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Motivated by the increasing availability and quality of miniaturized sensors, computers, and wireless communication devices arid given their enormous potential, the use of wireless sensor networks (WSN) has become widespread. Because in many applications of WSNs one is required to estimate at each local sensor unit the state of a system given the measurements acquired by multiple sensors, there has been a flurry of activity related to the theory of distributed state estimation. This article contains a literature survey of distributed state estimation for discrete-time linear time invariant systems. In order to obtain the proper historical context, we review the state of the art in this field and summarize previous work. To provide the mathematical intuition behind some of the methods, this survey paper reproduces some of the main results given in the literature. It also provides a critical appraisal of the state of the art and affords the reader a comprehensive presentation of the most relevant results published so far. (C) 2019 Elsevier Ltd. All rights reserved.

The past few years have seen a steady rise of public interest in ocean science and technology as evident through the United Nations proclaiming the coming decade as the United Nations Decade of Ocean Science for Sustainable Development. To appropriately address this challenge, it is essential to possess the right set of information dissemination tools. In this paper, we present a steady effort towards one such tool, called the Networked Marine Systems Simulator or NetMarSyS. Here, we describe a platform to model and visualize the behaviour of marine vehicles in three-dimensional space for surface and subsurface applications. The simulator is suitable for a wide range of applications, from a single-vehicle lawnmower survey to a complex multi-vehicle cooperative mission scenario. We use Robot Operating System, Unity3D game engine and WebSocket server technology to create a distributed multi-agent networked system where in multi-vehicle simulation is carried out. This allow us to support Hardware-in-the-Loop, Software-in-the-Loop simulations and real-time mission visualization. We highlight the competence of the visualizing software using an reference underwater-docking mission comprising of 2 vehicles, and one underwater structure.

The Sustainable Development Goals (SDGs), also known as the Global Goals, were adopted by all United Nations Member States in 2015 as a universal call to action to end poverty, protect the planet and ensure that all people enjoy peace and prosperity by 2030. All sectors of the society need to be involved in order to achieve those goals. This paper represents an initiative among several universities to explicitly look at the UN SDGs from the higher education perspective, in the field of marine systems and robotics, fostering self- reflection, developing specific actions addressing several goals. Currently half-way in the project life, the preliminary results and the activities performed up to now are very promising, bringing academia closer to the implementation of the Agenda 2030.

In many scientific and commercial missions at sea, it is of crucial importance to localize one ore more targets underwater. This objective meets with difficulties due to the unavailability of GPS underwater and the high cost of the equipment classically used for target localization. For these reasons, there has been a surge of interest in the problem of range-based underwater target localization, defined as that of localizing a group of unknown (fixed/moving) targets resorting to surface vehicles (called trackers) equipped with sensors capable of measuring their distances to the targets. In this setup, the surface sensor nodes should be placed according to some optimality criterion aimed at maximizing the information available for target tracking. In addition, the number of sensor nodes should be kept to a minimum in order to avoid the use of a complex and expensive network of vehicles that must be positioned and controlled in a coordinated manner. Motivated by these considerations, in this paper we study the problem of multiple target localization using two trackers and present a constructive method to generate a family of optimal waypoints for the trackers. The use of two surface sensors is motivated by the fact that a single surface sensor does not provide enough positioning accuracy for multiple target localization simultaneously. For two and three targets, we provide a family of analytical solutions for optimal sensor node placements. Further, the proposed solutions can be extended to more than three targets under some well-defined constraints on the target configuration. The optimal sensor positions are derived by maximizing the determinants of appropriately defined Fisher information matrices associated with each of the targets. It is shown that the optimal sensor configuration thus obtained lends itself to an interesting and useful geometrical interpretation. Simulation examples illustrate the results derived.

This paper presents a method for optimal trajectory planning with applications to drone cinematography. Aerial cinematography with drones is growing fast due to their maneuverability and ability to create unique visual effects. However, planning optimal drone trajectories and camera movements is still a major challenge to autonomous aerial filming. The trajectories must meet the objectives on aesthetic quality of the videos while satisfying several constraints imposed by drone dynamics, gimbal mechanical limits and surrounding obstacles. In this paper, we propose a novel formulation of the problem by decoupling the gimbal and the drone control systems. The problem is formulated as an optimization problem taking into account the gimbal rotation limits and collision avoidance constraints as well as camera angle driven objective functions to ensure feasible and smooth drone trajectories that generate visually pleasing videos. We evaluate the efficacy of our method through simulations and real-world experiments in an outdoor environment.

Multirotor unmanned aerial vehicles (UAVs) have experienced a very fast-paced technological development over the past years. Flight control systems have evolved from simple stability augmentation systems, barely enabling an external pilot to remotely fly a multirotor UAV, to full-fledged command augmentation systems, opening up the possibilities of autonomous operations of multirotors. Due to their small size, low cost, and high agility, multirotors draw a plethora of applications, including multiple vehicles operations, where the vehicles cooperate and jointly execute a mission, in constrained complex environments such as crowd monitoring and utility line inspection.

