Mosquito-inspired Swarming and Pursuit for Autonomous Rotorcraft

The long-term goal of this research is to design cooperative-control algorithms for autonomous vehicles inspired by the collective behaviors in animal groups. The specific research objectives of this dissertation are twofold: (1) to analyze and model the swarming and pursuit behaviors observed in the mating swarms of mosquitoes, and (2) to design mosquito-inspired control algorithms to perform swarming and pursuit with autonomous rotorcraft. The first part of this dissertation analyzes the reconstructed flight data of the malarial mosquito Anopheles gambiae to characterize the velocity-alignment interaction between male mosquitoes, who aggregate to form mating swarms and subsequently pursue a female mosquito. Both swarming and pursuit behaviors are represented using self-propelled particle models. The model is used together with tools from control theory to investigate the connection between velocity-alignment behavior and success in pursuit. The results of this research have a potential impact on vector-control methods for malaria, and are also utilized in the second part of this dissertation. The second part of this dissertation studies two types of pursuit problems inspired by the collective behavior in mosquito swarms. The first problem considers the strategy for a single pursuer chasing a single target. This problem has been studied extensively for the application to missile guidance and navigation. Here, we tailor the assumptions on the dynamics of the agents as well as the design criteria for the application to small and agile rotorcraft. The second pursuit problem incorporates the swarming behavior by considering a scenario in which multiple guardian vehicles are deployed to protect an area against fast intruders. We derive necessary and sufficient conditions for capturing the intruder. We also present swarming strategies to maximize the performance of the guardians, inspired by the random-oscillatory motion and the velocity-alignment behavior of male mosquitoes

Projection-Based Clustering through Self-Organization and Swarm Intelligence

It covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cluster analysis, the Databionic swarm (DBS). DBS consists of the 3D landscape visualization and clustering of data. The 3D landscape enables 3D printing of high-dimensional data structures. The clustering and number of clusters or an absence of cluster structure are verified by the 3D landscape at a glance. DBS is the first swarm-based technique that shows emergent properties while exploiting concepts of swarm intelligence, self-organization and the Nash equilibrium concept from game theory. It results in the elimination of a global objective function and the setting of parameters. By downloading the R package DBS can be applied to data drawn from diverse research fields and used even by non-professionals in the field of data mining

Projection-Based Clustering through Self-Organization and Swarm Intelligence: Combining Cluster Analysis with the Visualization of High-Dimensional Data

Cluster Analysis; Dimensionality Reduction; Swarm Intelligence; Visualization; Unsupervised Machine Learning; Data Science; Knowledge Discovery; 3D Printing; Self-Organization; Emergence; Game Theory; Advanced Analytics; High-Dimensional Data; Multivariate Data; Analysis of Structured Dat

Bioturbation by Hexagenia larvae (Ephemeroptera: Ephemeridae) and its implications for sediment suspension in Lake Erie.

Burrowing activities of aquatic benthic organisms can influence sediment suspension and nutrient cycling. The burrowing mayfly Hexagenia is a dominant benthic organism in western Lake Erie, and Hexagenia bioturbation can potentially influence water quality and other benthic organisms. Using laboratory experiments, I determined bioturbation-induced sediment suspension rates of fine Lake Erie sediment caused by Hexagenia larvae of varying body lengths (13--28 mm) at densities of 70--1,111 larvae/m2 and water temperatures ranging from 10--25°C. Bioturbation rates (sediment suspension, g/m2/h) were estimated by nonlinear regression from measurements of suspended sediment concentrations in jars, taken twice-daily for 14 d. Sediment settling rates were also estimated from twice-daily measurements of suspended sediment concentrations collected for an additional 18 d in the surface water from the bioturbation experiments. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 43-01, page: 0145. Adviser: Jan J. H. Ciborowski. Thesis (M.Sc.)--University of Windsor (Canada), 2004

ARCTIC FLORA AND FAUNA: Status and Conservation

This report draws on the diversity of projects that the Program for the Conservation of Arctic Flora and Fauna (CAFF) has undertaken in its first decade, underscoring the need to address conservation on a circumpolar basis. What is the overall state of the Arctic environment? The aim of this report is to answer the many aspects of this seemingly straightforward question. Although several national and international efforts have looked at parts of the Arctic, this is the first attempt to assess the state of Arctic flora and fauna as a whole

Arctic Flora and Fauna: Status and Conservation

What is the overall state of the Arctic environment? The aim of this report is to answer the many aspects of this seemingly straightforward question. Although several national and international efforts have looked at parts of the Arctic, this is the first attempt to assess the state of Arctic flora and fauna as a whole