The talk will first give a brief overview on current robotic system developments at the DFKI RIC in the maritime context, from new remotely operated vehicles (ROVs), hybrid ROVs, to hydrobatic autonomous underwater vehicles (AUVs) with intervention capabilities and subsea crawlers.
We will then take a deeper look into the software architectures and autonomous capabilities of such systems and discuss autonomous mission planning, task decomposition and execution, concepts like behaviour trees, approaches to sensor fusion and environment representation and how systems can reason about their own state and marine environment and act accordingly.
The talk will also showcase two real-world examples of successful application of machine learning methods to marine robots in order to identify the motion model and to learn magnetic field distortions for navigation purposes.