A Distributed, Passivity-Based Control of Autonomous Mobile Sensors in an Underwater Acoustic Network

This paper presents a cooperative and distributed control law for multiple Autonomous Underwater Vehicles (AUVs) executing a mission while meeting mutual communication constraints. Virtual couplings define interaction control forces between neighbouring vehicles. Moreover, the couplings are designed to enforce a desired vehicle-vehicle and vehicle-target spacing. The whole network is modelled in the passive, energy-based, port-Hamiltonian framework. Such framework allows to prove closed-loop stability using the whole system kinetic and virtual potential energy by constructing a suitable Lyapunov function. Furthermore, the robustness to communication delays is also demonstrated. Simulation results are given to illustrate the effectiveness of the proposed approach

Adaptable underwater networks: The relation between autonomy and communications

This paper discusses requirements for autonomy and communications in maritime environments through two use cases which are sourced from military scenarios: Mine Counter Measures (MCM) and Anti-Submarine Warfare (ASW). To address these requirements, this work proposes a service-oriented architecture that breaks the typical boundaries between the autonomy and the communications stacks. An initial version of the architecture has been implemented and its deployment during a field trial done in January 2019 is reported. The paper discusses the achieved results in terms of system flexibility and ability to address the MCM and ASW requirements

A nonlinear complementary filter for underwater navigation using inertial measurements

This paper describes a nonlinear complementary filter capable of estimating the course motion variables namely the position, velocity, heading and accelerometers bias of an agile, over-actuated AUV during underwater operations, using the inertial sensors (IMU), the DVL, the depth sensor and the compass. The proposed work is within the framework of the V-Fides project, co-funded by Tuscany Region (Italy) and developed by a team lead by WASS S.p.A. (Whitehead Sistemi Subacquei, Livorno). The aim of the project was to develop and evaluate an high-depth, over-actuated, long endurance Autonomous Underwater Vehicle (AUV). The paper proposes the mathematical development of the observer, together with some experimental results, able to demonstrate the capabilities of the estimation scheme, compared with the estimations obtained via a standard Kalman Filter

Ad hoc Acoustic Network Aided Localization for micro-AUVs

The navigation of Autonomous Underwater Vehicles (AUVs) is still an open research problem. This is further exacerbated when vehicles can only carry limited sensors as typically the case with micro-AUVs that need to survey large marine areas that can be characterized by high currents and dynamic environments. To address this problem, this work investigates the usage of ad hoc acoustic networks that can be established by a set of cooperating vehicles. Leveraging the network structure makes it possible to greatly improve the navigation of the vehicles and as a result to enlarge the operational envelope of vehicles with limited capabilities. The paper details the design and implementation of the network, and specific details of localization and navigation services made available to the vehicles by the network stack. Results are provided from a sea-trial undertaken in Croatia in October 2019. Results validate the approach, demonstrating the increased flexibility of the system and the navigational performance obtained: the deployed network was able to support long-range navigation of vehicles with no inertial navigation or Doppler Velocity Log (DVL) during a 9.5 km channel crossing, reducing the navigation error from approximately 7% to 0.27% of the distance traveled

Development of a navigation algorithm for autonomous underwater vehicles

In this paper, the authors present an underwater navigation system for Autonomous Underwater Vehicles (AUVs) which exploits measurements from an Inertial Measurement Unit (IMU), a Pressure Sensor (PS) for depth and the Global Positioning System (GPS, used during periodic and dedicated resurfacings) and relies on either the Extended Kalman Filter (EKF) or the Unscented Kalman Filter (UKF) for the state estimation. Both (EKF and UKF) navigation algorithms have been validated through experimental navigation data related to some sea tests performed in La Spezia (Italy) with one of Typhoon class vehicles during the NATO CommsNet13 experiment (held in September 2013) and through Ultra-Short BaseLine (USBL) fixes used as a reference (ground truth). Typhoon is an AUV designed by the Department of Industrial Engineering of the Florence University for exploration and surveillance of underwater archaeological sites in the framework of the Italian THESAURUS project and the European ARROWS project. The obtained results have demonstrated the effectiveness of both navigation algorithms and the superiority of the UKF (very suitable for AUV navigation and, up to now, still not used much in this field) without increasing the computational load (affordable for on-line on-board AUV implementation)

