Coverage control with anytime updates for persistent surveillance missions

Peters, Jeffrey R.; Wang, Sean J.; Bullo, Francesco

doi:10.23919/acc.2017.7962964

Cited by 4 publications

(3 citation statements)

References 13 publications

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“…In the approach of Araujo et al (2013), a line in the optimal sweeping direction is moved along the environment to slice it each time the area on one of the sides is the same as any required partition. A polygon decomposition was applied by Maza and Ollero (2007), with the restriction of including the robot position inside its partition, and in Peters et al (2017) an algorithm handles sporadic communication between each robot and a central base to update the partition. Pavone et al (2011) computed equitable partitions in convex environments using power diagrams in a distributed way.…”

Section: Environment Partitioningmentioning

confidence: 99%

Equitable persistent coverage of non-convex environments with graph-based planning

Palacios-Gasós¹,

Tardioli

Montijano

et al. 2019

The International Journal of Robotics Research

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In this article, we tackle the problem of persistently covering a complex non-convex environment with a team of robots. We consider scenarios where the coverage quality of the environment deteriorates with time, requiring every point to be constantly revisited. As a first step, our solution finds a partition of the environment where the amount of work for each robot, weighted by the importance of each point, is equal. This is achieved using a power diagram and finding an equitable partition through a provably correct distributed control law on the power weights. Compared with other existing partitioning methods, our solution considers a continuous environment formulation with non-convex obstacles. In the second step, each robot computes a graph that gathers sweep-like paths and covers its entire partition. At each planning time, the coverage error at the graph vertices is assigned as weights of the corresponding edges. Then, our solution is capable of efficiently finding the optimal open coverage path through the graph with respect to the coverage error per distance traversed. Simulation and experimental results are presented to support our proposal.

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Section: Environment Partitioningmentioning

confidence: 99%

Equitable persistent coverage of non-convex environments with graph-based planning

Palacios-Gasós¹,

Tardioli

Montijano

et al. 2019

The International Journal of Robotics Research

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“…Furthermore, some agent combinations are not associated to a cell at all, e.g. V ( 1, 5) and V ( 3,4). This is due to the fact that these agents do not share points in the space that are mutually closer to them combined than to any of the other agents.…”

Section: A K-order Voronoi Partitionsmentioning

confidence: 99%

“…This is commonly referred to as coverage control. Specific applications include topics such as environmental monitoring [1], [2], survelliance [3], data collection [4], [5], and search and rescue [6]. More specifically, we consider a generalization of the coverage problem that extends to scenarios where more than one agent may be required to overlap a region in the coverage area.…”

Section: Introductionmentioning

confidence: 99%

Self-triggered distributed k-order coverage control

Tabatabai¹,

Ajina²,

Nowzari³

2019

Preprint

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A k-order coverage control problem is studied where a network of agents must deploy over a desired area. The objective is to deploy all the agents in a decentralized manner such that a certain coverage performance metric of the network is maximized. Unlike many prior works that consider multiagent deployment, we explicitly consider applications where more than one agent may be required to service an event that randomly occurs anywhere in the domain. The proposed method ensures the distributed agents autonomously cover the area while simultaneously relaxing the requirement of constant communication among the agents. In order to achieve the stated goals, a self-triggered coordination method is developed that both determines how agents should move without having to continuously acquire information from other agents, as well as exactly when to communicate and acquire new information. Through analysis, the proposed strategy is shown to provide asymptotic convergence similar to that of continuous or periodic methods. Simulation results demonstrate that the proposed method can reduce the number of messages exchanged as well as the amount of communication power necessary to accomplish the deployment task.

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