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Robotic Sensory Systems for Environment Protection and Conservation

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

Deadline for manuscript submissions: closed (31 July 2016) | Viewed by 86074

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Prof. Dr. João Valente

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Departamento de Ingenieria de Sistemas y Automatica, Universidad Carlos III de Madrid, Av. Universidad, 30, Leganes (Madrid) 28911, Spain
Interests: Field Robotics; UAV; remote sensing; multi-robot systems; Path and Mission planning

Prof. Dr. Antonio Barrientos

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Guest Editor

Centro de Automática y Robótica, Universidad Politécnica de Madrid, 28006 Madrid, Spain
Interests: field robotics; multirobot systems; surveillance, search and rescue robots; robotics in agriculture
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Special Issue Information

Dear Colleagues,

I am proud to announce this Special Issue, addressing the state-of-the-art of robotic systems and related sensors technologies applied to environment monitoring (EM).

Environment protection and conservation researchers manage different biophysical parameters measured over wide areas. The data used for analysis is sometimes acquired manually or through less accessible methods.

Other sensory alternatives, such as robotic systems endowed with dedicated on-board sensor systems, have been reported for pollution monitoring, soils conservation, natural disaster research, and nuclear and radiation accidents.

This Special Issue is an effort to sum up some of these technologies and respective applications. Welcome applications and case studies are: natural disasters, gases emission measuring, pollution monitoring, biomass estimation, agricultural management, natural resources research, and many others.

Authors are encouraged to write review articles, original research papers, short communications, and field reports addressing real applications.

Prof. Dr. João Valente
Prof. Dr. Antonio Barrientos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

field robotics
sensors configurations and architectures
onboard systems
sensor-based path and mission planning
data acquisition and processing
simulations and real applications

Published Papers (10 papers)

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Research

33445 KiB

Open AccessArticle

Sediment Sampling in Estuarine Mudflats with an Aerial-Ground Robotic Team

by Pedro Deusdado, Magno Guedes, André Silva, Francisco Marques, Eduardo Pinto, Paulo Rodrigues, André Lourenço, Ricardo Mendonça, Pedro Santana, José Corisco, Susana Marta Almeida, Luís Portugal, Raquel Caldeira, José Barata and Luis Flores

Sensors 2016, 16(9), 1461; https://doi.org/10.3390/s16091461 - 09 Sep 2016

Cited by 10 | Viewed by 9683

Abstract

This paper presents a robotic team suited for bottom sediment sampling and retrieval in mudflats, targeting environmental monitoring tasks. The robotic team encompasses a four-wheel-steering ground vehicle, equipped with a drilling tool designed to be able to retain wet soil, and a multi-rotor aerial vehicle for dynamic aerial imagery acquisition. On-demand aerial imagery, properly fused on an aerial mosaic, is used by remote human operators for specifying the robotic mission and supervising its execution. This is crucial for the success of an environmental monitoring study, as often it depends on human expertise to ensure the statistical significance and accuracy of the sampling procedures. Although the literature is rich on environmental monitoring sampling procedures, in mudflats, there is a gap as regards including robotic elements. This paper closes this gap by also proposing a preliminary experimental protocol tailored to exploit the capabilities offered by the robotic system. Field trials in the south bank of the river Tagus’ estuary show the ability of the robotic system to successfully extract and transport bottom sediment samples for offline analysis. The results also show the efficiency of the extraction and the benefits when compared to (conventional) human-based sampling. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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2694 KiB

Open AccessArticle

Subsea Cable Tracking by Autonomous Underwater Vehicle with Magnetic Sensing Guidance

