Daniel Freire

Papers

Total Citations

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About

Daniel Freire is a researcher specializing in autonomous maritime systems, with a particular focus on obstacle detection and collision avoidance for Autonomous Surface Vehicles (ASVs). His work addresses a critical challenge in marine robotics: enabling ASVs to safely navigate congested waterways near harbors and shorelines by reliably tracking and avoiding both static and dynamic obstacles. Freire’s most cited paper, “Radar-based target tracking for Obstacle Avoidance for an Autonomous Surface Vehicle (ASV)” (2019), proposes a multi-target tracking framework that integrates radar data with avoidance algorithms, allowing vessels to steer clear of incoming ships and other hazards in real time. This contribution is foundational for the development of robust, perception-driven navigation systems in unpredictable marine environments. While his citation count remains modest, his research is highly relevant to the growing field of autonomous shipping and maritime safety. Freire’s work exemplifies the practical engineering required to transition ASVs from controlled trials to real-world deployment, making him a notable contributor to the advancement of intelligent, self-navigating vessels.