Offshore pipelines and structures require regular marine growth removal and inspection to ensure structural integrity. These operations are typically carried out by Remotely Operated Vehicles (ROVs) and demand reliable and accurate feedback signals for operating the ROVs efficiently under harsh offshore conditions. This study investigates and quantifies how sensor delays impact the expected control performance without the need for defining the control parameters. Input-output (IO) controllability analysis of the open-loop system is applied to find the lower bound of the H-infinity peaks of the unspecified optimal closed-loop systems. The performance analyses have shown that near-structure operations, such as pipeline inspection or cleaning, in which small error tolerances are required, have a small threshold for the time delays. The IO controllability analysis indicates that off-structure navigation allow substantial larger time delays. Especially heading is vulnerable to time delay; however, fast-responding sensors usually measure this motion. Lastly, a sensor comparison is presented where available sensors are evaluated for each ROV motion’s respective sensor-induced time delays. It is concluded that even though off-structure navigation have larger time delay tolerance the corresponding sensors also introduce substantially larger time delays.
Autonomous systems strive to obtain salient features that include computer intelligence for obtaining situation awareness, decision support to a human navigator, or for facilitating autonomous decision-making in unmanned vehicles. This paper considers the case of autonomous marine surface vehicles, where high-quality decision support will be instrumental for obtaining a periodically unattended bridge and for approval of unmanned bridge operation with fallback through remote operation. The proposed design focuses on a sovereign-based architecture that facilitates safety, resilience and cyber-security. We address central elements of risk in the development and approval of autonomous systems; we analyze the challenges associated with testing, commissioning and maintenance of a highly complex cyber-physical system, and describe design principles for the sovereign agents architecture.