by Xianbo Xiang, Caoyang Yu, Zemin Niu and Qin Zhang

Sensors 2016, 16(8), 1335; https://doi.org/10.3390/s16081335 - 20 Aug 2016

Cited by 97 | Viewed by 9507

Abstract

The changes of the seabed environment caused by a natural disaster or human activities dramatically affect the life span of the subsea buried cable. It is essential to track the cable route in order to inspect the condition of the buried cable and protect its surviving seabed environment. The magnetic sensor is instrumental in guiding the remotely-operated vehicle (ROV) to track and inspect the buried cable underseas. In this paper, a novel framework integrating the underwater cable localization method with the magnetic guidance and control algorithm is proposed, in order to enable the automatic cable tracking by a three-degrees-of-freedom (3-DOF) under-actuated autonomous underwater vehicle (AUV) without human beings in the loop. The work relies on the passive magnetic sensing method to localize the subsea cable by using two tri-axial magnetometers, and a new analytic formulation is presented to compute the heading deviation, horizontal offset and buried depth of the cable. With the magnetic localization, the cable tracking and inspection mission is elaborately constructed as a straight-line path following control problem in the horizontal plane. A dedicated magnetic line-of-sight (LOS) guidance is built based on the relative geometric relationship between the vehicle and the cable, and the feedback linearizing technique is adopted to design a simplified cable tracking controller considering the side-slip effects, such that the under-actuated vehicle is able to move towards the subsea cable and then inspect its buried environment, which further guides the environmental protection of the cable by setting prohibited fishing/anchoring zones and increasing the buried depth. Finally, numerical simulation results show the effectiveness of the proposed magnetic guidance and control algorithm on the envisioned subsea cable tracking and the potential protection of the seabed environment along the cable route. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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7208 KiB

Open AccessArticle

A Multi-Robot Sense-Act Approach to Lead to a Proper Acting in Environmental Incidents

by Jesús Conesa-Muñoz, João Valente, Jaime Del Cerro, Antonio Barrientos and Angela Ribeiro

Sensors 2016, 16(8), 1269; https://doi.org/10.3390/s16081269 - 10 Aug 2016

Cited by 19 | Viewed by 6471

Abstract

Many environmental incidents affect large areas, often in rough terrain constrained by natural obstacles, which makes intervention difficult. New technologies, such as unmanned aerial vehicles, may help address this issue due to their suitability to reach and easily cover large areas. Thus, unmanned aerial vehicles may be used to inspect the terrain and make a first assessment of the affected areas; however, nowadays they do not have the capability to act. On the other hand, ground vehicles rely on enough power to perform the intervention but exhibit more mobility constraints. This paper proposes a multi-robot sense-act system, composed of aerial and ground vehicles. This combination allows performing autonomous tasks in large outdoor areas by integrating both types of platforms in a fully automated manner. Aerial units are used to easily obtain relevant data from the environment and ground units use this information to carry out interventions more efficiently. This paper describes the platforms and sensors required by this multi-robot sense-act system as well as proposes a software system to automatically handle the workflow for any generic environmental task. The proposed system has proved to be suitable to reduce the amount of herbicide applied in agricultural treatments. Although herbicides are very polluting, they are massively deployed on complete agricultural fields to remove weeds. Nevertheless, the amount of herbicide required for treatment is radically reduced when it is accurately applied on patches by the proposed multi-robot system. Thus, the aerial units were employed to scout the crop and build an accurate weed distribution map which was subsequently used to plan the task of the ground units. The whole workflow was executed in a fully autonomous way, without human intervention except when required by Spanish law due to safety reasons. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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8877 KiB

Open AccessArticle

A Novel Cloud-Based Service Robotics Application to Data Center Environmental Monitoring

by Ludovico Orlando Russo, Stefano Rosa, Marcello Maggiora and Basilio Bona

Sensors 2016, 16(8), 1255; https://doi.org/10.3390/s16081255 - 08 Aug 2016

Cited by 16 | Viewed by 6095

Abstract

This work presents a robotic application aimed at performing environmental monitoring in data centers. Due to the high energy density managed in data centers, environmental monitoring is crucial for controlling air temperature and humidity throughout the whole environment, in order to improve power efficiency, avoid hardware failures and maximize the life cycle of IT devices. State of the art solutions for data center monitoring are nowadays based on environmental sensor networks, which continuously collect temperature and humidity data. These solutions are still expensive and do not scale well in large environments. This paper presents an alternative to environmental sensor networks that relies on autonomous mobile robots equipped with environmental sensors. The robots are controlled by a centralized cloud robotics platform that enables autonomous navigation and provides a remote client user interface for system management. From the user point of view, our solution simulates an environmental sensor network. The system can easily be reconfigured in order to adapt to management requirements and changes in the layout of the data center. For this reason, it is called the virtual sensor network. This paper discusses the implementation choices with regards to the particular requirements of the application and presents and discusses data collected during a long-term experiment in a real scenario. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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2850 KiB

