Autonomous Underwater Vehicle: Electronics and Software Implementation of the Proton AUV
This work addresses the problem of enabling autonomous navigation and object detection for underwater vehicles, but it appears incremental as it builds on existing protocols and methods.
The paper tackled the development of electronics and software for an autonomous underwater vehicle, resulting in a system that integrates hardware communication and implements a CNN-based object detection algorithm with hyperparameter tuning for specific models.
The paper deals with the software and the electronics unit for an autonomous underwater vehicle. The implementation in the electronics unit is the connection and communication between SBC, pixhawk controller and other sensory hardware and actuators. The major implementation of the software unit is the algorithm for object detection based on Convolutional Neural Network (CNN) and its models. The Hyperparameters were tuned according to Odroid Xu4 for various models. The maneuvering algorithm uses the MAVLink protocol of the ArduSub project for movement and its simulation.