This paper addresses the problem of optimal acoustic sensor placement for underwater target localization in 3-D using range measurements only. By adopting an estimation theoretical framework, the optimal geometric sensor formation that will yield the best achievable performance in terms of target positioning accuracy is computed by maximizing the determinant of an appropriately defined Fisher information matrix (FIM). For mathematical tractability, it is assumed that the measurements of the ranges between the target and a set of acoustic sensors are corrupted with white Gaussian noise. For the sake of completeness, an explicit analytical result for a generic $n$ -sensor network is first obtained for the case when there is no uncertainty in the prior knowledge about the target position. The result is then extended to the practical case where the target is known to lie inside a region of uncertainty. The optimal sensor configuration thus obtained lends itself to an interesting and useful geometrical interpretation. In addition, the “spreading” of the configuration is shown to depend on the number of range measurements, target depth, and the probability distribution function that characterizes the prior knowledge about the target position. Results are also obtained for the problem of optimal sensor placement with constraints, namely, by considering that the sensors can be either located at the sea surface or distributed between the surface and the seabed. The connection between 2-D and 3-D scenarios is clarified. Simulation examples illustrate the key results derived.

Summary The work described in this paper is motivated by the need to develop efficient and robust estimation filters with application to terrain-aided navigation of underwater robotic vehicles. One of the main problems addressed is the development of navigation particle filters that can deal with the scarcity of landmarks and the terrain ambiguity that characterize vast regions of the ocean floor. As a contribution to solve this problem, the paper proposes three novel particle filter algorithms and assesses their estimation efficiency and robustness to non-informative measurements using two well-known benchmarking tests. The performance of the new filters in these tests demonstrates their potential to solve a class of nonlinear problems that include, but are not limited to, the type of underwater navigation problem that motivated the present work. Our study concludes by examining the performance of the filters in terms of determining the position and velocity of an autonomous underwater vehicle in the presence of unknown ocean currents. When applied to terrain-aided navigation, the novel particle filter formulations formulations mitigate filter divergence issues frequently caused by terrain symmetries and are more robust than other well-known versions when used in scenarios with poor terrain information. The theoretical developments presented and the results obtained in simulations are validated using real data acquired during tests with an autonomous marine robot. Copyright © 2016 John Wiley & Sons, Ltd.

We propose a numerical algorithm for multiple-vehicle motion planning that explicitly takes into account the vehicle dynamics, temporal and spatial specifications, and energy-related requirements. As a motivating example, we consider the case where a group of vehicles is tasked to reach a number of target points at the same time (simultaneous arrival problem) without colliding among themselves and with obstacles, subject to the requirement that the overall energy required for vehicle motion be minimized. With the theoretical setup adopted, the vehicle dynamics are explicitly taken into account at the planning level. This paper formulates the problem of multiple-vehicle motion planning in a rigorous mathematical setting, describes the optimization algorithm used to solve it, and discusses the key implementation details. The efficacy of the method is illustrated through numerical examples for the simultaneous arrival problem. The initial guess to start the optimization procedure is obtained from simple geometrical considerations, e.g., by joining the desired initial and final positions of the vehicles via straight lines. Even though the initial trajectories thus obtained may result in intervehicle and vehicle/obstacle collisions, we show that the optimization procedure that we employ in this paper will generate collision-free trajectories that also minimize the overall energy spent by each vehicle and meet the required temporal and spatial constraints. The method developed applies to a very general class of vehicles; however, for clarity of exposition, we adopt as an illustrative example the case of wheeled robots.

In the classical set-up adopted for marine geotechnical surveys, one or more acoustic sources carried by a vessel emit signals that penetrate the seafioor, reflect or refract off geological features, and travel back to multiple acoustic receivers, or hydrophones, placed along cables (streamers) towed by the same vessel. Processing the data obtained by the hydrophones yields information about the physical properties of the Earth’s crust. In this set-up, the acoustic sources and receivers are coupled and the geometry of the latter is fixed. The EC WiMUST project aims to contribute to the development of a new breed of reflection seismology systems whereby the source and the receivers are physically decoupled and free to change their spatial configurations. The project puts forward a novel concept where shorter streamers are towed by autonomous marine vehicles (AMVs) that are required to maintain a possibly time-varying formation. The paper describes the first steps taken by 1ST, in cooperation with project partners, towards the development of the networked navigation and control systems of the WiMUST vehicles. We first address the problem of modeling a coupled streamer-vehicle system and propose a solution based on Kane’s method to obtain a dynamic simulation model. A brief description of the on-going work on model parameter identification is given. We then focus on the cooperative navigation problem and propose a simplified version of a nonlinear least squares approach previously described in the literature. Finally, we address the problem of cooperative control of a fleet of streamer-vehicle systems. We give an overview of cooperative path-following and target/trajectory tracking techniques and discuss possible adaptations to align them with the technical requirements imposed by the WiMUST concept. Preliminary simulation and experimental results are shown.

The paper addresses the problems of range-based marine vehicle positioning and target localization. Vehicle positioning aims to estimate the positions of one or more vehicles from a sequence of range measurements to fixed or moving acoustic beacons with known locations. In this context, the vehicles must execute sufficiently exciting maneuvers so as to maximize the range-based information available for multiple vehicle positioning. Using an estimation theoretical setting, the vehicle trajectories are computed by maximizing the determinant of a suitably defined Fisher information matrix (FIM), subject to inter-vehicle collision avoidance and vehicle maneuvering constraints. A numerical solution is proposed for the general case. Analytical solutions are obtained in the case of one vehicle and one beacon, when the latter undergoes trajectories that are straight lines, pieces of arcs, or a combination thereof. The theoretical analysis is complemented with practical experiments that focus on the dual problem of underwater target localization. The objective is to estimate the position of a moving underwater target by using range measurements between the target and a vehicle, called a tracker, undergoing a trajectory that can be measured on-line. The experimental set-up includes a surface and an autonomous underwater vehicle of the MEDUSA*-class playing the roles of tracker and target, respectively. In the methodology adopted for system implementation the tracker runs three key algorithms simultaneously, over a sliding time window: i) tracker motion planning, ii) tracker motion control, and iii) target motion estimation based on range data acquired on-line.