Interoperability Among Unmanned Maritime Vehicles: Review and First In-field Experimentation

Complex maritime missions, both above and below the surface, have traditionally been carried out by manned surface ships and submarines equipped with advanced sensor systems. Unmanned Maritime Vehicles (UMVs) are increasingly demonstrating their potential for improving existing naval capabilities due to their rapid deployability, easy scalability, and high reconfigurability, offering a reduction in both operational time and cost. In addition, they mitigate the risk to personnel by leaving the man far-from-the-risk but in-the-loop of decision making. In the long-term, a clear interoperability framework between unmanned systems, human operators, and legacy platforms will be crucial for effective joint operations planning and execution. However, the present multi-vendor multi-protocol solutions in multi-domain UMVs activities are hard to interoperate without common mission control interfaces and communication protocol schemes. Furthermore, the underwater domain presents significant challenges that cannot be satisfied with the solutions developed for terrestrial networks. In this paper, the interoperability topic is discussed blending a review of the technological growth from 2000 onwards with recent authors' in-field experience; finally, important research directions for the future are given. Within the broad framework of interoperability in general, the paper focuses on the aspect of interoperability among UMVs not neglecting the role of the human operator in the loop. The picture emerging from the review demonstrates that interoperability is currently receiving a high level of attention with a great and diverse deal of effort. Besides, the manuscript describes the experience from a sea trial exercise, where interoperability has been demonstrated by integrating heterogeneous autonomous UMVs into the NATO Centre for Maritime Research and Experimentation (CMRE) network, using different robotic middlewares and acoustic modem technologies to implement a multistatic active sonar system. A perspective for the interoperability in marine robotics missions emerges in the paper, through a discussion of current capabilities, in-field experience and future advanced technologies unique to UMVs. Nonetheless, their application spread is slowed down by the lack of human confidence. In fact, an interoperable system-of-systems of autonomous UMVs will require operators involved only at a supervisory level. As trust develops, endorsed by stable and mature interoperability, human monitoring will be diminished to exploit the tremendous potential of fully autonomous UMVs

Estimation filtering for Deep Water Navigation

The navigation task for Unmanned Underwater Vehicles is made difficult in a deep water scenario because of the lack of bottom lock for Doppler Velocity Log (DVL). This is due to the operating altitude that, for this kind of applications, is typically greater than the sensor maximum range. The effect is that the velocity measurements are biased by sea currents resulting in a rapidly increasing estimation error drift. The solution proposed in this work is based on a distributed, cooperative strategy strongly relying on an acoustic underwater network. According to the distributed philosophy, an instance of a specifically designed navigation filter (named DWNF - Deep Water Navigation Filter) is executed by each vehicle. Each DWNF relies on different Extended Kalman Filters (EKFs) running in parallel on-board: one for own navigation state estimation (AUV-EKF), the other ones for the navigation state of the remaining assets (Asset-EKF). The AUV-EKF is designed to simultaneously estimate the vehicle position and the sea current for more reliable predictions. The DWNF builds in real-time a database of past measurements and estimations; in this way it can correctly deal with delayed information. An outlier detection and rejection policy based on the Mahalanobis distance associated to each measurement is implemented. The experimental validation of the proposed approach took place in a deep water scenario during the Dynamic Mongoose’17 exercise off the South coast of Iceland (June-July 2017); preliminary analysis of the results is presented

Fusing Acoustic Ranges and Inertial Measurements in AUV Navigation: the Typhoon AUV at CommsNet13 Sea Trial

The paper presents some experimental results of autonomous underwater navigation, based on the fusion of acoustic and inertial measurements. The work is in the framework of the Thesaurus project, funded by the Tuscany Region, aiming at developing techniques for systematic exploration of marine areas of archaeological interest through a team of Autonomous Underwater Vehicles (AUVs). The test was carried out with one Typhoon vehicle, a 300m depth rated AUV with acoustic communication capabilities, during the CommsNet13 experiment, organized and scientifically coordinated by the NATO S&T Org. Ctr. for Maritime Research and Experimentation (CMRE, formerly NURC), with the participation of several research institutions. The fusion algorithm is formally casted into an optimal stochastic filtering problem, where the rough estimation of the vehicle position, velocity and attitude, are refined by using the depth measurement, the relative measurements available on the acoustic channel and the vehicle surge speed