Towards a Semantic Digital Twin for Marine Robotics

Abstract:
Digital twins (DTs) offer high-fidelity, dataenhanced virtual representations of physical entities. Introduced by NASA, DTs have since found popularity in the automotive, healthcare, energy, and, in particular, robotic sectors. In this work, we discuss the potential of semantic DTs (SemDTs) in the harsh, dynamic, and unstructured environments common to marine robots. The proposed SemDTs offer several improvements over traditional DTs including: ontology-based knowledge representations of both the robot and its environment, symbolic reasoning mechanisms relating the knowledge generated and required during underwater missions, and semantic scene graphs to interpret and explain the current state of the robot-environment system. To guide the discussion of the proposed framework, we consider a particularly promising application of the SemDT—that of an autonomous underwater vehicle performing inspection and monitoring of a subsea station.