This paper describes the work developed towards the implementation of magnetic navigation (MAGNAV) methods for small, affordable underwater robotic vehicles. MAGNAV constitutes a particular implementation of a broader class of methods designated as geophysical navigation, which encompasses the already classical terrain-aided, or terrain-referenced, navigation approach. Relying on prior work by the authors, the paper proposes a particle filter navigation algorithm which may be combined with other position estimation methods to increase the robustness of the estimation process. The results of a series of tests performed in the water with a marine robotic vehicle in order to assess the impact of different sensor-vehicle configurations on the quality of the magnetic data used in MAGNAV are reported. The magnetic navigation solution proposed is validated in simulated trials using real magnetic and navigation data acquired with an autonomous marine vehicle in real trials using standard navigation sensors and an affordable total field magnetometer. The results obtained illustrate the high potential of the approach for geophysical navigation of autonomous underwater vehicles.

"CADDY - Cognitive Autonomous Diving Buddy" is an FP7 project that that is devoted to developing a cognitive underwater robotic system that will help divers during their activities in this hazardous environment. The envisioned resulting system will play a threefold role similar to those that a human buddy diver should have: buddy "observer", buddy "slave", and buddy "guide". During the second year of the project, validation trials were organized in Croatia with the purpose of testing all developed algorithms that will enable the three roles of the CADDY system. The trials were structured in five experiments. This paper is devoted to providing a concise overview of the conducted experiments and major results.

This paper presents a 2D B-spline mapping framework for representing unstructured environments in a compact manner. While occupancy-grid and landmark-based maps have been successfully employed by the robotics community in indoor scenarios, outdoor long-term autonomous operations require a more compact representation of the environment. This work tackles this problem by interpolating the data of a high frequency sensor using B-spline curves. Compared to lines and circles, splines are more powerful in the sense that they allow for the description of more complex shapes in the scene. In this work, spline curves are continuously tracked and aligned across multiple sensor readings using lightweight methods, making the proposed framework suitable for robot navigation in outdoor missions. In particular, a Simultaneous Localization and Mapping (SLAM) algorithm specifically tailored for B-spline maps is presented here. The efficacy of the proposed framework is demonstrated by Software-in-the-Loop (SiL) simulations in different scenarios.

Spawned by fast paced progress in marine science and technology, the past two decades have witnessed growing interest in ocean exploration and exploitation for scientific and commercial purposes, the development of technological products for the maritime and offshore industries, and a host of other activities in which the marine environment takes center stage. In this context, marine robotics has steadily emerged as a key enabling technology for the execution of increasingly complex and challenging missions at sea. Intensive research and development in this field have led to major advances and shown unequivocally the effectiveness and reliability of marine robotics solutions in several domains. This progress goes hand in hand with the availability of increasingly sophisticated acoustic networks for multiple, cooperative missions involving surface and underwater robots. At the root of this trend is the fruitful dialogue between robotic systems developers and end-users with the capacity to convert general mission objectives into functional and technical specifications that serve as application-driven requirements for engineering development. The result is the tremendous progress observed in the consolidated methodologies and procedures adopted and the consequent impact on science, industry, and the society at large. In spite of the progress in the area, however many challenges must still be faced and novel applications will continue to set further requirements for future generations of marine robots and their enabling systems. The time is therefore appropriate to overview recent trends in the field of marine robotics and assess their impact on several important application domains. With these objectives in mind, in the present paper we highlight key technological achievements in the field, analyze some of the shortcomings encountered, and indicate specific issues that warrant further research and development effort. To this end, we review a number of highly representative projects in the field, with due account for the theoretical frameworks upon which technological developments build upon. Finally, the paper concludes with an outlook on the future of marine robotics, both from a theoretical and practical standpoint, and describes recently initiated projects that hold promise for the development of advanced tools and systems for ocean exploration and exploitation. (C) 2018 Elsevier Ltd. All rights reserved.

This paper addresses the problem of time-coordination of a team of cooperating multirotor unmanned aerial vehicles that exchange information over a supporting time-varying network. A distributed control law is developed to ensure that the vehicles meet the desired temporal assignments of the mission, while flying along predefined collision-free paths, even in the presence of faulty communication networks, temporary link losses, and switching topologies. In this paper, the coordination task is solved by reaching consensus on a suitably defined coordination state. Conditions are derived under which the coordination errors converge to a neighborhood of zero. Simulation and flight test results are presented to validate the theoretical findings.

