Detection of Coherent Structures in Flows

In this work, we have developed an experimental flow tank that can produce realistic ocean-like flows, including multi-gyre flows. By generating controllable ocean-like flow fields, we can study the flows to gain a better understanding of ocean dynamics. In particular, we use particle image velocimetry and finite-time Lyapunov exponents to determine the location of the Lagrangian Coherent Structures that determine transport in complex fluid flows. This understanding is useful for designing control algorithms and for optimizing the use of autonomous vehicles operating in the stochastic and time-dependent ocean environment

Communicating through motion in dance and animal groups

This study explores principles of motion based communication in animal and human group behavior. It develops models of cooperative control that involve communication through actions aimed at a shared objective. Moreover, it aims at understanding the collective motion in multi-agent models towards a desired objective which requires interaction with the environment. In conducting a formal study of these problems, first we investigate the leader-follower interaction in a dance performance. Here, the prototype model is salsa. Salsa is of interest because it is a structured interaction between a leader (usually a male dancer) and a follower (usually a female dancer). Success in a salsa performance depends on how effectively the dance partners communicate with each other using hand, arm and body motion. We construct a mathematical framework in terms of a Dance Motion Description Language (DMDL). This provides a way to specify control protocols for dance moves and to represent every performance as sequences of letters and corresponding motion signals. An enhanced form of salsa (intermediate level) is discussed in which the constraints on the motion transitions are described by simple rules suggested by topological knot theory. It is shown that the proficiency hierarchy in dance is effectively captured by proposed complexity metrics. In order to investigate the group behavior of animals that are reacting to environmental features, we have analyzed a large data set derived from 3-d video recordings of groups of Myotis velifer emerging from a cave. A detailed statistical analysis of large numbers of trajectories indicates that within certain bounds of animal diversity, there appear to be common characteristics of the animals' reactions to features in a clearly defined flight corridor near the mouth of the cave. A set of vision-based motion control primitives is proposed and shown to be effective in synthesizing bat-like flight paths near groups of obstacles. A comparison of synthesized paths and actual bat motions culled from our data set suggests that motions are not based purely on reactions to environmental features. Spatial memory and reactions to the movement of other bats may also play a role. It is argued that most bats employ a hybrid navigation strategy that combines reactions to nearby obstacles and other visual features with some combination of spatial memory and reactions to the motions of other bats

Distributed Allocation of Mobile Sensing Agents in Geophysical Flows

We address the synthesis of distributed control policies to enable a homogeneous team of mobile sensing agents to maintain a desired spatial distribution in a geophysical flow environment. Geophysical flows are natural large-scale fluidic environments such as oceans, eddies, jets, and rivers. In this work, we assume the agents have a \u27map\u27 of the fluidic environment consisting of the locations of the Lagrangian coherent structures (LCS). LCS are time-dependent structures that divide the flow into dynamically distinct regions, and are time-dependent extensions of stable and unstable manifolds. Using this information, we design agent-level hybrid control policies that leverage the surrounding fluid dynamics and inherent environmental noise to enable the team to maintain a desired distribution in the workspace. We validate the proposed control strategy using flow fields given by: 1) an analytical time-varying wind-driven multi-gyre flow model, 2) actual flow data generated using our coherent structure experimental testbed, and 3) ocean data provided by the Navy Coastal Ocean Model (NCOM) database