Safe, Remote-Access Swarm Robotics Research on the Robotarium

This paper describes the development of the Robotarium -- a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-agent research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium as well as connects these to the particular considerations one must take when making complex hardware remotely accessible. In particular, safety must be built in already at the design phase without overly constraining which coordinated control programs the users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.Comment: 13 pages, 7 figures, 3 code samples, 72 reference

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

THE NEXT GENERATION OF WILDLAND FIREFIGHTING TOOLS: USING UAV SWARMS FOR FIRE ATTACK

Wildland fires pose a direct threat to homeland security because of the severe personal, economic, and social stress they cause to those affected. As unmanned aerial vehicle (UAV) swarms become more ubiquitous in use, they will likely find a place as a frontline firefighting aerial asset, increasing the operational pace of aerial suppression flights and consequently increasing the safety of firefighters. This thesis explored the concept of using UAV swarms as a method for fire attack by comparing theoretical swarms to a conventional aerial asset within a realistic fire scenario and then using a systems engineering approach to define pressure points for implementing UAV swarms in the wildland space. The findings of this research support continued development of UAV swarms and clearly define areas that must be addressed before implementing large-scale UAV swarm flights. The firefighting UAV swarm system shows great promise due to its relative portability and ability to provide an aerial firefighting option to areas without ready access to conventional firefighting aircraft. It will be critical, however, to address logistical and communications constraints of UAV swarm systems before implementation to ensure positive outcomes.Civilian, Portland Fire and RescueApproved for public release. Distribution is unlimited

Creativity and Autonomy in Swarm Intelligence Systems

This work introduces two swarm intelligence algorithms -- one mimicking the behaviour of one species of ants (\emph{Leptothorax acervorum}) foraging (a `Stochastic Diffusion Search', SDS) and the other algorithm mimicking the behaviour of birds flocking (a `Particle Swarm Optimiser', PSO) -- and outlines a novel integration strategy exploiting the local search properties of the PSO with global SDS behaviour. The resulting hybrid algorithm is used to sketch novel drawings of an input image, exploliting an artistic tension between the local behaviour of the `birds flocking' - as they seek to follow the input sketch - and the global behaviour of the `ants foraging' - as they seek to encourage the flock to explore novel regions of the canvas. The paper concludes by exploring the putative `creativity' of this hybrid swarm system in the philosophical light of the `rhizome' and Deleuze's well known `Orchid and Wasp' metaphor

Crowdsourcing Swarm Manipulation Experiments: A Massive Online User Study with Large Swarms of Simple Robots

Micro- and nanorobotics have the potential to revolutionize many applications including targeted material delivery, assembly, and surgery. The same properties that promise breakthrough solutions---small size and large populations---present unique challenges to generating controlled motion. We want to use large swarms of robots to perform manipulation tasks; unfortunately, human-swarm interaction studies as conducted today are limited in sample size, are difficult to reproduce, and are prone to hardware failures. We present an alternative. This paper examines the perils, pitfalls, and possibilities we discovered by launching SwarmControl.net, an online game where players steer swarms of up to 500 robots to complete manipulation challenges. We record statistics from thousands of players, and use the game to explore aspects of large-population robot control. We present the game framework as a new, open-source tool for large-scale user experiments. Our results have potential applications in human control of micro- and nanorobots, supply insight for automatic controllers, and provide a template for large online robotic research experiments.Comment: 8 pages, 13 figures, to appear at 2014 IEEE International Conference on Robotics and Automation (ICRA 2014

A Novel Communications Protocol Using Geographic Routing for Swarming UAVs Performing a Search Mission

This research develops the UAV Search Mission Protocol (USMP) for swarming UAVs and determines the protocol\u27s effect on search mission performance. It is hypothesized that geographically routing USMP messages improves search performance by providing geography-dependent data to locations where it impacts search decisions. It is also proposed that the swarm can use data collected by the geographic routing protocol to accurately determine UAV locations and avoid sending explicit location updates. The hypothesis is tested by developing several USMP designs that are combined with the Greedy Perimeter Stateless Routing (GPSR) protocol and a search mission swarm logic into a single network simulation. The test designs use various transmission power levels, sensor types and swarm sizes. The simulation collects performance metrics for each scenario, including measures of distance traveled, UAV direction changes, number of searches and search concentration. USMP significantly improves mission performance over scenarios without inter-UAV communication. However, protocol designs that simply broadcast messages improve search performance by 83% in total searches and 20% in distance traveled compared to geographic routing candidates. Additionally, sending explicit location updates generates 3%-6% better performance per metric versus harvesting GPSR\u27s location information

