  Robots are becoming an essential part of many operations including marine
exploration or environmental monitoring. However, the underwater environment
presents many challenges, including high pressure, limited visibility, and
harsh conditions that can damage equipment. Real-world experimentation can be
expensive and difficult to execute. Therefore, it is essential to simulate the
performance of underwater robots in comparable environments to ensure their
optimal functionality within practical real-world contexts.OysterSim generates
photo-realistic images and segmentation masks of objects in marine
environments, providing valuable training data for underwater computer vision
applications. By integrating ChatGPT into underwater simulations, users can
convey their thoughts effortlessly and intuitively create desired underwater
environments without intricate coding. \invis{Moreover, researchers can realize
substantial time and cost savings by evaluating their algorithms across diverse
underwater conditions in the simulation.} The objective of ChatSim is to
integrate Large Language Models (LLM) with a simulation
environment~(OysterSim), enabling direct control of the simulated environment
via natural language input. This advancement can greatly enhance the
capabilities of underwater simulation, with far-reaching benefits for marine
exploration and broader scientific research endeavors.