Open AccessArticle

Towards a Real-Time Embedded System for Water Monitoring Installed in a Robotic Sailboat

by Andouglas Goncalves da Silva Junior, Sarah Thomaz de Lima Sa, Davi Henrique dos Santos, Álvaro Pinto Ferrnandes de Negreiros, João Moreno Vilas Boas de Souza Silva, Justo Emílio Álvarez Jácobo and Luiz Marcos Garcia Gonçalves

Sensors 2016, 16(8), 1226; https://doi.org/10.3390/s16081226 - 08 Aug 2016

Cited by 15 | Viewed by 5638

Abstract

Problems related to quality (and quantity) of water in natural resources or in artificial reservoirs are frequently arising and are at the center of attention of authorities and governments around the world. Many times the monitoring is not performed in an efficient time frame and a precise manner, whereas the adoption of fast and punctual solutions would undoubtedly improve the water quality and consequently enhance the life of people. To minimize or diminish such kinds of problems, we propose an architecture for sensors installed in a robotic platform, an autonomous sail boat, able to acquire raw data relative to water quality, to process and make them available to people that might be interested in such information. The main contributions are the sensors architecture itself, which uses low cost sensors, with practical experimentation done with a prototype. Results show data collected for points in lakes and rivers in the northeast of Brazil. This embedded system is fixed in the sailboat robot with the intention to facilitate the study of water quality for long endurance missions. This robot can help monitoring water bodies in a more consistent manner. Nonetheless the system can also be used with fixed vases or buoys in strategic points. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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49651 KiB

Open AccessArticle

Autonomous Underwater Navigation and Optical Mapping in Unknown Natural Environments

by Juan David Hernández, Klemen Istenič, Nuno Gracias, Narcís Palomeras, Ricard Campos, Eduard Vidal, Rafael García and Marc Carreras

Sensors 2016, 16(8), 1174; https://doi.org/10.3390/s16081174 - 26 Jul 2016

Cited by 54 | Viewed by 9818

Abstract

We present an approach for navigating in unknown environments while, simultaneously, gathering information for inspecting underwater structures using an autonomous underwater vehicle (AUV). To accomplish this, we first use our pipeline for mapping and planning collision-free paths online, which endows an AUV with the capability to autonomously acquire optical data in close proximity. With that information, we then propose a reconstruction pipeline to create a photo-realistic textured 3D model of the inspected area. These 3D models are also of particular interest to other fields of study in marine sciences, since they can serve as base maps for environmental monitoring, thus allowing change detection of biological communities and their environment over time. Finally, we evaluate our approach using the Sparus II, a torpedo-shaped AUV, conducting inspection missions in a challenging, real-world and natural scenario. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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9050 KiB

Open AccessArticle

Heterogeneous Multi-Robot System for Mapping Environmental Variables of Greenhouses

by Juan Jesús Roldán, Pablo Garcia-Aunon, Mario Garzón, Jorge De León, Jaime Del Cerro and Antonio Barrientos

Sensors 2016, 16(7), 1018; https://doi.org/10.3390/s16071018 - 01 Jul 2016

Cited by 93 | Viewed by 16103

Abstract

The productivity of greenhouses highly depends on the environmental conditions of crops, such as temperature and humidity. The control and monitoring might need large sensor networks, and as a consequence, mobile sensory systems might be a more suitable solution. This paper describes the application of a heterogeneous robot team to monitor environmental variables of greenhouses. The multi-robot system includes both ground and aerial vehicles, looking to provide flexibility and improve performance. The multi-robot sensory system measures the temperature, humidity, luminosity and carbon dioxide concentration in the ground and at different heights. Nevertheless, these measurements can be complemented with other ones (e.g., the concentration of various gases or images of crops) without a considerable effort. Additionally, this work addresses some relevant challenges of multi-robot sensory systems, such as the mission planning and task allocation, the guidance, navigation and control of robots in greenhouses and the coordination among ground and aerial vehicles. This work has an eminently practical approach, and therefore, the system has been extensively tested both in simulations and field experiments. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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14375 KiB

Open AccessArticle

Building an Enhanced Vocabulary of the Robot Environment with a Ceiling Pointing Camera

by Alejandro Rituerto, Henrik Andreasson, Ana C. Murillo, Achim Lilienthal and José Jesús Guerrero