This paper addresses the design and implementation of terrain-aided navigation (TAN) methods for small autonomous underwater vehicles (AUVs) that rely on standard navigation sensors and dispense with the need for dedicated sensors for terrain data acquisition. The research described focuses on the problem of TAN implementation in underwater scenarios characterized by smooth sea-bottom topography and very shallow water, where the terrain information available for navigation is scarce. The navigation algorithms and the data fusion methods whose tests are documented in the paper build upon and expand prior theoretical work published by the authors; the TAN solutions adopted exploit the terrain information and the navigation data acquired with an inexpensive Doppler velocity logger (DVL) and a standard motion reference unit, respectively. The position estimation methods analyzed include a bi-dimensional particle filter (PF) and a four-dimensional Rao-Blackwellized PF that was designed to estimate the unknown Doppler velocity measurement biases responsible for the unbound localization errors typically observed in dead-recknoning navigation. The positioning accuracy achieved with these filters is compared with the output of a novel method, also proposed in the paper, that mechanizes a complementary-like filter designed to fuse the output of a TAN estimator with the velocity measurements provided by a DVL. Experimental results obtained during field tests with an autonomous marine vehicle are reported and analyzed.

The MORPH project (FP 7, 2012-2016) advances a novel concept of an underwater robotic system composed of a number of spatially separated mobile robot-modules, carrying complementary resources. Instead of being physically coupled, the modules are connected via communication links that allow a limited flow of information among them. Without rigid links, the so called Morph Supra-Vehicle can reconfigure itself and adapt in response to the shape of the terrain, including walls with negative slope. The MORPH concept requires new concepts in a number of technological fields. Examples are adaptive sensor placement for perception and navigation or environmental modeling in complex environments. As the project enters its final year the basic developments have been achieved. It is still a huge effort to create a system out of components which can be perceived as a supra-vehicle. This paper focuses on a presentation of the current state.

Based on a companion publication that introduces the theoretical foundations, this paper describes the implemented architecture for formation control of the upper segment vehicles of the MORPH project. We highlight the necessary modifications and additional elements, mainly in terms of control and estimation, to allow for the implementation in real vehicles. We illustrate the performance of the system with results from sea trials in Lisbon and in the Azores, with a number of heterogeneous vehicles from multiple partners involved in the project.

We address the subject of formation control of underwater vehicles, using either inter-vehicle relative position measurements or range-only measurements. The work is motivated by the MORPH project, aiming at the use of formations of vehicles with complementary capabilities to map the underwater environment in complex 3D environments. The main problem studied is that of driving a vehicle (follower) to an appropriately defined position with respect to another vehicle (leader), which moves along a trajectory that is unknown to the follower. This control task is divided into two steps. Firstly, a trajectory-tracking controller is designed so that a follower vehicle can track a specified virtual target. Secondly, we design path-generators that yield the position and velocity of the virtual target to be tracked, for both the relative position measurements and the range-only measurements scenarios. These path-generation strategies take into account desirable formation behaviour and typical maneuver geometries. Applications to the MORPH project are presented. Finally, results of simulations are shown.

This paper described the basic concept behind the second and final validation trials of the Cognitive Autonomous Diving Buddy (CADDY) system. The CADDY system is composed of three components: autonomous surface vehicle (ASV), an autonomous underwater vehicle (AUV) named BUDDY, and a diver. CADDY aims to establish an innovative setup between a diver and companion autonomous robots (underwater and surface) that exhibit cognitive behaviour by adapting to diver's physical state, and actions, thereby improving overall diving experience by assisting the diver. Although certain problems were encountered during trials, the collected data and experience were valuable to identify potential improvements. Most importantly, divers felt safe and comfortable working and interacting with a robotic BUDDY thus achieving the primary goal.

This paper describes a procedure to design robust controllers for Dynamic Positioning (DP) of ships and offshore rigs subjected to the influence of sea waves, currents, and wind loads using H∞ and mixed-μ techniques. The proposed method will increase operational weather window and robustness of the DP vessel and associated DP system. To this effect, practical assumptions are exploited in order to obtain a linear design model with parametric uncertainties describing the dynamics of the vessel. Appropriate frequency weighting functions are selected to capture the required performance specifications at the controller design phase. The proposed model and weighting functions are then used to design robust controllers. The problem of wave filtering is also addressed during the process of modelling and controller design. The key contribution of the paper is threefold: (i) it affords system designers a new method to efficiently obtain linearized design models that fit naturally in the framework of H∞ control theory, (ii) it describes, in a systematic manner, the different steps involved in the controller design process for DP systems operating under different sea conditions, and (iii) it contains the details of simulations and results of experimental model tests in a towing tank equipped with a hydraulic wave maker. This is a submitted manuscript of an article published by Elsevier Ltd in Ocean Engineering, 6 December 2016.

This paper addresses the observability properties of a 3D autonomous underwater vehicle (AUV) model in the presence of ocean currents, under the assumption that the vehicle can only measure its distance to a fixed transponder using an acoustic ranging device. In the set-up adopted, the AUV may undergo a wide range of maneuvers that are usually described as trimming trajectories. The latter are of paramount importance in flight dynamics and can be completely parametrized by three variables: i) linear body speed v, ii) flight-path angle γ, and iii) yaw rate ψ. We assume that v > 0, γ, and ψ are constant but otherwise arbitrary (within the constraints of the vehicle capabilities) and examine the observability of the resulting system with the output (measured) variable described above. We adopt weaker definitions of observability that are akin to those proposed by Herman and Krener (Hermann and Krener, 1977) but reflect the fact that we consider specific kinds of maneuvers in 3D. We show that in the presence of known constant ocean currents the 3D kinematic model of the AUV that corresponds to trimming trajectories with nonzero flight path angle and yaw rate is observable. In case the latter conditions fail, we give a complete characterization of the sets of states that are indistinguishable from a given initial state. We further show that in the case of unknown constant ocean currents the model is locally weakly observable for yaw rate different from zero but fails to be locally weakly observable for zero yaw rate. In both the cases we give a complete characterization of the sets of states that are indistinguishable from a given initial state.

