Validation of Underwater Sensor Package Using Feature Based SLAM
Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, unde...
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doaj-2ecc391d4ff14108b57515622dceac152020-11-25T00:46:31ZengMDPI AGSensors1424-82202016-03-0116338010.3390/s16030380s16030380Validation of Underwater Sensor Package Using Feature Based SLAMChristopher Cain0Alexander Leonessa1SEW-EURODRIVE, Lyman, SC 29365, USADepartment of Mechanical Engineering, Center for Dynamic Systems Modeling and Control, Virginia Tech, Blacksburg, VA 24061, USARobotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package.http://www.mdpi.com/1424-8220/16/3/380underwater range finderEKF SLAMFastSLAMSLAMvision range findervision odometry |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Christopher Cain Alexander Leonessa |
spellingShingle |
Christopher Cain Alexander Leonessa Validation of Underwater Sensor Package Using Feature Based SLAM Sensors underwater range finder EKF SLAM FastSLAM SLAM vision range finder vision odometry |
author_facet |
Christopher Cain Alexander Leonessa |
author_sort |
Christopher Cain |
title |
Validation of Underwater Sensor Package Using Feature Based SLAM |
title_short |
Validation of Underwater Sensor Package Using Feature Based SLAM |
title_full |
Validation of Underwater Sensor Package Using Feature Based SLAM |
title_fullStr |
Validation of Underwater Sensor Package Using Feature Based SLAM |
title_full_unstemmed |
Validation of Underwater Sensor Package Using Feature Based SLAM |
title_sort |
validation of underwater sensor package using feature based slam |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2016-03-01 |
description |
Robotic vehicles working in new, unexplored environments must be able to locate themselves in the environment while constructing a picture of the objects in the environment that could act as obstacles that would prevent the vehicles from completing their desired tasks. In enclosed environments, underwater range sensors based off of acoustics suffer performance issues due to reflections. Additionally, their relatively high cost make them less than ideal for usage on low cost vehicles designed to be used underwater. In this paper we propose a sensor package composed of a downward facing camera, which is used to perform feature tracking based visual odometry, and a custom vision-based two dimensional rangefinder that can be used on low cost underwater unmanned vehicles. In order to examine the performance of this sensor package in a SLAM framework, experimental tests are performed using an unmanned ground vehicle and two feature based SLAM algorithms, the extended Kalman filter based approach and the Rao-Blackwellized, particle filter based approach, to validate the sensor package. |
topic |
underwater range finder EKF SLAM FastSLAM SLAM vision range finder vision odometry |
url |
http://www.mdpi.com/1424-8220/16/3/380 |
work_keys_str_mv |
AT christophercain validationofunderwatersensorpackageusingfeaturebasedslam AT alexanderleonessa validationofunderwatersensorpackageusingfeaturebasedslam |
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1725264845367934976 |