Active drifters: Towards a practical multi-robot system for ocean monitoring

Molchanov, Artem; Breitenmoser, Andreas; Sukhatme, Gaurav S.

doi:10.1109/icra.2015.7139232

Cited by 14 publications

(31 citation statements)

References 14 publications

(18 reference statements)

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“…The authors give a monitoring timeline with distinctive phases. A frequently seen approach, such as in [ 12 , 13 ], is using Lagrangian (current-following) drifters, capable of vertical movement.…”

Section: Introductionmentioning

confidence: 99%

“…Utility balances information gain, travelling costs, and localisation ability for each point [ 17 ]. In an underwater setting, there are fewer approaches, focusing mostly on specific hardware properties [ 12 , 13 , 18 ] or exploration strategies [ 19 ]. Recently, in [ 20 ], the authors used information-theoretic exploration and sampling together with ocean models to derive an exploration strategy.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Paradigm for Underwater Monitoring Using Mobile Sensor Networks

Babić

Lončar

Arbanas

et al. 2020

Sensors

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This paper presents a novel autonomous environmental monitoring methodology based on collaboration and collective decision-making among robotic agents in a heterogeneous swarm developed within the project subCULTron, tested in a realistic marine environment. The swarm serves as an underwater mobile sensor network for exploration and monitoring of large areas. Different robotic units enable outlier and fault detection, verification of measurements and recognition of environmental anomalies, and relocation of the swarm throughout the environment. The motion capabilities of the robots and the reconfigurability of the swarm are exploited to collect data and verify suspected anomalies, or detect potential sensor faults among the swarm agents. The proposed methodology was tested in an experimental setup in the field in two marine testbeds: the Lagoon of Venice, Italy, and Biograd an Moru, Croatia. Achieved experimental results described in this paper validate and show the potential of the proposed approach.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Paradigm for Underwater Monitoring Using Mobile Sensor Networks

Babić

Lončar

Arbanas

et al. 2020

Sensors

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“…The application of underactuated underwater vehicles has attracted considerable interests in ocean monitoring [1], ocean observation [2], and coral reef surveying [3], [4] since they require minimal resources in the actuation and sensing. Also, these vehicles are suitable for persistent deployment [5] in marine environments to tackle several oceanographic tasks.…”

Section: Introductionmentioning

confidence: 99%

An Underactuated Vehicle Localization Method in Marine Environments

Alam

Reis

Bobadilla

et al. 2018

OCEANS 2018 MTS/IEEE Charleston

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The underactuated vehicles are apposite for the longterm deployment and data collection in spatiotemporally varying marine environments. However, these vehicles need to estimate their positions (states) with intrinsic sensing in their long-term trajectories. In previous studies, autonomous underwater vehicles have commonly used vision and range sensors for autonomous state estimation. Inspired by the intrinsic sensing and the persistent deployment, we investigate the localization problem (state estimation) for an inexpensive and underactuated drifting vehicle called a drifter. In this paper, we present a localization method for the drifter making use of the observations of a proprioceptive sensor, i.e., compass. We create the water flow pattern within a given region from ocean model predictions, develop a stochastic motion model, and analyze the persistent water flow behavior. Given a distribution of initial deployment states of the drifter at a particular depth of the water column within the region and the water flow pattern, our method finds attractors and their transient groups at the given depth as the persistent behavior of the water flow. A most-likely localized trajectory of the drifter for a sequence of compass observations is generated based on the persistent behavior of the water flow and hidden Markov model. Our simulation results based on data from ocean model predictions substantiate good performance of our proposed localization method with a low error rate of the state estimation in the long-term trajectory of the drifter.

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“…Existing 3D current models come with significant limitations, however. As surveyed in Section 1.2, 3D current models in the literature are restricted to the output of numerical ocean models [42,130,179,182], which are too low resolution to reflect the interaction between neighbouring nodes, and land-based synthetic mobility models [35,36,119,204,205] such as random walk or random waypoint where nodes move independently of each other. In reality, nodes are advected underwater by a common flow, which can be represented by a current velocity field [37].…”

