Low-end small unmanned surface vehicles (USV) are higly agile machines ideal for patrolling coastal waters. Such vehicles are typically used in perimeter surveillance, in which the USV travels along a pre-planned path. To quickly and efficiently respond to the challenges from highly dynamic environment, the USV requires an onboard logic to observe the surrounding, detect potentially dangerous situations, and apply proper route modifications. This page is a collection of algorithms and approaches that we have developed for such machines.
This is a Matlab demo code for the semantic segmentation model for obstacle image map estimation for unmanned surface vehicles. The demo requires downloading the MOD dataset and has pretrained hiperparameters on the MOD dataset.