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Conference Presentation - IEEE OCEANS25 in Brest

Activité: Conférence ou présentationPrésentation orale à caractère scientifique

Description

Participation and presentation at the IEEE OCEANS25 conference in Brest, France.
Presentation of our conference paper "Belief Propagation-Based Sensor Fusion for Monitoring Dynamic Maritime Environments and Autonomous Navigation".

Description complémentaire

We present a distributed multi-sensor multi-target
tracking algorithm for maritime surveillance using unmanned
surface vehicles (USVs) in multi-agent settings. Our approach
fuses measurements from radar, Automatic Identification System
(AIS), and camera sensors within a Bayesian framework, employing
an adaptive particle filtering strategy to jointly estimate
the kinematic states and identities of vessels. Our solution
incorporates a factorized data association model that integrates
cooperative self-reports from AIS with radar and camera measurements,
with visual re-identification capability. We evaluate
our method using a high-fidelity simulation environment, which
generates photorealistic maritime scenarios. Our performance
analysis indicates that the integration of camera-based cues
improves both the spatial localization and identity consistency,
particularly in scenarios with low radar detection probability and
non-cooperative targets. Furthermore, the distributed inference
framework scales well with the number of USVs, making it
well suited for large-scale multi-agent applications. Overall, our
work demonstrates that fusing heterogeneous sensor modalities
using belief propagation can enhance multi-target tracking performance
in congested maritime environments.
Période16 juin 202519 juin 2025
Titre de l'événementOCEANS 2025 Brest, OCEANS 2025
Type d'événementUne conférence
EmplacementBrest, FranceAfficher sur la carte
Degré de reconnaissanceInternational

mots-clés

  • Multi-target tracking
  • Maritime surveillance
  • Unmanned Surface Vessels
  • Distributed sensor fusion
  • Particle filtering
  • Belief propagation
  • Multi-agent robotics