
Mathew Chu developed a Torpedo Target Detection Node for the DukeRobotics/robosub-ros2 repository, focusing on enhancing autonomous perception capabilities. He implemented the node using C++ and Python, leveraging computer vision techniques such as HSV color filtering and contour matching to process camera input and identify upper and lower torpedo targets. The node outputs bounding box data for detected targets, supporting downstream planning and control modules. To facilitate validation and tuning, Mathew included intermediate debugging visuals, such as HSV-filtered and contour-detected images. This work deepened the ROS2 perception pipeline, reducing manual intervention and providing actionable vision data for mission readiness.
February 2025 summary for DukeRobotics/robosub-ros2: Implemented a new Torpedo Target Detection Node in the ROS2 perception stack. The node processes camera input using HSV color filtering and contour matching against a reference image to detect upper and lower torpedo targets and publishes bounding box information for downstream planning and control. It also outputs intermediate debugging visuals (HSV-filtered and contour-detected views) to aid validation and tuning. This work includes an initial HSV-based torpedo detection implementation committed to the repository. No major bugs were documented this month. Overall, the feature enhances autonomous target detection, reduces manual intervention, and improves mission readiness by providing actionable vision data for downstream modules.
February 2025 summary for DukeRobotics/robosub-ros2: Implemented a new Torpedo Target Detection Node in the ROS2 perception stack. The node processes camera input using HSV color filtering and contour matching against a reference image to detect upper and lower torpedo targets and publishes bounding box information for downstream planning and control. It also outputs intermediate debugging visuals (HSV-filtered and contour-detected views) to aid validation and tuning. This work includes an initial HSV-based torpedo detection implementation committed to the repository. No major bugs were documented this month. Overall, the feature enhances autonomous target detection, reduces manual intervention, and improves mission readiness by providing actionable vision data for downstream modules.

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