Section: Chapter 3 a Realistic 3d Depth-decaying Meandering Current Mobility Modelmentioning

confidence: 99%

“…Being an order of magnitude cheaper to fabricate, float networks have the potential to achieve similar coverage performance as much more expensive AUV networks, by also being able to move back to their initial deployment locations fully covering the RoI. Previous works have considered the problem of path planning for single [93,180,182] and widely spaced 2D arrays of floats [42,130], making this thesis the first to examine exploiting the mobility of UWSNs consisting of profiling floats for 3D coverage.…”

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confidence: 99%

Drifting 3D Underwater Wireless Sensor Networks for Pollution Monitoring

Ren¹

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<p>Increasing demands by a growing population for food and oil have resulted in synchronous rises in the past 40 years of aquaculture and offshore oil drilling. Growth in these industries has highlighted the potential crippling impacts of coastal pollution, with marine farms likely to be susceptible to damage from harmful algal blooms and oil platforms to cause oil spills, as headlined by the 2010 Deepwater Horizon incident in the Gulf of Mexico. Drifting underwater wireless sensor networks (UWSNs) represent a technology that can greatly enhance our understanding of such processes. Consisting of a swarm of untethered sensor nodes, an UWSN can be deployed over a large segment of the feature. The feature is carried through to different positions by underwater currents, the nodes, also drifting with the currents, are able to follow it and track it. To enable UWSNs, work is proceeding at multiple laboratories throughout the world on the design of localization, medium access control and routing protocols that can adapt to the problem that a drifting network topology has over short time intervals: frequent neighbour changes. However, the long-term impact that current drift has on 3D drifting UWSNs is poorly understood. Current mobility models used to generate the motion of drifting nodes in simulation do not reflect how devices in real-life will disperse in water. At present, UWSN protocol schemes are evaluated in simulations where the current mobility of nodes is generated by unrealistic land-based random waypoint and other stochastic mobility models, or coarsely resolved numerical ocean models. Recently, a physically-inspired current mobility model known as MCM has been proposed. This is only defined along the water's surface, in 2D, however, and 3D extensions of this model have been simplistic and arbitrary. The lack of realistic 3D current mobility models motivates this thesis to develop one so that the simulated evolution of UWSNs can more accurately reflect real-life. A consideration of the oceanographic data on which MCM is based is used to derive a 3D extension of the model that reflects observed features of the Gulf Stream current. The speed of the current declines with depth. This model is utilized to advect a drifting UWSN in an oil plume monitoring scenario and study the performance of two pressure routing protocols, Depth Based Routing (DBR) and HydroCast, over time. Previously, these schemes had only been validated in unrealistic stochastic and depth-invariant mobility models and their time-averaged performances were only reported. Our findings show that 3D UWSNs cannot expect to stay connected and functioning if nodes only passively drift with the currents, with results demonstrating that a fully connected network can be so dispersed after three hours that no paths to sinks exist at all. Nodes must be equipped with some form of mobility to prevent their being separated and carried out of the monitoring region. Autonomous underwater vehicles (AUVs) capable of omnidirectional motion are expensive however, and instead UWSNs consisting of pro ling floats are considered in this thesis. Floats can move up and down by adjusting their buoyancy, which also allow them to move in 3D by exploiting water layers that are flowing in different directions to proceed along a desired heading. Recently, promising results in 2D path planning and formation control of floats have been presented. However, these works consider the floats to have infinite vertical velocity whereas in reality this is around 0:3 metres per second. In this thesis, a practical node movement scheme is proposed for extending the coverage lifetime of a 3D UWSN consisting of floats. By accounting for the finite profiling velocity of floats, the scheme is able to position nodes at coverage holes with greater precision than existing 2D strategies. The scheme's performance is analysed by simulations. The results support the use of floats for achieving partial coverage, which can achieve similar levels of coverage as an AUV strategy while requiring less cost to deploy. In determining the lifetime of the network, we find that both energy and dispersion limit the lifetime of the network. Without propulsion, the nodes are carried out of and cease to cover the monitoring region. Using mobility to remain with the region, at the end of a 5 day mission duration floats have had to use up some or almost all of their battery capacity in profiling.</p>

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Active drifters: Towards a practical multi-robot system for ocean monitoring

Cited by 14 publications

References 14 publications

A Novel Paradigm for Underwater Monitoring Using Mobile Sensor Networks

A Novel Paradigm for Underwater Monitoring Using Mobile Sensor Networks

An Underactuated Vehicle Localization Method in Marine Environments

Drifting 3D Underwater Wireless Sensor Networks for Pollution Monitoring

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