This paper addresses the problem of keeping an autonomous marine vehicle in a moving triangular formation by regulating its position with respect to two leader vehicles. The follower vehicle has no prior knowledge of the path described by the leaders but has access to their heading angle and is able to measure inter-vehicle ranges. It is assumed that the distance between the leaders is constant and known. A control strategy is adopted that generates speed and heading commands so as to drive suitably defined along track and cross track errors to zero. The commands are used as input to local inner loops for yaw and speed control. The paper describes the algorithms derived for range-based control and assesses their performance in simulations using realistic models of the vehicles involved. Tests with three autonomous marine vehicles equipped with acoustic modems and ranging devices allow for the evaluation of the performance of the algorithms in a real-world situation.

The needing to explore the depths of the sea is currently increasing. However, human exploration can be compromised due to dangers that divers face at great depths. The Autonomous Underwater Vehicle (AUV) has allowed underwater research to make a great stride and avoid human accidents. In such situation, designing an optimized AUV's hull is essential. To maximize periods of operation, AUV's hull must be outfitted to withstand harsh environmental conditions and minimize hydrodynamic drag. In this paper, a variant of torpedo body is proposed, with four Degrees Of Freedom (DoF) and capable of exploring the Caribbean Sea at great depths. Computational Fluid Dynamics (CFD) analysis and empirical methods are used to investigate the hydrodynamic resistance of the designed hull and estimate the drag, employing an optimization process and proving the effectiveness of the optimization algorithm with the profile efficiency analysis. The results demonstrate that CFD optimization methods have an influence on drag estimation. Furthermore, this paper shows that main factors impact the AUV design are the pressure on its body and the hydrodynamic drag. With results obtained based on CFD and empirical estimations, it was possible to achieve optimal parameters concerning the protection of internal hardware, the buoyancy of the vehicle and minimum drag to reach optimal energy consumption. Finally, the variation made to the typical torpedo body does not increase the drag of the vehicle.

The paper addresses observability issues related to the general problem of single and multiple Autonomous Underwater Vehicle (AUV) localization using only range measurements. While an AUV is submerged, localization devices, such as Global Navigation Satellite Systems, are ineffective, due to the attenuation of electromagnetic waves. AUV localization based on dead reckoning techniques and the use of affordable motion sensor units is also not practical, due to divergence caused by sensor bias and drift. For these reasons, localization systems often build on trilateration algorithms that rely on the measurements of the ranges between an AUV and a set of fixed transponders using acoustic devices. Still, such solutions are often expensive, require cumbersome calibration procedures and only allow for AUV localization in an area that is defined by the geometrical arrangement of the transponders. A viable alternative for AUV localization that has recently come to the fore exploits the use of complementary information on the distance from the AUV to a single transponder, together with information provided by on-board resident motion sensors, such as, for example, depth, velocity and acceleration measurements. This concept can be extended to address the problem of relative localization between two AUVs equipped with acoustic sensors for inter-vehicle range measurements. Motivated by these developments, in this paper, we show that both the problems of absolute localization of a single vehicle and the relative localization of multiple vehicles can be treated using the same mathematical framework, and tailoring concepts of observability derived for nonlinear systems, we analyze how the performance in localization depends on the types of motion imparted to the AUVs. For this effect, we propose a well-defined observability metric and validate its usefulness, both in simulation and by carrying out experimental tests with a real marine vehicle during which the performance of an Extended Kalman Filter state observer is shown to depend on the types of motion imparted to the vehicle.

In this paper, we address the problem of determining the optimal geometric configuration of an acoustic sensor network that will maximize the angle-related information available for underwater target positioning. In the set-up adopted, a set of autonomous vehicles carries a network of acoustic units that measure the elevation and azimuth angles between a target and each of the receivers on board the vehicles. It is assumed that the angle measurements are corrupted by white Gaussian noise, the variance of which is distance-dependent. Using tools from estimation theory, the problem is converted into that of minimizing, by proper choice of the sensor positions, the trace of the inverse of the Fisher Information Matrix (also called the Cramer-Rao Bound matrix) to determine the sensor configuration that yields the minimum possible covariance of any unbiased target estimator. It is shown that the optimal configuration of the sensors depends explicitly on the intensity of the measurement noise, the constraints imposed on the sensor configuration, the target depth and the probabilistic distribution that defines the prior uncertainty in the target position. Simulation examples illustrate the key results derived.

This paper addresses the problem of optimal sensor placement for acoustic range-based underwater target positioning. In particular, we focus on the experimental set-up whereby target positioning is performed by measuring the ranges between the underwater target and a number of surface units equipped with acoustic ranging devices and GPS. With the objective of affording the reader a concise overview of the main theoretical challenges involved, this paper starts with a survey of previous work done in the area, including that of the authors. By casting the problem at hand in the form of a classical estimation problem we describe and solve the equivalent mathematical problem of maximizing the determinant of a conveniently defined Fisher Information Matrix (FIM). The latter is related to the Cramer-Rao Bound, which equals the smallest possible position estimation error variance that can possibly be achieved with any unbiased estimator. To further clarify the presentation, the details of Monte Carlo simulations in 2D and 3D with a selected target positioning algorithm are included to confirm the theoretical results numerically.

