Historical Data is Useful for Navigation Planning: Data Driven Route Generation for Autonomous Ship
Wei Chian Tan, Ching-Yen Weng, Yu Zhou, Kie Hian Chua, I.-Ming Chen
Abstract
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.
BibTeX
@inproceedings{icra2018_historicaldatais,
title = {Historical Data is Useful for Navigation Planning: Data Driven Route Generation for Autonomous Ship},
author = {Wei Chian Tan and Ching-Yen Weng and Yu Zhou and Kie Hian Chua and I.-Ming Chen},
booktitle = {ICRA 2018},
year = {2018}
}