On Collaborative Aerial and Surface Robots for Environmental Monitoring of Water Bodies

Part 8: Robotics and ManufacturingInternational audienceRemote monitoring is an essential task to help maintaining Earth ecosystems. A notorious example is the monitoring of riverine environments. The solution purposed in this paper is to use an electric boat (ASV - Autonomous Surface Vehicle) operating in symbiosis with a quadrotor (UAV – Unmanned Air Vehicle). We present the architecture and solutions adopted and at the same time compare it with other examples of collaborative robotics systems, in what we expected could be used as a survey for other persons doing collaborative robotics systems. The architecture here purposed will exploit the symbiotic partnership between both robots by covering the perception, navigation, coordination, and integration aspects

Prototype Design of Unmanned Surface Ship to Detect Illegal Fishing Using Solar Power Generation Technology

This paper describes the prototype and implementation of the unmanned surface ship to detect illegal fishing using solar power generation technology. Indonesia, one of the Southeast Asian countries, has some of the world’s most productive fishing grounds. Under the leadership of President Joko Widodo, Indonesia has launched a severe crackdown on illegal fishing in its waters. The color tracking technique is the capability to take a picture, segregate a specific color, and extricate data regarding the location of that picture containing merely that color. Whilst processing the pixels in a vision, the CMUcam5 controls a counter that keeps tracking the number of consecutive pixels in the current row before being within the tracked color bounds. The current pixel is marked as a tracked pixel only when the value is higher than the noise filter value. The team has developed innovative features to complete the program. The features are double hull and propulsion design, automatic cooling system, automatic camera scanning using pixy CMUcam5 for image processing, Webcam video camera, voice command with system recognition intelligent software, fuel engine speed maximum 50 km/h, double fin, solar panel for supply battery, and computerized control. In the screen base station, we can see the situation of PTS Siluman Ship from serial communication microcontroller, serial communication image processing CMUCam 5, video webcam, GPS, and compass. All of the data from PTS Siluman Ship are sent online

Environmental modeling with precision navigation using ROAZ autonomous surface vehicle

The use of robotic vehicles for environmental modeling is discussed. This paper presents diverse results in autonomous marine missions with the ROAZ autonomous surface vehicle. The vehicle can perform autonomous missions while gathering marine data with high inertial and positioning precision. The underwater world is an, economical and environmental, asset that need new tools to study and preserve it. ROAZ is used in marine environment missions since it can sense and monitor the surface and underwater scenarios. Is equipped with a diverse set of sensors, cameras and underwater sonars that generate 3D environmental models. It is used for study the marine life and possible underwater wrecks that can pollute or be a danger to marine navigation. The 3D model and integration of multibeam and sidescan sonars represent a challenge in nowadays. Adding that it is important that robots can explore an area and make decisions based on their surroundings and goals. Regard that, autonomous robotic systems can relieve human beings of repetitive and dangerous tasks

A HADOOP-ENABLED SENSOR-ORIENTED INFORMATION SYSTEM FOR KNOWLEDGE DISCOVERY ABOUT TARGET-OF-INTEREST

To obtain a real-time situational awareness about the specific behavior of targets-of-interest using large-scale sensory data-set, this paper presents a generic sensor-oriented information system based on Hadoop Ecosystem, which is denoted as SOIS-Hadoop for simplicity.  Robotic heterogeneous sensor nodes bound by wireless sensor network are used to track things-of-interest. Hadoop Ecosystem enables highly scalable and fault-tolerant acquisition, fusion and storage, retrieval, and processing of sensory data. In addition, SOIS-Hadoop employs temporally and spatially dependent mathematical model to formulate the expected behavior of targets-of-interest, based on which the observed behavior of targets can be analyzed and evaluated.  Using two real-world sensor-oriented information processing and analysis problems as examples, the mechanism of SOIS-Hadoop is also presented and validated in detail

Aquatic Invasions: Causes, Consequences, And Solutions

Invasive species represent a global threat to ecosystems, human health, and the economy. A basic knowledge of invasive species biology is crucial to understand current and future impacts and implications. The purpose of this book is to provide a broad background on invasive species, and also details on specific examples through case studies. The students in the course Aquatic Invasive Species (MAR 442) at the University of New England in Biddeford, Maine, have researched and reviewed scientific literature to educate readers about these issues. The class, comprised of twelve junior and senior Marine Science, Marine Affairs, Applied Mathematics, and Environmental Sciences students, selected the different topics, presented the material, wrote the chapters, and assembled the final versions into this book. This book cannot be all inclusive, but we think this book will provide an excellent broad overview of the most important aspects of Invasive Species Biology and might stimulate the reader to dive deeper into the material.https://dune.une.edu/marinesci_studproj/1002/thumbnail.jp

