Robust Continuous System Integration for Critical Deep-Sea Robot Operations Using Knowledge-Enabled Simulation in the Loop

Abstract

Deep-sea robot operations demand a high level of safety, efficiency and reliability. As a consequence, measures within the development stage have to be implemented to extensively evaluate and benchmark system components ranging from data acquisition, perception and localization to control. We present an approach based on high-fidelity simulation that embeds spatial and environmental conditions from recorded real-world data. This simulation in the loop (SIL) methodology allows for mitigating the discrepancy between simulation and real-world conditions, e.g. regarding sensor noise. As a result, this work provides a platform to thoroughly investigate and benchmark behaviors of system components concurrently under real and simulated conditions. The conducted evaluation shows the benefit of the proposed work in tasks related to perception and self-localization under changing spatial and environmental conditions.

Synthetic Aperture Sonar (SAS) without Navigation: Scan Registration as Basis for Near Field Synthetic Imaging in 2D

“…The object used for the experiments here ( Figure 10 ) is a test structure in the form of a mock-up panel for trials in the context of deep-sea oil- and gas-production (OGP) [ 18 ], which was used in the EU project “Effective Dexterous ROV Operations in Presence of Communications Latencies (DexROV)”. In DexROV, the amount of robot operators required offshore (Mediterranean Sea, offshore of Marseille, France) was reduced—hence, reducing cost and inconveniences—by facilitating offshore OPG operations from an onshore control center (in Brussels, Belgium) via a satellite communication link and by reducing the gap between low-level tele-operation and full autonomy, among others by enabling machine perception on-board of the Remotely Operated Vehicle (ROV) itself [ 43 , 44 , 45 , 46 ]. The model of the test structure is in the following experiments in a top-down view, which corresponds to the scenario when the ROV is in the initial approach phase, i.e., when sonar is used to localize the target structure from above.…”

Detecting Square Markers in Underwater Environments

“…In the clear water of swimming pools, developers of games for diving children can use AR to place visually-appealing virtual objects and rewards on markers, as was presented by Bellarbi et al [43], who used specialized hardware, or Oppermann et al [44], who used a tablet in a waterproof housing. In the bad visibility conditions of open sea, markers are used to detect and track the position of remotely-operated vehicles (ROVs) [45], which is extremely important when performing an automatic docking of autonomous underwater vehicles (AUVs) [46,47]. In close ranges where the visibility conditions are still sufficient, markers are used for underwater photogrammetry either in the form of large calibration frames [48] or small and light quadrats [49].…”