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Coverage control for mobile sensing networks

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TLDR
This paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies which are adaptive, distributed, asynchronous, and verifiably correct.
Abstract
This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

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Citations
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Proceedings ArticleDOI

Decentralized vehicle routing in a stochastic and dynamic environment with customer impatience

TL;DR: Borders are derived on the minimum number of agents required to ensure a given performance level, and decentralized motion coordination algorithms that approximate the optimal strategy are presented.
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Distributed receding horizon control of spatially invariant systems

TL;DR: It is proved that for spatially invariant systems with constraints, optimal receding horizon controllers are piecewise affine (represented as a convolution sum plus an offset) in the unconstrained infinite-horizon case.
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Distributed area coverage control with imprecise robot localization: Simulation and experimental studies

TL;DR: This article examines the static area coverage problem by a network of mobile, sensor-equipped agents with imprecise localization with a novel partitioning scheme, the Additively Weighted Guaranteed Voronoi diagram, which takes into account both the agents’ positioning uncertainty and their heterogeneous sensing performance.
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Cooperative Search by Multiple Unmanned Aerial Vehicles in a Nonconvex Environment

TL;DR: An asynchronous distributed cooperative search framework is proposed by integrating the information update into the coverage control scheme, and an adaptive density function is designed based on the real-time updated probability map and uncertainty map, which can balance target detection and environment exploration.
Journal ArticleDOI

How to Systematically Distribute Candidate Models and Robust Controllers in Multiple-Model Adaptive Control: A Coverage Control Approach

TL;DR: A systematic solution to the distribution of nominal models in multiple-models applications is presented by phrasing the distribution as coverage control problem, in which each model covers a subset of the uncertainty.
References
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Coordination of groups of mobile autonomous agents using nearest neighbor rules

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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.
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