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Robot and Sensor Networks for Environmental Monitoring

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 25187

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Special Issue Editors

Dr. Annalisa Milella

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Guest Editor

Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing, National Research Council of Italy, via Amendola 122/D-I, 70126 Bari, Italy
Interests: multi-sensor systems for robot perception; 3D reconstruction and mapping; signal and image processing applied to robotics and intelligent systems; agricultural robotics
Special Issues, Collections and Topics in MDPI journals

Dr. Antonio Petitti

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Guest Editor

Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council (CNR), 70126 Bari, Italy
Interests: distributed estimation; agricultural robotics; distributed control; robotic-aided IoT

Special Issue Information

Dear Colleagues,

In recent decades, sensor networks have been used across expansive environments to develop effective surveying systems in critical domains like agricultural, forest, and sea monitoring and for ambient intelligence in general. While sensor networks provide a powerful tool to capture relevant information about environments and people activities therein, managing and maintaining the network can be challenging if a dense sampling of the environment is required. On the other hand, sparse area coverage may induce connection failures. Mobile robots hold the promise to enhance the potential of sensor networks. Robots can carry a wide range of sensors, thus offering increased availability and awareness as compared to a static system. They can interact with the environment, with humans or with other robots to perform complex tasks, enabling the development of intelligent systems that are not only able to detect events but also to actively intervene on the environment accordingly. They can also interact with stationary sensors by improving their connectivity or to support labor-intensive tasks such as deployment, maintenance or charging of multiple nodes in wide areas.

The aim of this Special Issue is to provide researchers and professionals with high-quality and state-of-the-art papers addressing the latest advances in the design, development, and deployment of robot and sensor networks. Related research includes but is not limited to robot and sensor network architectures, multisensor data fusion and analysis, communications in monitoring systems, agricultural and forest, sea monitoring, and ambient intelligence applications.

Dr. Annalisa Milella
Dr. Antonio Petitti
Guest Editors

Manuscript Submission Information

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Keywords

Robot and sensor networks
Robotic-aided IoT
Multisensor data fusion and analysis
IoT for environmental monitoring
IoT for precision agriculture
Agricultural and forest monitoring
Sea monitoring
Security and surveillance
Ambient Intelligence

Published Papers (4 papers)

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Research

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32 pages, 8482 KiB

Open AccessArticle

Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

by Jin-Gu Kang, Dong-Woo Lim, Yong-Sik Choi, Woo-Jin Jang and Jin-Woo Jung

Sensors 2021, 21(2), 333; https://doi.org/10.3390/s21020333 - 6 Jan 2021

Cited by 62 | Viewed by 6303

Abstract

This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time. Full article

(This article belongs to the Special Issue Robot and Sensor Networks for Environmental Monitoring)

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35 pages, 820 KiB

Open AccessArticle

Energy-Efficient Cluster-Based Data Collection by a UAV with a Limited-Capacity Battery in Robotic Wireless Sensor Networks

by Omer Melih Gul and Aydan Muserref Erkmen

Sensors 2020, 20(20), 5865; https://doi.org/10.3390/s20205865 - 16 Oct 2020

Cited by 21 | Viewed by 2214

Abstract

In this work, our motivation focuses on an energy-efficient data collection problem by a mobile sink, an unmanned aerial vehicle (UAV) with limited battery capacity, in a robot network divided into several robot clusters. In each cluster, a cluster head (CH) robot allocates tasks to the remaining robots and collects data from them. Our contribution is to minimize the UAV total energy consumption coupled to minimum cost data collection from CH robots by visiting optimally a portion of the CH robots. The UAV decides the subset of CH robots to visit by considering not only the locations of all CH robots but also its battery capacity. If the UAV cannot visit all CH robots, then the CH robots not visited by the UAV transmit their data to another CH robot to forward it. The decision of transmission paths of transmitting robots is included in the cost optimization. Our contribution passes beyond the existing paradigms in the literature by considering the constant battery capacity for the UAV. We derive the optimal approach analytically for this problem. For various numbers of clusters, the performance of our strategy is compared with the approach in the close literature in terms of total energy consumed by CH robots, which affects network lifetime. Numerical results demonstrate that our strategy outperforms the approach in the close literature. Full article

(This article belongs to the Special Issue Robot and Sensor Networks for Environmental Monitoring)

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21 pages, 3514 KiB

Open AccessArticle

The Repair Strategy for Event Coverage Holes Based on Mobile Robots in Wireless Sensor and Robot Networks

by Yaoming Zhuang, Chengdong Wu, Hao Wu, Hao Chu, Yuan Gao and Li Li

Sensors 2019, 19(22), 5045; https://doi.org/10.3390/s19225045 - 19 Nov 2019

Cited by 4 | Viewed by 2564

Abstract

In the application of the wireless sensor and robot networks (WSRNs), there is an urgent need to accommodate flexible surveillance tasks in intricate surveillance scenarios. On the condition of flexible surveillance missions and demands, event coverage holes occur in the networks. The conventional network repair methods based on the geometric graph theory such as Voronoi diagram method are unable to meet the conditions of flexible surveillance tasks and severe multi-restraint scenarios. Mobile robots show obvious advantages in terms of adaptation capacity and mobility in hazardous and severe scenarios. First, we propose an event coverage hole healing model for multi-constrained scenarios. Then, we propose a joint event coverage hole repair algorithm (JECHR) on the basis of global repair and local repair to apply mobile robots to heal event coverage holes in WSRNs. Different from conventional healing methods, the proposed algorithm can heal event coverage holes efficaciously which are resulted from changing surveillance demands and scenarios. The JECHR algorithm can provide an optimal repair method, which is able to adapt different kinds of severe multi-constrained circumstances. Finally, a large number of repair simulation experiments verify the performance of the JECHR algorithm which can be adapted to a variety of intricate surveillance tasks and application scenarios. Full article

(This article belongs to the Special Issue Robot and Sensor Networks for Environmental Monitoring)

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Review

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23 pages, 704 KiB

Open AccessEditor’s ChoiceReview

Internet of Robotic Things in Smart Domains: Applications and Challenges

by Laura Romeo, Antonio Petitti, Roberto Marani and Annalisa Milella

Sensors 2020, 20(12), 3355; https://doi.org/10.3390/s20123355 - 12 Jun 2020

Cited by 80 | Viewed by 13361

Abstract

With the advent of the Fourth Industrial Revolution, Internet of Things (IoT) and robotic systems are closely cooperating, reshaping their relations and managing to develop new-generation devices. Such disruptive technology corresponds to the backbone of the so-called Industry 4.0. The integration of robotic agents and IoT leads to the concept of the Internet of Robotic Things, in which innovation in digital systems is drawing new possibilities in both industrial and research fields, covering several domains such as manufacturing, agriculture, health, surveillance, and education, to name but a few. In this manuscript, the state-of-the-art of IoRT applications is outlined, aiming to mark their impact on several research fields, and focusing on the main open challenges of the integration of robotic technologies into smart spaces. IoRT technologies and applications are also discussed to underline their influence in everyday life, inducing the need for more research into remote and automated applications. Full article

(This article belongs to the Special Issue Robot and Sensor Networks for Environmental Monitoring)

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