Historical data is useful for navigation planning : data driven route generation for autonomous ship
This work presents a method for automated generation of navigation plan for autonomous or robotic surface vessel. Historical Automatic Identification System (AIS) data is of significant value to this problem. The method joins AIS locations of a same vessel at different time and locations in a region...
| Main Authors: | , , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2021
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/147158 |
| _version_ | 1826114008242978816 |
|---|---|
| author | Tan, Wei Chian Weng, Ching-Yen Zhou, Yu Chua, Kie Hian Chen, I-Ming |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Tan, Wei Chian Weng, Ching-Yen Zhou, Yu Chua, Kie Hian Chen, I-Ming |
| author_sort | Tan, Wei Chian |
| collection | NTU |
| description | This work presents a method for automated generation of navigation plan for autonomous or robotic surface vessel. Historical Automatic Identification System (AIS) data is of significant value to this problem. The method joins AIS locations of a same vessel at different time and locations in a region into a route. Next, it automatically computes navigation plans using nearest neighbour based path retrieval relying on two representations, Ship Feature and Navigation Feature. Before starting service, existing AIS records in the form of ship properties and corresponding route are preprocessed and stored in the form of Ship and Navigation Feature. During online retrieval, given input constraints in vector form, nearest neighbour of this query vector in the same space is found and corresponding path of the neighbour is returned as recommended path. Analysis was done in four and two dimensional spaces for Ship and Navigation Feature respectively. Application of the method is demonstrated in two regions of Australian, covering Bass Strait and Great Australian Bight. |
| first_indexed | 2024-10-01T03:32:11Z |
| format | Conference Paper |
| id | ntu-10356/147158 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:32:11Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1471582021-03-24T04:22:49Z Historical data is useful for navigation planning : data driven route generation for autonomous ship Tan, Wei Chian Weng, Ching-Yen Zhou, Yu Chua, Kie Hian Chen, I-Ming School of Mechanical and Aerospace Engineering 2018 IEEE International Conference on Robotics and Automation (ICRA) Engineering::Mechanical engineering Marine Vehicles Navigation This work presents a method for automated generation of navigation plan for autonomous or robotic surface vessel. Historical Automatic Identification System (AIS) data is of significant value to this problem. The method joins AIS locations of a same vessel at different time and locations in a region into a route. Next, it automatically computes navigation plans using nearest neighbour based path retrieval relying on two representations, Ship Feature and Navigation Feature. Before starting service, existing AIS records in the form of ship properties and corresponding route are preprocessed and stored in the form of Ship and Navigation Feature. During online retrieval, given input constraints in vector form, nearest neighbour of this query vector in the same space is found and corresponding path of the neighbour is returned as recommended path. Analysis was done in four and two dimensional spaces for Ship and Navigation Feature respectively. Application of the method is demonstrated in two regions of Australian, covering Bass Strait and Great Australian Bight. Economic Development Board (EDB) Nanyang Technological University This project was carried out under funding from Economic Development Board of Singapore, Lloyd’s Register and Nanyang Technological University through Industrial Postgraduate Programme 2021-03-24T04:22:49Z 2021-03-24T04:22:49Z 2018 Conference Paper Tan, W. C., Weng, C., Zhou, Y., Chua, K. H. & Chen, I. (2018). Historical data is useful for navigation planning : data driven route generation for autonomous ship. 2018 IEEE International Conference on Robotics and Automation (ICRA), 7478-7483. https://dx.doi.org/10.1109/ICRA.2018.8460880 9781538630815 https://hdl.handle.net/10356/147158 10.1109/ICRA.2018.8460880 2-s2.0-85063123253 7478 7483 en © 2018 IEEE. All rights reserved. |
| spellingShingle | Engineering::Mechanical engineering Marine Vehicles Navigation Tan, Wei Chian Weng, Ching-Yen Zhou, Yu Chua, Kie Hian Chen, I-Ming Historical data is useful for navigation planning : data driven route generation for autonomous ship |
| title | Historical data is useful for navigation planning : data driven route generation for autonomous ship |
| title_full | Historical data is useful for navigation planning : data driven route generation for autonomous ship |
| title_fullStr | Historical data is useful for navigation planning : data driven route generation for autonomous ship |
| title_full_unstemmed | Historical data is useful for navigation planning : data driven route generation for autonomous ship |
| title_short | Historical data is useful for navigation planning : data driven route generation for autonomous ship |
| title_sort | historical data is useful for navigation planning data driven route generation for autonomous ship |
| topic | Engineering::Mechanical engineering Marine Vehicles Navigation |
| url | https://hdl.handle.net/10356/147158 |
| work_keys_str_mv | AT tanweichian historicaldataisusefulfornavigationplanningdatadrivenroutegenerationforautonomousship AT wengchingyen historicaldataisusefulfornavigationplanningdatadrivenroutegenerationforautonomousship AT zhouyu historicaldataisusefulfornavigationplanningdatadrivenroutegenerationforautonomousship AT chuakiehian historicaldataisusefulfornavigationplanningdatadrivenroutegenerationforautonomousship AT cheniming historicaldataisusefulfornavigationplanningdatadrivenroutegenerationforautonomousship |