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.

Coverage control for mobile sensing networks

Wireless Sensor Networks (WSNs) consist of several battery powered sensor nodes. The sensing coverage of the Field of Interest (FoI) is an important function of the sensor nodes in connected WSNs. A FoI is said to be covered if each point in the FoI is monitored by at least one sensor node. Due to small size, battery power supply, simple architecture, and light weight Operating System of the sensor nodes, maintaining the desired coverage of the FoI consists various issues and challenges in a connected WSN. This paper surveys the existing work done to address various issues and challenges for solving the coverage and connectivity problems in WSNs. Our discussion emphasis on sensing models, classification of coverage, research issues in WSNs and practical challenges in deployment of WSNs. We review a brief but complete overview of the various solutions of coverage problems in connected WSNs and describing insights into issues and challenges for research in this area.

Coverage and Connectivity in WSNs: A Survey, Research Issues and Challenges

Definitions and basic properties of the Voronoi diagram generalizations of the Voronoi diagram algorithms for computing Voronoi diagrams poisson Voronoi diagrams spatial interpolation models of spatial processes point pattern analysis locational optimization through Voronoi diagrams.

Spatial tessellations. Concepts and Applications of Voronoi diagrams

This paper investigates the output formation-containment problem of the coupled heterogeneous linear systems under intermittent communication. The systems considered in this paper are more general in the sense that each system, whether a leader or a follower, has different dimension and different dynamic. Besides, each system only communicates with its neighbors intermittently. Based on the intermittent information, both the state-feedback and the output-feedback distributed control protocols are designed and a criterion is derived to calculate the lower bound of the communication ratio. Furthermore, a heuristic algorithm based on the Fireworks Algorithm is developed to obtain an optimized communication ratio, which greatly reduces the communication burden. Finally, numerical examples are provided to demonstrate the effectiveness of the theoretical results.

Output formation-containment of coupled heterogeneous linear systems under intermittent communication

In this article, we propose the dynamic coverage control method based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K -means. In the traditional coverage control, Voronoi partition method is used to assign the coverage positions for intelligent units. However, the Voronoi partition method requires that the space to be covered is compact and convex, and it is difficult to realize the coverage control of high-dimensional space. Therefore, in this article, we propose a dynamic coverage planning algorithm based on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K -means, which relaxes the requirements on the coverage objects and can calculate the optimal coverage positions of the intelligent units. In addition, we also design a dynamic coverage control law based on discrete sliding mode control to drive the intelligent units to the optimal coverage positions. Through the combination of planning algorithm and control law, the optimal coverage control performance can be achieved for the specified targets and the specified area, which can be discrete, nonconvex, and high dimensional. The stability of the planning algorithm and the control law are proved by theoretical deduction. The effectiveness and superiority of the dynamic coverage control method are verified by two examples.

Dynamic Coverage Control Based on K-Means

We address the nonuniform coverage of a planar region by a platoon of autonomous mobile agents when communications among them are stochastically intermittent. Given a set of generating points and a suitable metric, the solution of the optimal coverage problem is the well known Voronoi tessellation, with a set of mobile agents converging to the centroids of the corresponding Voronoi cells. In the framework of decentralized motion control, this implementation requires that all agents have knowledge of the state of other agents in the platoon. Here we generalize this scenario by considering the optimal area coverage when a group of agents share information in a time varying, stochastically intermittent fashion. We embed on board of each agent a full state estimator that relies on local estimates and on information received by others, when available. We show that under appropriate conditions on the communication network, all agents' estimates asymptotically converge to true states while maximizing the coverage metric despite intermittent communications. The current work has applications in military and civilian domains including harbor protection, perimeter surveillance, and search and rescue missions. Theoretical results are illustrated through computer simulations.

Nonuniform Coverage Control With Stochastic Intermittent Communication

We propose a nonuniform deployment strategy of a group of homogeneous autonomous agents in harbor-like environments. High value units berthed in the area need to be secured against external attacks. Defenders deployed in the area are expected to monitor, intercept, engage, and neutralize threats. In the framework of decentralized coordinated multi-agent systems, we model and simulate the optimal deployment of a group of mobile autonomous agents that accounts for a risk map of the area and the optimal trajectories that minimize the energy consumed to intercept a threat in a given area of interest. Theoretical results are numerically illustrated through simulations in a realistic harbor protection scenario.

/pdf/nonuniform-deployment-of-autonomous-agents-in-harbor-like-4cns0c0re0.pdf

Nonuniform Deployment of Autonomous Agents in Harbor-Like Environments

We address nonuniform coverage with networked multi-agent systems and a nonuniform, time varying risk density function throughout the spatial workspace. The proposed solution for the nonuniform coverage problem is different from existing ones in that the evolution of the density is described by a conservation law with time-varying boundary conditions. By adopting a first gradient constitutive relation between the flux and the density we obtain a simple diffusion equation. The diffused density is then employed by a platoon of autonomous agents for spatially configuring themselves in optimum locations so that the coverage metric is maximized or minimized. We exploit the generalized centroidal Voronoi tessellation technique for generating the motion control of autonomous agents. By assuming that the risk density evolves much faster than the boundary conditions, we prove that the generalized Voronoi centroids are equilibrium points for the coverage metric. A set of numerical simulations illustrate the theoretical results.Copyright © 2014 by ASME and Her Majesty the Queen in Right of Canada

Nonuniform Coverage With Time-Varying Diffusive Density

We propose optimal strategies to develop an automated layered defence system for protecting structured environments, illustrated here by a typical harbor. The harbor is modeled as a two-dimensional environment, with a cooperative set of autonomous mobile agents to be deployed as the defence system. Optimal deployment is measured in a well-known area coverage metric, that encodes agents’ sensing performance and a weight measure defined on the harbor, which allows to represent a priori and time varying risk field. The time-varying risk field allows to model several interesting scenarios. In this work, we consider the case of area surveillance against moving targets or external threats penetrating through the perimeter. We present a feedback control law for the platoon of surveying agents that implies the emergency of locally optimal configurations, that adapt to time evolving harbor environments.

Non-autonomous Area Coverage and Coordination of a Multi-agent System for Harbor Protection Applications.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of {limit} columns in the table. Remove at least 1 column to add or create another one.

Alex Bourque

Author Tools

Chat about Author

Papers

Nonuniform Coverage Control With Stochastic Intermittent Communication

Nonuniform Deployment of Autonomous Agents in Harbor-Like Environments

Nonuniform Coverage With Time-Varying Diffusive Density

Non-autonomous Area Coverage and Coordination of a Multi-agent System for Harbor Protection Applications.