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Perception

The Perception team is responsible for translating the boat’s surroundings, position, and orientation into information useful for decision making. This encompasses both computer vision and sensors.

Computer Vision

Members working on computer vision spend time researching neural networks, building and training an object detection model, augmenting and annotating data, and integrating the model with our ZED 2i camera. The CV group had one main goal this semester: to make our model more robust. Some of the annotations were inaccurate leading the model to recognize objects incorrectly. We worked on correcting these annotations to ensure the model was given the best possible data to be trained on.

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A big project the CV group has been working on is creating a testing plan to go about choosing the best YOLO model that suits our needs and produces the best results. We researched each YOLO model version and size and noted their advantages and disadvantages. We then went out testing these YOLO model versions and sizes and ultimately saw that YOLOv8 yielded the best results.

A future goal of the CV group is building a neural network from scratch to serve as our new object detection model. There has been some progress on this but it is still in its elementary development phase.

Sensors

Our sensor suite includes a ZED2i stereo camera, SparkFun MicroMod GNSS boards, and a Vectornav VN-300 GPS/IMU. The sensors group works closely with members of the Controls & Microcontrollers and Electrical Systems groups to integrate the sensors into our microcontroller framework.

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In the future, we hope to integrate LiDAR into our sensor suite for more robust depth sensing and confirmation of the objects detected by CV.

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