To reduce Operation and Maintenance (O&M) costs on offshore wind farms, wherein 80% of the O&M cost relates to deploying personnel, the offshore wind sector looks to Robotics and Artificial Intelligence (RAI) for solutions. Barriers to Beyond Visual Line of Sight (BVLOS) robotics include operational safety compliance and resilience, inhibiting the commercialization of autonomous services offshore. To address safety and resilience challenges we propose a Symbiotic System Of Systems Approach (SSOSA), reflecting the lifecycle learning and co-evolution with knowledge sharing for mutual gain of robotic platforms and remote human operators. Our novel methodology enables the run-time verification of safety, reliability and resilience during autonomous missions. To achieve this, a Symbiotic Digital Architecture (SDA) was developed to synchronize digital models of the robot, environment, infrastructure, and integrate front-end analytics and bidirectional communication for autonomous adaptive mission planning and situation reporting to a remote operator. A reliability ontology for the deployed robot, based on our holistic hierarchical-relational model, supports computationally efficient platform data analysis. We demonstrate an asset inspection mission within a confined space through Cooperative, Collaborative and Corroborative (C3) governance (internal and external symbiosis) via decision-making processes and the associated structures. We create a hyper enabled human interaction capability to analyze the mission status, diagnostics of critical sub-systems within the robot to provide automatic updates to our AI-driven run-time reliability ontology. This enables faults to be translated into failure modes for decision-making during the mission.
翻译:为了降低离岸风力农场的运行和维护(O&M)成本(O&M)成本(O&M成本的80%与部署人员有关),离岸风力部门期待机器人和人工智能(RAI)解决问题。超视线(BVLOS)机器人的障碍包括操作安全合规和复原力,阻止离岸自主服务商业化。为了应对安全和复原力挑战,我们提议建立一个系统方法共生系统(SSOSA),反映生命周期学习和共同演变,分享知识,共同获取机器人平台和远程人类操作者的共同收益。我们的新方法使得能够在自主任务期间对安全、可靠性和复原力进行实时核查。为了实现这一目标,开发了一个Symsocial数字架构(SDADA),以同步机器人、环境、基础设施以及整合前端分析和双向通信等数字模型,以自主适应任务规划和向远程操作者报告情况。基于我们的整体等级关系模型,对部署的机器人进行可靠的数据分析,支持计算高效的平台数据分析。为了实现这一点,我们通过合作、合作性、内部分析、内部分析,使资产检查和内部分析能够通过内部分析,使内部分析系统进行内部分析,使内部分析成为内部分析。