ATLS: Automated Trailer Loading for Surface Vessels
Amer Abughaida, Meet Gandhi, Jun Heo, Vaishnav Tadiparthi, Yosuke, Sakamoto, Joohyun Woo, Sangjae Bae

TL;DR
This paper presents a mathematical framework for automated trailer loading of surface vessels, addressing wind disturbances and perception errors, demonstrated on a commercial pontoon boat with promising success rates.
Contribution
It introduces a novel pipeline combining localization, system identification, and trajectory optimization for trailer loading under challenging conditions.
Findings
Achieved 80% success rate in real-world tests
Effectively handles wind disturbances and perception errors
Demonstrates potential for practical marine automation
Abstract
Automated docking technologies of marine boats have been enlightened by an increasing number of literature. This paper contributes to the literature by proposing a mathematical framework that automates "trailer loading" in the presence of wind disturbances, which is unexplored despite its importance to boat owners. The comprehensive pipeline of localization, system identification, and trajectory optimization is structured, followed by several techniques to improve performance reliability. The performance of the proposed method was demonstrated with a commercial pontoon boat in Michigan, in 2023, securing a success rate of 80\% in the presence of perception errors and wind disturbance. This result indicates the strong potential of the proposed pipeline, effectively accommodating the wind effect.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsOffshore Engineering and Technologies · Engineering Structural Analysis Methods
