Explorations in AI for Marine Robotics
Ocean Sciences the world over is at a cusp, with a move from the Expeditionary to the Observatory mode of doing science. With the advent of ocean observatories, a number of key technologies have proven to be promising for sustained ocean presence — Robotics and AI are some of these. In this context robots will need to be contextually aware and respond rapidly to evolving phenomenon, especially in dynamic waters due to the diversity of atmospheric, oceanographic and land-sea interactions. They will need to respond by exhibiting scientific opportunism while being aware of their own limitations in the harsh oceanic environment. We have designed, built, tested and deployed deliberative techniques to dynamically command autonomous underwater vehicles (AUVs) with deep roots in work to command and control deep space probes for NASA. Our effort is aimed to use a blend of generative and deliberative Artificial Intelligence Planning and Execution techniques to shed goals, introspectively analyze onboard resources and recover from failures. In addition we are working on Machine Learning techniques to adaptively trigger science instruments that will contextually sample the seas driven by scientific intent. The end goal is towards unstructured exploration of the subsea environments that are a rich trove of problems for autonomous systems. This work is a continuum of efforts from research at NASA to command deep space probes and Mars rovers, the lessons of which we have factored into the oceanic domain.