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Command Control for Many-Robot Systems

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TLDR
This paper describes a program of analysis, modeling, algorithm development, and simulation which has been undertaken to develop, refine, and validate this basic approach to real-world problem solving in the development of military mobile robots.
Abstract
Rapidly evolving sensor, effector and processing technologies, including micromechanical fabrication techniques, will soon make possible the development of very inexpensive autonomous mobile devices with adequate processing but fairly limited sensor capabilities. One goal which has been proposed is to employ large numbers (more than 100) of these simple robots to achieve real-world military mission goals in the ground, air, and underwater environments, using sensor-based reactive planners to realize desired emergent collective group behaviors. One key prerequisite to realizing this goal is the capability to command and control the system of robots in terms of meaningful mission-oriented system-level parameters. A commander requires an understanding of a system's capabilities, doctrine for employing it, and measures of effectiveness to assess its performance once deployed. It is thus necessary to relate system (ensemble) functionality and performance to the behaviors realized by the individual autonomous elements. This paper describes a program of analysis, modeling, algorithm development, and simulation which has been undertaken to develop, refine, and validate this basic approach to real-world problem solving. The initial thrust has been to develop generic behaviors, such as blanket, barrier, and sweep coverage, and various deployment and recovery modes, which can address a broad spectrum of generic applications such as mine deployment, minesweeping, surveillance, sentry duty, maintenance inspection, ship hull cleaning, and communications relaying. Initial simulation results are presented. 1.0 INTRODUCTION The critical sensor, effector, and processing technologies that are prerequisite to the development of the military mobile robots of the 21st century are evolving rapidly. Moreover, while major thrusts in the development of military mobile robots have been undertaken in the areas of Unmanned Ground Vehicles (UGVs), Unmanned Air Vehicles (UAVs), and Unmanned Underwater Vehicles (UUVs), continuing developments in solid-state sensor and effector technologies suggest that unexploited opportunities exist at the "lower end" of the spectrum of robotic vehicle functionality and performance [1, 2]. In fact, the emerging field of "micromachines" (also termed "microdynamics", "mechatronics", or "microelectromechanical systems") was selected

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TL;DR: This article surveys recent contributions addressing energy-efficient coverage problems in the context of static wireless sensor networks, and presents various coverage formulations, their assumptions, as well as an overview of the solutions proposed.
References
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Book

A robust layered control system for a mobile robot

TL;DR: A new architecture for controlling mobile robots is described, building a robust and flexible robot control system that has been used to control a mobile robot wandering around unconstrained laboratory areas and computer machine rooms.
Proceedings ArticleDOI

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TL;DR: In this article, an approach based on simulation as an alternative to scripting the paths of each bird individually is explored, with the simulated birds being the particles and the aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course.
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TL;DR: Braitenberg's "vehicles" as mentioned in this paper are a series of hypothetical, self-operating machines that exhibit increasingly intricate if not always successful or civilized "behavior." Each of the vehicles in the series incorporates the essential features of all the earlier models and along the way they come to embody aggression, love, logic, manifestations of foresight, concept formation, creative thinking, personality, and free will.
Proceedings Article

The dynamics of collective sorting robot-like ants and ant-like robots

TL;DR: A distributed sorting algorithm, inspired by how ant colonies sort their brood, is presented for use by robot teams, offering the advantages of simplicity, flexibility and robustness.
Journal Article

The honey bee colony as a superorganism.

TL;DR: Hora's watches were no less complex than those of Tempus but were designed so that he could put together stable subassemblies of about ten parts each as discussed by the authors, which was the same as Tempus's.
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