A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position
In this paper, a novel technique is presented for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. In this work, both the sending vehicle and receiving vehicle or human operator are equi...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2015
|
| Online Access: | http://hdl.handle.net/1721.1/97710 https://orcid.org/0000-0003-3422-8700 |
| _version_ | 1826207881834266624 |
|---|---|
| author | Schneider, Toby Schmidt, Henrik |
| author2 | Massachusetts Institute of Technology. Center for Ocean Engineering |
| author_facet | Massachusetts Institute of Technology. Center for Ocean Engineering Schneider, Toby Schmidt, Henrik |
| author_sort | Schneider, Toby |
| collection | MIT |
| description | In this paper, a novel technique is presented for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. In this work, both the sending vehicle and receiving vehicle or human operator are equipped with a shared real-time simulation of the sender's state based on the prior transmitted positions. Thus, only the innovation between the sender's actual state and the shared state need be sent over the link, such as a very low throughput acoustic modem. The distribution of this innovation can be modeled a priori or assembled adaptively. This distribution is then paired with an arithmetic entropy encoder, producing a very low cost representation of the vehicle's position vector. This system was analyzed on experimental data from the GLINT10 and AGAVE07 expeditions involving two different classes of AUVs performing a diverse number of maneuvers, and implemented on a fielded vehicle in the MBAT12 experiment. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-b integer baseline, was achieved. |
| first_indexed | 2024-09-23T13:56:26Z |
| format | Article |
| id | mit-1721.1/97710 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:56:26Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/977102022-09-28T17:14:04Z A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position Schneider, Toby Schmidt, Henrik Massachusetts Institute of Technology. Center for Ocean Engineering Massachusetts Institute of Technology. Department of Mechanical Engineering Schneider, Toby Schmidt, Henrik In this paper, a novel technique is presented for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. In this work, both the sending vehicle and receiving vehicle or human operator are equipped with a shared real-time simulation of the sender's state based on the prior transmitted positions. Thus, only the innovation between the sender's actual state and the shared state need be sent over the link, such as a very low throughput acoustic modem. The distribution of this innovation can be modeled a priori or assembled adaptively. This distribution is then paired with an arithmetic entropy encoder, producing a very low cost representation of the vehicle's position vector. This system was analyzed on experimental data from the GLINT10 and AGAVE07 expeditions involving two different classes of AUVs performing a diverse number of maneuvers, and implemented on a fielded vehicle in the MBAT12 experiment. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-b integer baseline, was achieved. United States. Office of Naval Research (Grant N00014-08-1-0011) United States. Office of Naval Research (Grant N00014-11-1-0097) 2015-07-08T17:44:59Z 2015-07-08T17:44:59Z 2013-10 2013-02 Article http://purl.org/eprint/type/JournalArticle 0364-9059 1558-1691 http://hdl.handle.net/1721.1/97710 Schneider, Toby, and Henrik Schmidt. “A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position.” IEEE J. Oceanic Eng. 38, no. 4 (October 2013): 796–808. https://orcid.org/0000-0003-3422-8700 en_US http://dx.doi.org/10.1109/joe.2013.2268292 IEEE Journal of Oceanic Engineering Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Other repository |
| spellingShingle | Schneider, Toby Schmidt, Henrik A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position |
| title | A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position |
| title_full | A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position |
| title_fullStr | A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position |
| title_full_unstemmed | A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position |
| title_short | A State Observation Technique for Highly Compressed Source Coding of Autonomous Underwater Vehicle Position |
| title_sort | state observation technique for highly compressed source coding of autonomous underwater vehicle position |
| url | http://hdl.handle.net/1721.1/97710 https://orcid.org/0000-0003-3422-8700 |
| work_keys_str_mv | AT schneidertoby astateobservationtechniqueforhighlycompressedsourcecodingofautonomousunderwatervehicleposition AT schmidthenrik astateobservationtechniqueforhighlycompressedsourcecodingofautonomousunderwatervehicleposition AT schneidertoby stateobservationtechniqueforhighlycompressedsourcecodingofautonomousunderwatervehicleposition AT schmidthenrik stateobservationtechniqueforhighlycompressedsourcecodingofautonomousunderwatervehicleposition |