Autonomous Docking Using LiDAR-Based Tracking and Adaptive Pose Selection: Closed-Loop Sea Trials
August Johansen Fors, Simon J. N. Lexau, Edmund Brekke, Miguel Hinostroza, Anastasios M. Lekkas, Morten Breivik
AI summary
Problem
Current autonomous docking systems struggle with dynamic obstacles, lack real-time environmental adaptation, and remain unvalidated in live maritime traffic.
Approach
The authors integrated cartographic land masking, LiDAR clustering, probabilistic multi-target tracking, and adaptive pose selection into a finite state machine framework, validated via closed-loop sea trials on a research ferry.
Key results
- First integrated LiDAR perception-to-control pipeline demonstrated under real maritime traffic
- Successful closed-loop collision avoidance and adaptive docking with moving obstacles
- Online computation of safe docking regions and pose selection despite dynamic interference
- Operational insights on sensor limits, tracking stability, and runtime constraints
Why it matters
Demonstrates that robust autonomous harbor operations can be achieved by carefully engineering existing perception and control methods, guiding marine robotics deployment.
Abstract
This paper presents a fully integrated autonomous docking system validated through closed-loop sea trials on the milliAmpere1 research ferry operating in a live maritime harbour with moving vessels. Real harbour environments require continuous situational awareness and adaptive decision- making under dynamic traffic conditions. The proposed architecture combines cartographic land masking, LiDAR- based clustering, probabilistic multi-target tracking (JIPDA), dynamic footprint estimation, adaptive docking pose selection, and real-time path replanning within a finite state machine framework. Rather than introducing new algorithms, the contribution lies in system-level integration and operational validation of a complete perception-to-control pipeline under realistic maritime constraints. The system is demonstrated in multiple closed-loop experiments including collision avoidance and adaptive docking with moving obstacles. Results highlight both performance characteristics and practical deployment considerations, including runtime behaviour, sensor limitations, and integration trade-offs. The work provides empirical evidence that robust autonomous docking in dynamic harbour environments can be achieved through carefully engineered integration of established methods.