Deep models optimization on embedded devices to improve the orientation estimation task at sea

The environmental monitoring task has greatly benefited from the improvements achieved in the robotics field. The enhancement of navigation and control algorithms, together with the use of performing, small and low-cost sensors, allows in fact to reduce the implementation costs while improving the system reliability. This is strongly supported by the developments of embedded hardware, smart computing devices able to collect and process data in real-time and in low-resource settings. Following the results obtained by DOES, this work aims at putting another step towards its deployment in live scenarios: we propose a study on the performances of DOES tested on embedded systems, using lighter backbone architectures and model optimization techniques

DANAE: A denoising autoencoder for underwater attitude estimation

One of the main issues for underwater robots navigation is their accurate positioning, which heavily depends on the orientation estimation phase. The systems employed to this scope are affected by different noise typologies, mainly related to the sensors and to the irregular noise of the underwater environment. Filtering algorithms can reduce their effect if opportunely configured, but this process usually requires fine techniques and time. In this paper we propose DANAE, a deep Denoising AutoeNcoder for Attitude Estimation which works on Kalman filter IMU/AHRS data integration with the aim of reducing any kind of noise, independently of its nature. This deep learningbased architecture showed to be robust and reliable, significantly improving the Kalman filter results. Further tests could make this method suitable for real-time applications on navigation tasks

Optimization of the Maritime Signaling System in the Lagoon of Venice

Aids to Navigation (AtoN) are auxiliary devices intended to support maritime navigation. They include both traditional signals (e.g., buoys and lights) and electronic aids, as for example those transmitted to ships through automatic tracking systems. In both cases, international organizations together with local authorities define technical specifications and standards on their use. Work still being finalized in the Venetian Lagoon made it necessary an assessment of the existing signaling system to guarantee the maximum level of safety in the waterways. Considering the severe atmospheric conditions to which the Lagoon is frequently subjected and the bathymetry restrictions affecting the navigation, an alternative aid system has been formalized for the first time in Italy. It is based on electronic and identification devices employed to virtualize the AtoN that will not be located at sea but only remotely identified by their coded messages, thus guaranteeing the continuity of port operations in any visibility conditions. This paper presents the procedures followed to reach a solution in line with the safety and efficiency standards given for the AtoN systems, considering position and luminous characteristics of physical signals in the first case, theoretical and statistical studies on Virtual AIS AtoN placement in the second case

Optimization of the maritime signaling in the Venetian Lagoon

Aids to Navigation (AtoN) are supporting devices to nautical operations. They include both electronic and traditional signaling systems (e.g. buoys and lights), for which international organizations together with local authorities define operative and technical standards. Work still being finalized in the Venetian Lagoon made it necessary an assessment of the existing signals, with the aim of optimizing their position to guarantee the maximum level of safety in the waterways.This paper presents the procedures followed to reach a solution in line with the safety and efficiency standards given for the AtoN systems in terms of position and luminous characteristics. Moreover, to ensure the continuity of port operations even in poor visibility conditions, an alternative aid system has been studied and formalized for the first time in Italy. It is based on electronic and identification devices which show Virtual AtoN, AtoN that are not physically at sea

An Enhanced Photogrammetric Approach for the Underwater Surveying of the Posidonia Meadow Structure in the Spiaggia Nera Area of Maratea

The Posidonia oceanica meadows represent a fundamental biological indicator for the assessment of the marine ecosystem’s state of health. They also play an essential role in the conservation of coastal morphology. The composition, extent, and structure of the meadows are conditioned by the biological characteristics of the plant itself and by the environmental setting, considering the type and nature of the substrate, the geomorphology of the seabed, the hydrodynamics, the depth, the light availability, the sedimentation speed, etc. In this work, we present a methodology for the effective monitoring and mapping of the Posidonia oceanica meadows by means of underwater photogrammetry. To reduce the effect of environmental factors on the underwater images (e.g., the bluish or greenish effects), the workflow is enhanced through the application of two different algorithms. The 3D point cloud obtained using the restored images allowed for a better categorization of a wider area than the one made using the original image elaboration. Therefore, this work aims at presenting a photogrammetric approach for the rapid and reliable characterization of the seabed, with particular reference to the Posidonia coverage