’s by giving it the ability to test the terrain through ‘feeling‘ using incorporated sensors, which would in turn increase its situational awareness. Once the conditions are measured the system will log the results and a database can be built up of terrain types and their properties (terrain classification), therefore when it comes to operating autonomously in an unknown, unpredictable environment, the vehicle will be able to cope by identifying the terrain and situation and then decide on the best and most efficient way to travel over it by making adjustments, which would greatly improve the vehicles ability to operate autonomously
unmanned, autonomous, mobility, situational awareness, way finding, terrain, reconfigurable, intelligent wheels
0302-9743
514-522
Odedra, Siddharth
3ebba4cd-6118-4330-a2c8-01cb780f8632
Prior, Stephen D.
9c753e49-092a-4dc5-b4cd-6d5ff77e9ced
Karamanoglu, Mehmet
635b350e-7c35-468b-b990-ef59089a1382
Odedra, Siddharth
3ebba4cd-6118-4330-a2c8-01cb780f8632
Prior, Stephen D.
9c753e49-092a-4dc5-b4cd-6d5ff77e9ced
Karamanoglu, Mehmet
635b350e-7c35-468b-b990-ef59089a1382

Odedra, Siddharth, Prior, Stephen D. and Karamanoglu, Mehmet (2007) Improving the mobility performance of autonomous unmanned ground vehicles by adding the ability to ‘sense/feel‘ their local environment. Lecture Notes in Computer Science, 4563, 514-522. (doi:10.1007/978-3-540-73335-5_56).

Record type: Article

Abstract

This paper explores how a ‘learning‘ algorithm can be added to UGV’s by giving it the ability to test the terrain through ‘feeling‘ using incorporated sensors, which would in turn increase its situational awareness. Once the conditions are measured the system will log the results and a database can be built up of terrain types and their properties (terrain classification), therefore when it comes to operating autonomously in an unknown, unpredictable environment, the vehicle will be able to cope by identifying the terrain and situation and then decide on the best and most efficient way to travel over it by making adjustments, which would greatly improve the vehicles ability to operate autonomously

Text
Prior_2007-improving_the_mobility_performance.pdf - Other
Download (1MB)

More information

Published date: 2007
Keywords: unmanned, autonomous, mobility, situational awareness, way finding, terrain, reconfigurable, intelligent wheels
Organisations: Aeronautics, Astronautics & Comp. Eng

Identifiers

Local EPrints ID: 343803
URI: http://eprints.soton.ac.uk/id/eprint/343803
ISSN: 0302-9743
PURE UUID: 54f19a0a-0aeb-4f00-bb37-562d4aabb0ce
ORCID for Stephen D. Prior: ORCID iD orcid.org/0000-0002-4993-4942

Catalogue record

Date deposited: 10 Oct 2012 10:30
Last modified: 15 Mar 2024 03:45

Export record

Altmetrics

Contributors

Author: Siddharth Odedra
Author: Mehmet Karamanoglu

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×