We propose a four-quadrant propeller model suitable for energy-efficient motion planning of autonomous marine vehicles. The model can be used to capture the main features of experimental thrust and torque curves by using a small number of parameters. We explore the connection between the propeller thrust, torque, and efficiency curves and the lift and drag curves of the propeller blades. The model originates from a well-known four-quadrant model, based on a sinusoidal approximation of the propeller curves, nontrivially modified in this paper to account for the typical drop off in the efficiency curve in correspondence to thrust inversion. Connections with the standard first-quadrant open-water model are drawn.

This paper proposes novel methods with the potential to improve the performance of navigation and tracking systems in underwater environments. The work relies on well-established methods of potential field inversion and introduces a new analytic formulation designed to stabilize the solution of the inverse problem in real-time applications. The navigation method proposed exploits the terrain information associated with geomagnetic field anomalies, without the need of a priori maps. The procedure can also be applied to track a moving vehicle based on its associated disturbance of the environmental magnetic field. We envision the integration of theses methods in terrain-aided navigation systems, simultaneous localization and mapping algorithms, and tracking applications.

The availability of reliable underwater positioning systems to localize one or more vehicles simultaneously based on information received on-board a support ship or an autonomous surface vessel is key to the operation of some classes of AUVs. Furthermore, there is considerable interest in reducing the number of sensors involved in acoustic navigation/positioning systems to reduce the costs involved and the time consumed in the deployment, callibration, and recovery phases. Motivated by these considerations, in this paper we address the problem of single underwater target positioning based on measurements of the ranges between the target and a moving sensor at the sea surface, obtained via acoustic ranging devices. In particular, and speaking in loose terms, we are interested in determining the optimal geometric trajectory of the surface sensor that will, in a well defined sense, maximize the range-related information available for underwater target positioning. To this effect, an appropriate Fisher Information Matrix is defined and its determinant is maximized to yield the sensor trajectory that maximizes the accuracy of the target position estimate that can possibly be obtained with any unbiased estimator. It is shown that the optimal trajectory depends on the relative velocity of the sensor, the sampling time between measurements, and the number of measurements acquired for the FIM computation. Simulation examples illustrate the key results derived.

We introduce an event driven communication logic for decentralized control of a network of robotic vehicles (agents). The strategy proposed is robust to packet losses and drives the vehicles to predefined paths while holding a desired geometric formation pattern. To this effect, the paper extends an existing cooperative path following framework to consider the practical case where communications among the vehicles occur at discrete instants, instead of continuously. The introduced communication logic takes into account the topology of the communication network, the fact that communications are discrete, and the cost of exchanging information. We also address explicitly communication losses and bounded delays. Conditions are derived under which the overall closed loop system is input-to-state practically stable. The communication logic is applied to a cooperative path-following control system of multiple underactuated autonomous marine robots. Simulation results are presented and discussed.

Autonomous vehicles are becoming an essential tool in a wide range of environmental applications that include ambient data acquisition, remote sensing, and mapping of the spatial extent of pollutant spills. Among these applications, pollution source localization has drawn increasing interest due to its scientific and commercial interest and the emergence of a new breed of robotic vehicles capable of performing demanding tasks in harsh environments without human supervision. In this task, the aim is to find the location of a region that is the source of a given substance of interest (e.g. a chemical pollutant at sea or a gas leakage in air) using a group of cooperative autonomous vehicles. Motivated by fast paced advances in this challenging area, this paper surveys recent advances in searching techniques that are at the core of environmental monitoring strategies using autonomous vehicles.

The large number of potential applications for robotic odor source localization has motivated the development of a variety of plume tracking algorithms, the majority of which work in restricted two-dimensional scenarios. In this paper, we introduce a distributed algorithm for 3-D plume tracking using a system of ground and aerial robots in formation. We propose an algorithm that takes advantage of spatially distributed measurements to track the plume in 3-D and lead the robots to the source by integrating three behaviors - upwind movement, plume centering, and Laplacian feedback formation control. We evaluate this strategy in simulation and with real robots in a wind tunnel. For a source close to the ground, results show that a team of robots running our algorithm reaches the source with low lateral error while also tracing the horizontal and vertical plume shape.

Robotic chemical plume tracing is a growing area of research, with envisioned real-world applications including pollution tracking, search and rescue, and ecosystem identification. However, following a chemical signal in the water is not an easy task due to the nature of chemical transport and to limitations in sensing and communication. In this paper, we propose an approach for near-surface waterborne plume tracing using a combined team of autonomous surface and underwater vehicles. All vehicles are equipped with appropriate chemical sensors and acoustic modems. The team moves in a triangular formation, while using the flow direction and the samples obtained to steer the group along the plume. Leader vehicles at the surface implement a formation controller based on Laplacian feedback while the underwater vehicle performs acoustic ranging to the leaders. The solution was evaluated using a CFD simulation of a freshwater plume and a calibrated dynamic model of the MEDUSA autonomous marine vehicles. The group is able to move in a stable formation, sample the salinity, and trace the plume to its source.

