Multirobot Tethering for Localization and Control
(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:
https://lup.lub.lu.se/record/1627502
- author
- Baillio, Brad and Vladimerou, Vladimeros LU
- organization
- publishing date
- 2009
- 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}}, }