Software

Simulation

To optimize testing time in the pool, a simulation of the course was created using the Gazebo software. This allows us to test the state machine logic and vision algorithms without needing to be physically in the pool.

This simulation is essential in helping us achieve our goals.

A computer-generated grid with obstacles and small drone-like objects arranged on it.

Vision

To detect different objects underwater, PIGEON is equipped with two cameras: a forward-facing stereo camera and a downward-facing camera to identify objects beneath the submarine.

A YOLO (You Only Look Once) detection algorithm is then used to identify objects during missions. Vision algorithms for estimating object angles and depths are also integrated to ensure smooth and accurate control of the submarine.

A colorful, pixelated digital image of a window with a purple and yellow color scheme.
Underwater image showing UAV parts detection with labels and confidence scores, including SOS safety, gate leg center, compass hammer, and gate leg right.

State machine

A custom decision tree was developed. The Nautilus team first identified the tasks they wanted to complete (Gate, Slalom, Torpedo, and Dropper), which then allowed them to determine an optimal path for PIGEON.

The decision tree can be seen in the diagram shown alongside.

Flowchart illustrating a robotic alignment and object detection process with steps such as alignment to center, moving in arc, centering table, surface detection, and identifying the next object, with decision points and different colored pathways.