The last few years, robots have moved from the pages of science fiction books into our everyday reality. Currently, robots are utilized in entertainment, scientific exploration, manufacturing, and household maintenance. While the above advances were made possible by recent improvements in sensors, actuators, and computing elements, the research of today is focused on the computational aspects of robotics. In particular, methodologies for utilizing the vast volumes of data that can be generated by a robotic mission, together with techniques that would allow a robot to respond adequately in unforeseeable circumstances are the challenges of tomorrow.

This talk presents an overview of algorithmic problems related to marine robotics, with the particular focus on increasing the autonomy of robotic systems in challenging environments. I will talk about vision-based state estimation and mapping of shipwrecks, underwater caves, and coral reefs. Results on machine learning approaches for coral classification will be discussed. I will also talk about several vehicles used at the University of South Carolina such as underwater and surface vehicles. In addition a short overview of current projects will be discussed.

The work that I will present has a strong algorithmic flavour, while it is validated in real hardware. Experimental results from several testing campaigns will be presented.