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Multirobot Tethering for Localization and Control

Baillio, Brad and Vladimerou, Vladimeros LU (2009) Fourth Swedish Workshop on Autonomous Robotics SWAR'09
Abstract
We investigate the use of particle filter (PF) estimation techniques on a hovercraft vehicle in an office environment. Monte Carlo Localization (MCL) with particle filtering is a popular method for localizing robots with laser range finders. In maps featuring long, uniform corridors though, a PF can produce low confidence estimates. When used as feedback to control an unstable vehicle this can prove fatal. This is because, unlike grounded wheeled vehicles, an airborne hovercraft requires accurate localization

not only for path planning, but for stabilization as well. We solve the low confidence problem using a secondary networked robot as a mobile map feature.
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Contribution to conference
publication status
published
subject
keywords
localization, particle filter, hovercraft, networked autonomous vehicles, laser range finder
conference name
Fourth Swedish Workshop on Autonomous Robotics SWAR'09
conference location
Västerås, Sweden
conference dates
2009-09-01
language
English
LU publication?
yes
id
56eeea94-5e88-4d3c-8e40-d0c0f9cc3733 (old id 1627502)
date added to LUP
2016-04-04 13:46:51
date last changed
2018-11-21 21:16:15
@misc{56eeea94-5e88-4d3c-8e40-d0c0f9cc3733,
  abstract     = {{We investigate the use of particle filter (PF) estimation techniques on a hovercraft vehicle in an office environment. Monte Carlo Localization (MCL) with particle filtering is a popular method for localizing robots with laser range finders. In maps featuring long, uniform corridors though, a PF can produce low confidence estimates. When used as feedback to control an unstable vehicle this can prove fatal. This is because, unlike grounded wheeled vehicles, an airborne hovercraft requires accurate localization<br/><br>
not only for path planning, but for stabilization as well. We solve the low confidence problem using a secondary networked robot as a mobile map feature.}},
  author       = {{Baillio, Brad and Vladimerou, Vladimeros}},
  keywords     = {{localization; particle filter; hovercraft; networked autonomous vehicles; laser range finder}},
  language     = {{eng}},
  title        = {{Multirobot Tethering for Localization and Control}},
  url          = {{https://lup.lub.lu.se/search/files/6203345/8146107.pdf}},
  year         = {{2009}},
}