Placement and motion planning algorithms for robotic sensing systems

University of Minnesota Ph.D. dissertation. October 2014. Major: Computer Science. Advisor: Prof. Ibrahim Volkan Isler. I computer file (PDF); xxiii, 226 pages.Recent technological advances are making it possible to build teams of sensors and robots that can sense data from hard-to-reach places at unprecedented spatio-temporal scales. Robotic sensing systems hold the potential to revolutionize a diverse collection of applications such as agriculture, environmental monitoring, climate studies, security and surveillance in the near future. In order to make full use of this technology, it is crucial to complement it with efficient algorithms that plan for the sensing in these systems. In this dissertation, we develop new sensor planning algorithms and present prototype robotic sensing systems.In the first part of this dissertation, we study two problems on placing stationary sensors to cover an environment. Our objective is to place the fewest number of sensors required to ensure that every point in the environment is covered. In the first problem, we say a point is covered if it is seen by sensors from all orientations. The environment is represented as a polygon and the sensors are modeled as omnidirectional cameras. Our formulation, which builds on the well-known art gallery problem, is motivated by practical applications such as visual inspection and video-conferencing where seeing objects from all sides is crucial. In the second problem, we study how to deploy bearing sensors in order to localize a target in the environment. The sensors measure noisy bearings towards the target which can be combined to localize the target. The uncertainty in localization is a function of the placement of the sensors relative to the target. For both problems we present (i) lower bounds on the number of sensors required for an optimal algorithm, and (ii) algorithms to place at most a constant times the optimal number of sensors. In the second part of this dissertation, we study motion planning problems for mobile sensors. We start by investigating how to plan the motion of a team of aerial robots tasked with tracking targets that are moving on the ground. We then study various coverage problems that arise in two environmental monitoring applications: using robotic boats to monitor radio-tagged invasive fish in lakes, and using ground and aerial robots for data collection in precision agriculture. We formulate the coverage problems based on constraints observed in practice. We also present the design of prototype robotic systems for these applications. In the final problem, we investigate how to optimize the low-level motion of the robots to minimize their energy consumption and extend the system lifetime.This dissertation makes progress towards building robotic sensing systems along two directions. We present algorithms with strong theoretical performance guarantees, often by proving that our algorithms are optimal or that their costs are at most a constant factor away from the optimal values. We also demonstrate the feasibility and applicability of our results through system implementation and with results from simulations and extensive field experiments

Adaptive Path Planning for Depth Constrained Bathymetric Mapping with an Autonomous Surface Vessel

This paper describes the design, implementation and testing of a suite of algorithms to enable depth constrained autonomous bathymetric (underwater topography) mapping by an Autonomous Surface Vessel (ASV). Given a target depth and a bounding polygon, the ASV will find and follow the intersection of the bounding polygon and the depth contour as modeled online with a Gaussian Process (GP). This intersection, once mapped, will then be used as a boundary within which a path will be planned for coverage to build a map of the Bathymetry. Methods for sequential updates to GP's are described allowing online fitting, prediction and hyper-parameter optimisation on a small embedded PC. New algorithms are introduced for the partitioning of convex polygons to allow efficient path planning for coverage. These algorithms are tested both in simulation and in the field with a small twin hull differential thrust vessel built for the task.Comment: 21 pages, 9 Figures, 1 Table. Submitted to The Journal of Field Robotic

Data driven modeling and simulation about carp aggregation

Asian carp is notorious as one of the most severe aquatic invasive species (AIS) threats to the waters of the Mississippi River Region. The devastating effect of Asian carp calls for desperate measures to decrease the spread of Asian carp and prevent possible invasion into the Great Lake. This work presents an agent-based mathematical model to simulate the aggregation of Asian carp which would provide valuable help in fish removal or control. The referred mathematical model is derived from the following assumptions: (1) the aggregation results from a completely random and spontaneous physical behavior of numerous independent carp rather than consensus among every carp involved in the aggregation; (2) carp aggregation is a collective effect of inter-carp and carp-environment interaction; (3) aggregation happens when two carp or two schools of carp approach each other within a perceptible distance. As a variant of the molecular dynamics method, the proposed mathematical model is based on an empirical inter-carp force field which is featured with repulsion, parallel orientation and attraction zone. Besides, due to the physical limitation of carp, we also considered out-of-perception zone and a blind zone. By employing an inter-carp force field, the aggregation behavior of carp is investigated. Preliminary simulation results about the aggregation of a small number of carp within a simple environment are provided. Further experiment-based validation about the mathematical model is also briefly discussed and further suggested as possible future work