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Coverage control for mobile sensing networks
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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.read more
Citations
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Consensus and Cooperation in Networked Multi-Agent Systems
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Flocking for multi-agent dynamic systems: algorithms and theory
TL;DR: A theoretical framework for design and analysis of distributed flocking algorithms, and shows that migration of flocks can be performed using a peer-to-peer network of agents, i.e., "flocks need no leaders."
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Stability of multiagent systems with time-dependent communication links
TL;DR: It is observed that more communication does not necessarily lead to faster convergence and may eventually even lead to a loss of convergence, even for the simple models discussed in the present paper.
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An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination
TL;DR: In this paper, the authors reviewed some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006, and proposed several promising research directions along with some open problems that are deemed important for further investigations.
BookDOI
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms
TL;DR: This self-contained introduction to the distributed control of robotic networks offers a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation.
References
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Journal ArticleDOI
Swarm Control of UAVs for Cooperative Hunting with DDDAS
Ryan McCune,Gregory R. Madey +1 more
TL;DR: An agent-based simulation for dynamic cooperative cleaning is augmented with additional behaviors and implemented into a Dynamic Data-Driven Applica- tion System (DDDAS) framework for dynamic swarm control.
Proceedings ArticleDOI
A differential game approach to formation control for a team of agents with one leader
TL;DR: It is shown that for the case in which collisions are not considered the problem simplifies to a linear-quadratic differential game, for which approximate solutions are identified.
Proceedings ArticleDOI
Optimal and adaptive battery discharge strategies for Cyber-Physical Systems
Fumin Zhang,Zhenwu Shi +1 more
TL;DR: A dynamic battery model is introduced that describes the variations of the capacity of a battery under time varying discharge current and allows battery capacity prediction for feedback control laws and online scheduling algorithms that are building blocks for Cyber-Physical Systems (CPS) theory.
Journal ArticleDOI
A Method of Optimized Deployment of Charging Stations for Drone Delivery
Hailong Huang,Andrey V. Savkin +1 more
TL;DR: This article considers the placement of charging stations to charge or replace the battery, and thus enlarge the coverage of customers in a demand area by first deploying charging stations in a triangle pattern, which fully covers the demand area.
Posted Content
Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation for Multi-Agent Reinforcement Learning
TL;DR: An explicit upper bound is obtained on the rate of convergence of this algorithm as a function of the network topology and the discount factor when the communication network between the agents is time-varying in general.
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