Wireless optical communications are emerging as a viable solution for high-speed data transmission over short ranges in the ocean, complementing mainstream acoustic communication systems that operate over much longer ranges, but at lower data rates. The current drive to develop cooperative autonomous vehicular systems to carry out surveying and other complex missions in the ocean critically depends on the existence of such communication links to share sensory and coordination information. This paper presents a compact, low power consumption, cost-efficient, and lightweight optical modem designed for fast data transmission between MEDUSA underwater vehicles at ranges on the order of 10 m. The transmitter uses LEDs for ON-OFF keying, while the receiver front-end adopts a transimpedance architecture with a photodiode detector. This simplistic transmission and reception technique reduces the overall design and hardware complexities compared to, e.g., laser diodes and photomultiplier tubes. The LEDs are arranged in a circular array, with a photodiode at the centre to enable half-duplex operation. These modems are designed to achieve data rates of 20–200 kb/s over short-range, line-of-sight, configurations. A transparent casing is customised to fit the Medusa vehicles, with proper alignment for inter-vehicle communication when they move in formation.

The Widely scalable Mobile Underwater Sonar Technology (WiMUST) project aims at developing a system of cooperative Autonomous Underwater Vehicles (AUVs) for geotechnical surveying and geophysical exploration. The paper reports about the first year activities and it gives an overview of the main objectives and methods. Results relative to distributed sensor array, cooperative control, mission planning, communications and preliminary experiments are summarized.

This paper describes a new class of autonomous marine vehicles named Medusa and highlights their role in a number of EU projects addressing multiple vehicle scenarios. The MEDUSA vehicles, with surface and diving versions, were designed and built at the Institute for Systems and Robotics, IST, Univ. de Lisboa, Portugal as a result of an effort aimed at affording researchers and practitioners of marine robotics tools to: i) assess the efficacy of cooperative motion control and navigation algorithms and ii) seamlessly execute scientific and commercial missions with multiple robots at sea. We first define the problem of designing the MEDUSA-class of vehicles by describing the desired functional requirements that motivated their development and then present our solution. Mechanical and electrical design considerations that relate to the requirements are explained, and the software architecture is described. This includes a brief overview of the navigation system, the main lower-level control loops which other features can build upon, and some of the higher-level algorithms for multiple-vehicle cooperative missions. We also illustrate the functionality of the mission control system, a dedicated software suite that allows operators to seamlessly program and follow the state of execution of cooperative missions involving multiple vehicles, possibly running different operations or missions in parallel. Finally, we summarize the participation of IST and the MEDUSA vehicles in a number of representative EC-funded Marine Robotics-related projects.

Safety is of particular interest when performing research related to human-robot interaction in unpredictable and hazardous underwater environment. Special attention is devoted to safety requirements within FP7 project “CADDY — Cognitive Autonomous Diving Buddy” in order to reduce hazards during experiments, since divers relying on technology for life support are exposed to additional risk of trauma as a consequence of impact with a marine vehicle. This paper focuses on the risk assessment of human-robot interaction in the underwater environment within the scope of CADDY project. Each vehicle comprising the CADDY fleet is analyzed for a number of risks, and an overall assessment is provided showing the appropriateness of selected vehicles for the application. Also, the acoustic communication scheme used in the project is described, as a means of efficient and robust navigation data exchange for the purpose of minimizing the risk of trauma due to unwanted contact between the vehicles and the diver.

Odor plume tracing is a challenging robotics application, made difficult by the combination of the patchy characteristics of odor distribution and the slow response of the available sensors. This work proposes a graph-based formation control algorithm to coordinate a group of small robots equipped with odor sensors, with the goal of tracing an odor plume to its source. This approach makes it possible to organize the robots in arbitrary and evolving formation shapes with the aim of improving tracing performance. The algorithm was evaluated in a high-fidelity submicroscopic simulator, using different formations and achieving quick convergence and negligible distance overhead in laminar wind flows.

The paper presents acoustic navigation aiding and path following results from demonstration experiments in Lisbon, Portugal. The demonstration was carried out as part of the second year CADDY Review Meeting. The paper presents the concept of the underwater leader, which entails an underwater vehicle, performing a desired task, and a surface vehicle maintaining relative position to improve navigation aiding through acoustics. The surface controller, utilizing the artificial potential field method, is proposed as an alternative to classical tracking and positioning controllers. Even in presence of multiple agents, the controller offers a more "relaxed" tracking and positioning algorithm for autonomous vehicles. The acoustic data-exchange scheme, required to achieve situation awareness of all agents, is described to specify cycle times and delays that have to be taken into account during state estimation. Finally, results from public demonstrations are presented and analyzed both from the surface and underwater perspectives.

Worldwide, there has been growing interest in the use of autonomous vehicles to execute missions of increasing complexity without constant supervision of human operators. A key enabling element for the execution of such missions is the availability of advanced systems for motion control of autonomous vehicles. Usually, the problems of motion control for a single autonomous vehicle are roughly classified into three groups:.

This paper addresses the problem of reaching consensus among a group of agents that evolve in continuous-time and exchange information at discrete-time instants, referred to as update times. Each agent has its own sequence of update times and therefore the agents are not required to keep synchronized clocks among them. At each update time, an agent receives from a subset of the other agents their state, as determined by the communication topology that may be time-varying. Due to transmission delays, the information may be received by an agent with latency. In our proposed solution, the state of each agent is augmented with an extra state variable that is updated instantaneously at update times. Between updates, the original state and the extra variable both evolve in a continuous fashion. It is shown that consensus is reached asymptotically by reducing the original problem involving continuous-time variables and asynchronous communications to a discrete-time equivalent and using known results for discrete-time consensus.