WATER-BASED MITIGATION TECHNIQUES AND NETWORK INTEGRATION TO COUNTER DRONE SWARMS

Potential and current U.S. adversaries are purchasing and deploying commercial small Unmanned Aircraft Systems (sUAS) in networked swarms. These swarms can be used for intelligence collection and reconnaissance, and have the potential to be weaponized as well. Additionally, the unlawful, but probably not malicious, activity of civilian UAS (drone) operators is of increasing concern. More specifically, there is increased risk to naval assets while in constrained environments, such as harbor transit, where both navigation and weaponized responses are serious concerns. This thesis uses the scenario of protecting a U.S. Navy destroyer entering and exiting a harbor to develop a sUAS mitigation procedure based on existing firefighting and counter-piracy technologies. The proposed procedure includes a communications plan and can be implemented almost immediately using existing civilian and military assets. Additional recommendations to improve the performance of such procedures are provided.CRUSARRRTOLieutenant, United States NavyApproved for public release. Distribution is unlimited

A Novel Approach for Image Localization Using SVM Classifier and PSO Algorithm for Vehicle Tracking

In this paper, we propose a novel methodology for vehicular image localization, by incorporating the surveillance image object identification, using a local gradient model, and vehicle localization using the time of action. The aerial images of different traffic densities are obtained using the Histograms of Oriented Gradients (HOG) Descriptor. These features are acquired simply based on locations, angles, positions, and height of cameras set on the junction board. The localization of vehicular image is obtained based on the different times of action of the vehicles under consideration. Support Vector Machines (SVM) classifier, as well as Particle Swarm Optimization (PSO), is also proposed in this work. Different experimental analyses are also performed to calculate the efficiency of optimization methods in the new proposed system. Outcomes from experimentations reveal the effectiveness of the classification precision, recall, and F measure

Natural computing for vehicular networks

La presente tesis aborda el diseño inteligente de soluciones para el despliegue de redes vehiculares ad-hoc (vehicular ad hoc networks, VANETs). Estas son redes de comunicación inalámbrica formada principalmente por vehículos y elementos de infraestructura vial. Las VANETs ofrecen la oportunidad para desarrollar aplicaciones revolucionarias en el ámbito de la seguridad y eficiencia vial. Al ser un dominio tan novedoso, existe una serie de cuestiones abiertas, como el diseño de la infraestructura de estaciones base necesaria y el encaminamiento (routing) y difusión (broadcasting) de paquetes de datos, que todavía no han podido resolverse empleando estrategias clásicas. Es por tanto necesario crear y estudiar nuevas técnicas que permitan de forma eficiente, eficaz, robusta y flexible resolver dichos problemas. Este trabajo de tesis doctoral propone el uso de computación inspirada en la naturaleza o Computación Natural (CN) para tratar algunos de los problemas más importantes en el ámbito de las VANETs, porque representan una serie de algoritmos versátiles, flexibles y eficientes para resolver problemas complejos. Además de resolver los problemas VANET en los que nos enfocamos, se han realizado avances en el uso de estas técnicas para que traten estos problemas de forma más eficiente y eficaz. Por último, se han llevado a cabo pruebas reales de concepto empleando vehículos y dispositivos de comunicación reales en la ciudad de Málaga (España). La tesis se ha estructurado en cuatro grandes fases. En la primera fase, se han estudiado los principales fundamentos en los que se basa esta tesis. Para ello se hizo un estudio exhaustivo sobre las tecnologías que emplean las redes vehiculares, para así, identificar sus principales debilidades. A su vez, se ha profundizado en el análisis de la CN como herramienta eficiente para resolver problemas de optimización complejos, y de cómo utilizarla en la resolución de los problemas en VANETs. En la segunda fase, se han abordado cuatro problemas de optimización en redes vehiculares: la transferencia de archivos, el encaminamiento (routing) de paquetes, la difusión (broadcasting) de mensajes y el diseño de la infraestructura de estaciones base necesaria para desplegar redes vehiculares. Para la resolución de dichos problemas se han propuesto diferentes algoritmos CN que se clasifican en algoritmos evolutivos (evolutionary algorithms, EAs), métodos de inteligencia de enjambre (swarm intelligence, SI) y enfriamiento simulado (simulated annealing, SA). Los resultados obtenidos han proporcionado protocolos de han mejorado de forma significativa las comunicaciones en VANETs. En la tercera y última fase, se han realizado experimentos empleando vehículos reales circulando por las carreteras de Málaga y que se comunicaban entre sí. El principal objetivo de estas pruebas ha sido el validar las mejoras que presentan los protocolos que se han optimizado empleando CN. Los resultados obtenidos de las fases segunda y tercera confirman la hipótesis de trabajo, que la CN es una herramienta eficiente para tratar el diseño inteligente en redes vehiculares