Sensors 2016, 16(4), 493; https://doi.org/10.3390/s16040493 - 07 Apr 2016

Cited by 2 | Viewed by 6408

Abstract

Mobile robots are of great help for automatic monitoring tasks in different environments. One of the first tasks that needs to be addressed when creating these kinds of robotic systems is modeling the robot environment. This work proposes a pipeline to build an enhanced visual model of a robot environment indoors. Vision based recognition approaches frequently use quantized feature spaces, commonly known as Bag of Words (BoW) or vocabulary representations. A drawback using standard BoW approaches is that semantic information is not considered as a criteria to create the visual words. To solve this challenging task, this paper studies how to leverage the standard vocabulary construction process to obtain a more meaningful visual vocabulary of the robot work environment using image sequences. We take advantage of spatio-temporal constraints and prior knowledge about the position of the camera. The key contribution of our work is the definition of a new pipeline to create a model of the environment. This pipeline incorporates (1) tracking information to the process of vocabulary construction and (2) geometric cues to the appearance descriptors. Motivated by long term robotic applications, such as the aforementioned monitoring tasks, we focus on a configuration where the robot camera points to the ceiling, which captures more stable regions of the environment. The experimental validation shows how our vocabulary models the environment in more detail than standard vocabulary approaches, without loss of recognition performance. We show different robotic tasks that could benefit of the use of our visual vocabulary approach, such as place recognition or object discovery. For this validation, we use our publicly available data-set. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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5216 KiB

Open AccessArticle

Quantitative Evaluation of Stereo Visual Odometry for Autonomous Vessel Localisation in Inland Waterway Sensing Applications

by Thomas Kriechbaumer, Kim Blackburn, Toby P. Breckon, Oliver Hamilton and Monica Rivas Casado

Sensors 2015, 15(12), 31869-31887; https://doi.org/10.3390/s151229892 - 17 Dec 2015

Cited by 16 | Viewed by 8468

Abstract

Autonomous survey vessels can increase the efficiency and availability of wide-area river environment surveying as a tool for environment protection and conservation. A key challenge is the accurate localisation of the vessel, where bank-side vegetation or urban settlement preclude the conventional use of line-of-sight global navigation satellite systems (GNSS). In this paper, we evaluate unaided visual odometry, via an on-board stereo camera rig attached to the survey vessel, as a novel, low-cost localisation strategy. Feature-based and appearance-based visual odometry algorithms are implemented on a six degrees of freedom platform operating under guided motion, but stochastic variation in yaw, pitch and roll. Evaluation is based on a 663 m-long trajectory (>15,000 image frames) and statistical error analysis against ground truth position from a target tracking tachymeter integrating electronic distance and angular measurements. The position error of the feature-based technique (mean of ±0.067 m) is three times smaller than that of the appearance-based algorithm. From multi-variable statistical regression, we are able to attribute this error to the depth of tracked features from the camera in the scene and variations in platform yaw. Our findings inform effective strategies to enhance stereo visual localisation for the specific application of river monitoring. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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9625 KiB

Open AccessArticle

Two-Dimensional Automatic Measurement for Nozzle Flow Distribution Using Improved Ultrasonic Sensor

by Changyuan Zhai, Chunjiang Zhao, Xiu Wang, Ning Wang, Wei Zou and Wei Li

Sensors 2015, 15(10), 26353-26367; https://doi.org/10.3390/s151026353 - 16 Oct 2015

Cited by 1 | Viewed by 6448

Abstract

Spray deposition and distribution are affected by many factors, one of which is nozzle flow distribution. A two-dimensional automatic measurement system, which consisted of a conveying unit, a system control unit, an ultrasonic sensor, and a deposition collecting dish, was designed and developed. The system could precisely move an ultrasonic sensor above a pesticide deposition collecting dish to measure the nozzle flow distribution. A sensor sleeve with a PVC tube was designed for the ultrasonic sensor to limit its beam angle in order to measure the liquid level in the small troughs. System performance tests were conducted to verify the designed functions and measurement accuracy. A commercial spray nozzle was also used to measure its flow distribution. The test results showed that the relative error on volume measurement was less than 7.27% when the liquid volume was 2 mL in trough, while the error was less than 4.52% when the liquid volume was 4 mL or more. The developed system was also used to evaluate the flow distribution of a commercial nozzle. It was able to provide the shape and the spraying width of the flow distribution accurately. Full article

(This article belongs to the Special Issue Robotic Sensory Systems for Environment Protection and Conservation)

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