Deployment and Development of a Cognitive Teleoreactive Framework for Deep Sea Autonomy

Abstract--A new AUV mission planning and execution software has been tested on AUV Sentry. Dubbed DINOS-R, it draws inspiration from cognitive architectures and AUV control systems to replace the legacy MC architecture. Unlike these existing architectures, however, DINOS-R is built from the ground-up to unify symbolic decision making (for understandable, repeatable, provable behavior) with machine learning techniques and reactive behaviors, for field-readiness across oceanographic platforms. Implemented primarily in Python3, DINOS-R is extensible, modular, and reusable, with an emphasis on non-expert use as well as growth for future research in oceanography and robot algorithms. Mission specification is flexible, and can be specified declaratively. Behavior specification is similarly flexible, supporting simultaneous use of real-time task planning and hard-coded user specified plans. These features were demonstrated in the field on Sentry, in addition to a variety of simulated cases. These results are discussed, and future work is outlined. In particular, although the MC (Mission Controller) system in use on AUV Sentry has repeatedly proven itself for lawnmower patterns, it presents several key limitations stemming from its rigid implementation. Most notably, it is capable of executing basic "go-to" commands and similar functionality, but was not engineered for scalability to new mission modalities or real-time interventions.