There is widespread interest in the deployment of fleets of marine robots with the potential to roam the oceans freely and collect data at an unprecedented scale. This calls for the development of efficient algorithms for multiple vehicle motion planning that can take directly into account the capabilities of each vehicle and environmental conditions and lend themselves to seamless integration with control and navigation systems. The paper describes advances towards the development of a new breed of motion planning systems that address explicitly inter-vehicle collision avoidance, together with a number of criteria that may include simultaneous times of arrival at assigned target points, energy minimization, and acoustic communication constraints. The theoretical framework adopted is rooted in the so-called Projection Operator Approach that borrows from optimization and dynamical systems theory. Simulations with full dynamic vehicle models illustrate the potential of the methods developed.

This paper addresses the challenging problem of achieving truly autonomous long-range navigation of underwater vehicles relying on affordable navigation sensors. Terrain-aided navigation (TAN) is a methodology that holds potential to solve this problem by dispensing with the need to use high-grade, inertial navigation sensors and the deployment and calibration of acoustic beacons. To implement TAN without incurring the additional cost of expensive dedicated sensors, we propose the utilization of a Doppler velocity logger (DVL) which is an equipment of widespread utilization in oceanography and also a standard instrument in underwater navigation. We avail ourselves of a less exploited characteristic of DVL sensors that consists in the ability to acquire, simultaneously with the velocity data, a set of accurate range measurements relatively to a reflective interface. The combination of these sensing capacities enables Doppler units to be used not only in dead-recknoning navigation but also in terrain-based localization of underwater vehicles. The main contribution of the paper is the design of a complementary filter (CF) for fusion of TAN estimates with DVL measurements. The CF approach is motivated by the need to reduce the short-term variability of position estimates that is typically observed in conventional TAN. The solution proposed is analysed in comparison with a well-known Rao-Blackwellized particle filter set-up which is shown to implement a data fusion filter designed in a stochastic estimation framework. The results obtained in Monte Carlo simulations performed with real bathymetric data evidence the superior performance of the complementary filter approach in terms of position estimation accuracy and long term output signal stability.

This paper addresses the problem of maintaining an autonomous robotic vehicle in a moving triangular formation by regulating its position with respect to two leader vehicles. The robotic vehicle has no a priori knowledge of the path described by the leaders and its goal is to follow them by constantly regulating the inter-vehicle distances to a desired fixed value, using range-only measurements. To solve this station keeping problem, we propose a control strategy that estimates the formation speed and heading from the ranges obtained to the two leading vehicles, and uses simple feedback laws for speed and heading commands to drive suitably defined common and differential errors to zero. For straight-line motion, we provide guaranteed conditions under which the proposed control strategy achieves local convergence of the distance errors to zero. We also indicate how our design procedure can be extended to full dynamic models of marine robotic vehicles equipped with inner loops for yaw and speed control. Simulation results using realistic models are described and discussed.

This paper describes a procedure to design robust controllers for Dynamic Positioning (DP) of ships and offshore rigs subjected to the influence of sea waves, currents, and wind loads using ℋ ∞ and mixed-μ techniques. To this effect, practical assumptions are exploited in order to obtain a linear design model with parametric uncertainties describing the dynamics of the vessel. Appropriate frequency weighting functions are selected to capture the required performance specifications at the controller design phase. The proposed model and weighting functions are then used to design robust controllers. The problem of wave filtering is also addressed during the process of modeling and controller design. The key contribution of the paper is twofold: i) it affords system designers a new method to efficiently obtain linearized design models that fit naturally in the framework of ℋ ∞ control theory, and ii) it describes, in a systematic manner, the different steps involved in the controller design process. Part II in a companion paper contains the details of simulations and results of experimental model tests in a towing tank equipped with a hydraulic wave maker.

This paper is a follow-up of a companion paper by Hassani et al. (2012b) on a control design methodology for Dynamic Positioning (DP) of marine vessels and offshore rigs subjected to the influence of sea waves, currents, and wind loads using mixed-μ synthesis. The present paper describes the results of a design exercise in which robust controllers were designed for a representative vessel. Its main focus is on the discussion of the results of numerical simulations and experimental model-testing of a set of robust DP controllers operating under different sea conditions: calm, moderate, high, and extreme seas. The robust DP controllers were first evaluated in a high fidelity nonlinear DP simulator, illustrating the efficiency of the design. To bridge the gap between theory and practice, the results were experimentally verified by model testing of a DP operated ship, the Cybership III, under different simulated sea conditions in a towing tank equipped with a hydraulic wave maker.

This paper describes a procedure to design multiple model adaptive controllers for Dynamic Positioning (DP) of ships and offshore rigs subjected to the influence of sea waves, currents, and wind loads. To this effect, a linear design model is obtained, based on practical assumptions, describing the dynamics of the vessel. Four Linear Quadratic Gaussian (LQG) DP controllers (with the same structure) are designed, covering the different sea conditions from calm to extreme seas. Tools from multiple model adaptive control (MMAC) theory are used to exploit the information provided by the different observers (models) in order to select the appropriate controller. Numerical simulations carried out using a high fidelity nonlinear DP simulator illustrate the efficiency of the MMAC techniques proposed. To bridge the gap between theory and practice, the results of the simulations were experimentally verified by model testing with a DP operated ship, the Cybership III, under different simulated sea conditions in a towing tank equipped with a hydraulic wave maker.