by Alex Philipose John
In this report I present the design and development of core software components that run on board an Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vessel (ASV). To achieve the ultimate goal of demon- strating autonomous launch and recovery (LARS) of the AUV from the ASV, we rst develop the navigation and control system. First, a suitable under-water simulation stack is developed and the derivation of the hydrodynamic model is detailed. Second, the simulation stack is used to test the control system and a simple proof of concept neural network based real time PID tuner is developed. This enables the PID controller to adapt its constants to changing environmental conditions, particularly wind. O the shelf sensors used in inertial navigation is benchmarked and compared. The inertial navigation system used on two separate vehicles was dismantled and re-developed as an Error State Kalman lter that dynamically adapts to either GPS, Camera, USBL or DVL observations. Real world test results are showcased and analyzed.
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