Distributed allocation of mobile sensing agents in geophysical flows

Hsieh, M. Ani; Mallory, Kenneth; Forgoston, Eric; Schwartz, Ira B.

doi:10.1109/acc.2014.6859084

Cited by 10 publications

(7 citation statements)

References 18 publications

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“…This is supported by Forgoston et al's work where they showed that LCS coincide with regions in the flow field where more escape events occur [1]. As such, knowledge of LCS is important for planning energy efficient trajectories in the ocean, maintaining sensors in their desired monitoring regions [13,9,6], and enabling computationally tractable and efficient estimation and prediction of the underlying geophysical fluid dynamics.…”

Section: Introductionmentioning

confidence: 89%

Tracking Attracting Lagrangian Coherent Structures in Flows

Kularatne

Hsieh

2015

Robotics: Science and Systems XI

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This paper presents a collaborative control strategy designed to enable a team of robots to track attracting Lagrangian coherent structures (LCS) and unstable manifolds in two-dimensional flows. Tracking LCS in dynamical systems is important for many applications such as planning energy optimal paths in the ocean and predicting various physical and biological processes in the ocean. Similar to existing approaches, the proposed strategy does not require global information about the dynamics of the surrounding flow, and is based on local sensing, prediction, and correction. Different from existing approaches, the proposed strategy has the ability to track attracting LCS and unstable manifolds in real time through direct computation of the local finite time Lyapunov exponent field. The collaborative control strategy is implemented on a team of robots and the theoretical guarantees of the tracking strategy is briefly discussed. We demonstrate the tracking strategy in simulation using static and time dependent flows and experimentally validate the strategy using a team of micro autonomous surface vehicles (mASVs) in an actual fluid environment.

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Section: Introductionmentioning

confidence: 89%

Tracking Attracting Lagrangian Coherent Structures in Flows

Kularatne

Hsieh

2015

Robotics: Science and Systems XI

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“…For the latter, sensors can act as mobile agents which can move around for better sensing performance. Assuming each mobile agent has a map of the natural fluidic environment, [28] raised a distributed control policies enabling a homogeneous team of mobile sensing agents to maintain a desired spatial distribution. Reference [29] discusses coordinating a mobile sensor team, which can dynamically change their positions to optimize their coverage of the target.…”

Section: A Sensingmentioning

confidence: 99%

“…In [30], two new patrol algorithms are introduced to plan the paths of controllable floating cars to participate in traffic monitoring. Reference [29] is a study of a more general case, while the control strategy in [28] is derived from the Lagrangian coherent structures of the flow, and the patrol algorithm in [30] is closely related to the characteristics of the data reconstruction scheme. It goes without saying that there is a lot of work to do about control strategy in new environments.…”

Section: A Sensingmentioning

confidence: 99%

A comprehensive overview of cyber-physical systems: from perspective of feedback system

Guan

Yang

Chen

et al. 2016

IEEE/CAA J. Autom. Sinica

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Cyber-physical systems (CPS) are characterized by integrating cybernetic and physical processes. The theories and applications of CPS face the enormous challenges. The aim of this paper is to provide a latest understanding of this emerging multi-disciplinary methodology. First, the features of CPS are described, and the research progresses are summarized from different components in CPS, such as system modeling, information acquisition, communication, control and security. Each part is also followed by the future directions. Then some typical applications are given to show the prospects of CPS.

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“…Figure 1 shows a simulation of the dispersion of particulates in a time-varying wind-driven double-gyre flow where the LCS boundaries are marked as red curves and the corresponding velocity field is shown in Figure 2 . Figure 1 suggests that (a) Lagrangian Coherent Structure (LCS) boundaries behave as basin boundaries, and thus fluid from opposing sides of the boundary do not mix; (b) in the presence of noise 1 , particles can cross the LCS boundaries, and thus LCS denote regions in the flow field where more escape events occur (Forgoston et al, 2011 ); and (c) it makes sense to decompose the oceanic workspace along LCS boundaries and assign sensors to each LCS-bounded region for large-scale monitoring operations (Hsieh et al, 2014 ).…”

Section: Introductionmentioning

confidence: 99%

“…boundaries and assign sensors to each LCS-bounded region for large-scale monitoring operations (Hsieh et al, 2014). While the model shown in Figures 1, 2 presents an idealized representation of the flow field, a snapshot of the ocean surface currents in August 2005 (Figure 3) shows a variety of flow patterns including jets and gyres similar to those in Figures 1, 2 2 .…”

Section: Introductionmentioning

confidence: 99%

Synchronous Rendezvous for Networks of Marine Robots in Large Scale Ocean Monitoring

Hsieh

Cong

et al. 2019

Front. Robot. AI

Self Cite

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We develop a synchronous rendezvous strategy for a network of minimally actuated mobile sensors or active drifters to monitor a set of Lagrangian Coherent Structure (LCS) bounded regions, each exhibiting gyre-like flows. This paper examines the conditions under which a pair of neighboring agents achieves synchronous rendezvous relying solely on the inherent flow dynamics within each LCS bounded region. The objective is to enable drifters in adjacent LCS bounded regions to rendezvous in a periodic fashion to exchange and fuse sensor data. We propose an agent-level control strategy to regulate the drifter speed in each monitoring region as well as to maximize the time the drifters are connected and able to communicate at every rendezvous. The strategy utilizes minimal actuation to ensure synchronization between neighboring pairs of drifters to ensure periodic rendezvous. The intermittent synchronization policy enables a locally connected network of minimally actuated mobile sensors to converge to a common orbit frequency. Robustness analysis against possible disturbance in practice and simulations are provided to illustrate the results.

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Distributed allocation of mobile sensing agents in geophysical flows

Cited by 10 publications

References 18 publications

Tracking Attracting Lagrangian Coherent Structures in Flows

Tracking Attracting Lagrangian Coherent Structures in Flows

A comprehensive overview of cyber-physical systems: from perspective of feedback system

Synchronous Rendezvous for Networks of Marine Robots in Large Scale Ocean Monitoring

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