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In this paper, we summarize the experiences with the autonomous passenger ferry development prototype milliAmpere, which has been used as a test platform in several research projects at the Norwegian University of Science and Technology (NTNU) since 2017. New algorithms for motion planning, motion control, collision avoidance, docking, multi-target tracking and localization have been developed and verified in full-scale experiments with milliAmpere. The infrastructure surrounding milliAmpere includes several sensor rigs supporting research on multi-sensor fusion and situational awareness, and a shore control lab which can be used to study the interaction between human operators and the autonomous ferry. Building upon the experiences with milliAmpere, the full-scale autonomous ferry milliAmpere2 was recently launched.

Safe navigation for autonomous surface vehicles requires a robust and reliable tracking system that maintains and estimates position and velocity of other vessels. This paper demonstrates a measurement level sensor fusion system for tracking in a maritime environment using lidar, radar, electrooptical and infrared cameras. The backbone of the system is a multi-sensor version of the Joint Integrated Probabilistic Data Association (JIPDA) with both existence and visibility probabilities. Using reference targets equipped with GPS receivers, the performance of different sensors and sensor combinations are evaluated for autonomous surface vehicles (ASVs). Several interesting observations are made, among them that passive sensors can help resolve merged measurements issues in radar tracking, and that the choice between radar and lidar may boil down to a trade-off between fast track initiation and large numbers of false tracks.