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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Goldfarb, Nathaniel Wang, Jinkun Bai, Shi Englot, Brendan |
| Copyright Year | 2015 |
| Description | Author affiliation: Department of Mechanical Engineering, Stevens Institute of Technology, Castle Point on Hudson, Hoboken NJ 07030 USA (Goldfarb, Nathaniel; Wang, Jinkun; Bai, Shi; Englot, Brendan) |
| Abstract | We propose a portfolio of filtering methods for a remotely-operated vehicle (ROV) that relies on a compass, gyro, depth sensor and ultra-short baseline (USBL) positioning system for localization in shallow-water environments. Our goal is to maintain an accurate state estimate that will be suitable as a basis for decision-making in the course of carrying out an autonomous underwater inspection. We employ Kalman filters in conjunction with an outlier filter to produce a reliable estimate in the presence of noisy and spurious data. Our localization result is then used as a basis for 3D occupancy mapping, in which further filtering and inference techniques are applied to remove false returns from the ROV's scanning sonar. Localization results from two field deployments of the ROV are given. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 6971362 |
| Page Count | 7 |
| File Format | |
| ISBN | 9780933957435 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-19 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | MTS |
| Subject Keyword | Robot sensing systems Kalman filters Sonar Three-dimensional displays Position measurement Inspection |
| Content Type | Text |
| Resource Type | Article |
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