Voronoi coverage of non-convex environments with a group of networked robots

Breitenmoser, Andreas; Schwager, Mac; Metzger, Jean-Claude; Siegwart, Roland; Rus, Daniela

doi:10.1109/robot.2010.5509696

Cited by 187 publications

(138 citation statements)

References 17 publications

(27 reference statements)

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“…Voronoi Diagram [2] is shown to be the best cell partition for the one-tier homogeneous networks and Lloydlike Algorithms are applied to minimize the distortions. A similar node deployment problem over a non-convex environment, where the nodes can be placed everywhere other than some obstacles, are considered in [39], [40]. The sensing coverage problem in heterogeneous WSNs where sensors have different sensing ranges is discussed in [41]- [43].…”

Section: Related Work and Applicationsmentioning

confidence: 99%

A Source Coding Perspective on Node Deployment in Two-Tier Networks

Guo

Koyuncu

Jafarkhani

2018

IEEE Trans. Commun.

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Abstract-Multi-tier networks have many applications in different fields. We define a novel two-tier quantizer that can be applied to different node deployment problems including the energy conservation in two-tier wireless sensor networks (WSNs) consisting of N access points (APs) and M fusion centers (FCs). We aim at finding an optimal deployment of APs and FCs to minimize the average weighted total, or Lagrangian, of sensor and AP powers. For one fusion center, M = 1, we show that the optimal deployment of APs is simply a linear transformation of the optimal N -level quantizer for density f , and the sole FC should be located at the geometric centroid of the sensing field. We also provide the exact expression of the AP-Sensor power function and prove its convexity. For more than one fusion center, M > 1, we provide a necessary condition for the optimal deployment. Furthermore, to numerically optimize the AP and FC deployment, we propose three Lloyd-like algorithms and analyze their convergence. Simulation results show that our algorithms outperform the existing algorithms.

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Section: Related Work and Applicationsmentioning

confidence: 99%

A Source Coding Perspective on Node Deployment in Two-Tier Networks

Guo

Koyuncu

Jafarkhani

2018

IEEE Trans. Commun.

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“…Volonoi-based techniques are also another methods that do not require graph descriptions of the environments, such as Refs. [4], [6], [18]. However, these require computational costs that limit their applicability.…”

Section: Related Workmentioning

confidence: 99%

Coordinated Area Partitioning Method by Autonomous Agents for Continuous Cooperative Tasks

Sea

Kato

Sugawara

2017

Journal of Information Processing

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Abstract:We describe a method for decentralized task/area partitioning for coordination in cleaning/sweeping domains with learning to identify the easy-to-dirty areas. Ongoing advances in computer science and robotics have led to applications for covering large areas that require coordinated tasks by multiple control programs including robots. Our study aims at coordination and cooperation by multiple agents, and we discuss it using an example of the cleaning tasks to be performed by multiple agents with potentially different performances and capabilities. We then developed a method for partitioning the target area on the basis of their performances in order to improve the overall efficiency through their balanced collective efforts. Agents, i.e., software for controlling devices and robots, autonomously decide in a cooperative manner how the task/area is partitioned by taking into account the characteristics of the environment and the differences in agents' software capability and hardware performance. During this partitioning process, agents also learn the locations of obstacles and the probabilities of dirt accumulation that express what areas are easy to be dirty. Experimental evaluation showed that even if the agents use different algorithms or have the batteries with different capacities resulting in different performances, and even if the environment is not uniform such as different locations of easy-to-dirty areas and obstacles, the proposed method can adaptively partition the task/area among the agents with the learning of the probabilities of dirt accumulations. Thus, agents with the proposed method can keep the area clean effectively and evenly.

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“…Environments with polygonal obstacles are considered in [63,7]. A solution to the multi-agent coverage problem for non-point robots in non-convex environments can be found in [51].…”

Section: Multi-agent Coverage and Spatial Load Balancingmentioning

confidence: 99%

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Boardman¹

2017

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Voronoi coverage of non-convex environments with a group of networked robots

Cited by 187 publications

References 17 publications

A Source Coding Perspective on Node Deployment in Two-Tier Networks

A Source Coding Perspective on Node Deployment in Two-Tier Networks

Coordinated Area Partitioning Method by Autonomous Agents for Continuous Cooperative Tasks

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

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