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.

翻译：一种新型自主水下航行器任务规划与执行软件已在AUV Sentry上完成测试。该软件命名为DINOS-R，其设计灵感来源于认知架构与AUV控制系统，旨在替代传统的MC架构。与现有架构不同，DINOS-R采用全新架构设计，将符号化决策（用于实现可理解、可重复、可验证的行为）与机器学习技术及反应式行为相融合，以实现跨海洋学平台的现场部署就绪性。DINOS-R主要采用Python3实现，具备可扩展性、模块化和可复用性，注重非专业用户的使用体验，并为未来海洋学与机器人算法研究预留发展空间。任务规范具有灵活性，可采用声明式方式定义。行为规范同样灵活，支持实时任务规划与硬编码用户定制方案的并行使用。除多种仿真场景外，这些功能已在Sentry平台上完成实地验证。本文讨论了相关实验结果，并对未来研究方向进行了展望。