Distributed allocation of mobile sensing swarms in gyre flows

We present the development and experimental validation of an autonomous surface/underwater vehicle control strategy that leverages the environmental dynamics and uncertainty to navigate in a stochastic fluidic environment. We assume that the workspace is composed of the union of a collection of disjoint regions, each bounded by Lagrangian coherent structures (LCSs). LCSs are dynamical features in the flow field that behave like invariant manifolds in general time-invariant dynamical systems and delineate the boundaries of attraction basins. We analyze a passive particle's noise-induced transition between adjacent LCS-bounded regions and show how most probable escape trajectories with respect to the transition probability between adjacent LCS-bounded regions can be determined. Additionally, we show how the likelihood of transition can be controlled through minimal actuation. The result is an energy efficient navigation strategy that leverages the inherent dynamics of the surrounding flow field for mobile sensors operating in a noisy fluidic environment. We experimentally validate the proposed vehicle control strategy and analyze its theoretical properties. Our results show that the single vehicle control parameter exhibits a predictable exponential scaling with respect to the escape times and is effective even in situations where the structure of the flow is not fully known and control effort is costly.

show abstract

“…The above control strategy was first introduced in Mallory et al (2013) and further analyzed in Heckman et al (2014). When c .…”

Section: Controller Synthesismentioning

confidence: 99%

Toward efficient navigation in uncertain gyre-like flows

Heckman¹,

Schwartz

Hsieh

2015

The International Journal of Robotics Research

View full text Add to dashboard Cite

show abstract

“…. , Γ N+M } associated with the virtual (spiral) vortices as control inputs; the problem is to characterize and stabilize the desired solutions of (11). Note that because it is necessary to have more than a single virtual vortex for controllability, the circulation strength Γ β of virtual vortex β only influences virtual vortex β indirectly.…”

Section: Point-vortex Dynamics and Relative Equilibriamentioning

confidence: 99%

“…Significant hardware and sensor improvements [19] as well as algorithmic performance guarantees [9], [10] have further encouraged interest. However, there are open challenges about how mobile sensor platforms can most effectively sample and interact with strong, circulating flows [3], [10], [11].…”

Section: Introductionmentioning

confidence: 99%

Active Singularities for Multivehicle Motion Planning in an N-Vortex System

Lagor

Paley

2015

Dynamic Data-Driven Environmental Systems Science

View full text Add to dashboard Cite

Abstract. This paper presents a path-planning paradigm for distributed control of multiple sensor platforms in a geophysical flow well-approximated by a point-vortex model. We utilize Hamiltonian dynamics to generate control vector fields for vehicle motion in N -vortex flows using the concept of an active singularity whose strength is a tunable control input. We introduce active singularities that are virtual point vortices possibly collocated with virtual point sources or sinks. We provide a principled method to stabilize relative equilibria of these virtual vortices in the presence of the actual point vortices, which represent the underlying geophysical flow. We illustrate how these relative equilibria may be useful for vehicle path planning and sampling in a geophysical flow. Preliminary results presented here are based on an adaptive control design.

show abstract

“…In this work, we present a method that exploits such modeling uncertainties and the inherent stochasticity of the environment, to control the dwell times of the sensors in a given region. We use a modeling framework where the ocean environment is considered to be composed of an array of gyre flow structures [5,6], which can clearly be observed in satellite imagery of the ocean (see Figure 1). With the proposed control strategy, the average dwell time of a sensor in a gyre can be controlled to a desired value.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Stochasticity for the Control of Transitions in Gyre Flows

Kularatne

Forgoston

Hsieh

2018

Robotics: Science and Systems XIV

View full text Add to dashboard Cite

Abstract-We present a control strategy to control the intergyre switching time of an agent operating in a gyre flow. The proposed control strategy exploits the stochasticity of the underlying environment to affect inter-gyre transitions. We show how control can be used to enhance or abate the mean escape time and present a strategy to achieve a desired mean escape time. We show that the proposed control strategy can achieve any desired escape time in an interval governed by the maximum available control. We demonstrate the effectiveness of the strategy in simulations.

show abstract

Distributed allocation of mobile sensing swarms in gyre flows

Cited by 28 publications

References 40 publications

Toward efficient navigation in uncertain gyre-like flows

Toward efficient navigation in uncertain gyre-like flows

Active Singularities for Multivehicle Motion Planning in an N-Vortex System

Exploiting Stochasticity for the Control of Transitions in Gyre Flows

Contact Info

Product

Resources

About