Distributed approach for coverage and patrolling missions with a team of heterogeneous aerial robots under communication constraints

Using aerial robots in area coverage applications is an emerging topic. These applications need a coverage path planning algorithm and a coordinated patrolling plan. This paper proposes a distributed approach to coordinate a team of heterogeneous UAVs cooperating efficiently in patrolling missions around irregular areas, with low communication ranges and memory storage requirements. Hence it can be used with small‐scale UAVs with limited and different capabilities. The presented system uses a modular architecture and solves the problem by dividing the area between all the robots according to their capabilities. Each aerial robot performs a decomposition based algorithm to create covering paths and a ’one‐to‐one’ coordination strategy to decide the path segment to patrol. The system is decentralized and fault‐tolerant. It ensures a finite time to share information between all the robots and guarantees convergence to the desired steady state, based on the maximal minimum frequency criteria. A set of simulations with a team of quad‐rotors is used to validate the approach

When Patrolmen Become Corrupted: Monitoring a Graph Using Faulty Mobile Robots

A team of k mobile robots is deployed on a weighted graph whose edge weights represent distances. The robots move perpetually along the domain, represented by all points belonging to the graph edges, without exceeding their maximum speed. The robots need to patrol the graph by regularly visiting all points of the domain. In this paper, we consider a team of robots (patrolmen), at most f of which may be unreliable, i.e., they fail to comply with their patrolling duties. What algorithm should be followed so as to minimize the maximum time between successive visits of every edge point by a reliable patrolman? The corresponding measure of efficiency of patrolling called idleness has been widely accepted in the robotics literature. We extend it to the case of untrusted patrolmen; we denote by Ifk(G) the maximum time that a point of the domain may remain unvisited by reliable patrolmen. The objective is to find patrolling strategies minimizing Ifk(G). We investigate this problem for various classes of graphs. We design optimal algorithms for line segments, which turn out to be surprisingly different from strategies for related patrolling problems proposed in the literature. We then use these results to study general graphs. For Eulerian graphs G, we give an optimal patrolling strategy with idleness Ifk(G)=(f+1)|E|/k, where |E| is the sum of the lengths of the edges of G. Further, we show the hardness of the problem of computing the idle time for three robots, at most one of which is faulty, by reduction from 3-edge-coloring of cubic graphs—a known NP-hard problem. A byproduct of our proof is the investigation of classes of graphs minimizing idle time (with respect to the total length of edges); an example of such a class is known in the literature under the name of Kotzig graphs

On fault tolerance and scalability of swarm robotic systems

This paper challenges the common assumption that swarm robotic systems are robust and scalable by default. We present an analysis based on both reliability modelling and experimental trials of a case study swarm performing team work, in which failures are deliberately induced. Our case study has been carefully chosen to represent a swarm task in which the overall desired system behaviour is an emergent property of the interactions between robots, in order that we can assess the fault tolerance of a self-organising system. Our findings show that in the presence of worst-case partially failed robots the overall system reliability quickly falls with increasing swarm size. We conclude that future large scale swarm systems will need a new approach to achieving high levels of fault tolerance. © 2013 Springer-Verlag

When Patrolmen Become Corrupted: Monitoring a Graph using Faulty Mobile Robots

International audienceA team of k mobile robots is deployed on a weighted graph whose edge weights represent distances. The robots perpetually move along the domain, represented by all points belonging to the graph edges, not exceeding their maximal speed. The robots need to patrol the graph by regularly visiting all points of the domain. In this paper, we consider a team of robots (patrolmen), at most f of which may be unreliable, i.e. they fail to comply with their patrolling duties. What algorithm should be followed so as to minimize the maximum time between successive visits of every edge point by a reliable patrolmen? The corresponding measure of efficiency of patrolling called idleness has been widely accepted in the robotics literature. We extend it to the case of untrusted patrolmen; we denote by Ifk (G) the maximum time that a point of the domain may remain unvisited by reliable patrolmen. The objective is to find patrolling strategies minimizing Ifk (G). We investigate this problem for various classes of graphs. We design optimal algorithms for line segments, which turn out to be surprisingly different from strategies for related patrolling problems proposed in the literature. We then use these results to study the case of general graphs. For Eulerian graphs G, we give an optimal patrolling strategy with idleness Ifk (G) = (f + 1)|E|/k, where |E| is the sum of the lengths of the edges of G. Further, we show the hardness of the problem of computing the idle time for three robots, at most one of which is faulty, by reduction from 3-edge-coloring of cubic graphs — a known NP-hard problem. A byproduct of our proof is the investigation of classes of graphs minimizing idle time (with respect to the total length of edges); an example of such a class is known in the literature under the name of Kotzig graphs

A review on multi-robot systems categorised by application domain

Literature reviews on Multi-Robot Systems (MRS) typically focus on fundamental technical aspects, like coordination and communication, that need to be considered in order to coordinate a team of robots to perform a given task effectively and efficiently. Other reviews only consider works that aim to address a specific problem or one particular application of MRS. In contrast, this paper presents a survey of recent research works on MRS and categorises them according to their application domain. Furthermore, this paper compiles a number of seminal review works that have proposed specific taxonomies in classifying fundamental concepts, such as coordination, architecture and communication, in the field of MRS.peer-reviewe

Effective Cooperation and Scalability in Multi-Robot Teams for Automatic Patrolling of Infrastructures

Tese de doutoramento em Engenharia Electrotécnica e de Computadores, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Faculdade de Ciências e Tecnologia da Universidade de CoimbraIn the digital era that we live in, advances in technology have proliferated throughout our society, quickening the completion of tasks that were painful in the old days, improving solutions to the everyday problems that we face, and generally assisting human beings both in their professional and personal life. Robotics is a clear example of a broad technological field that evolves every day. In fact, scientists predict that in the upcoming few decades, robots will naturally interact and coexist alongside human beings. While it is true that robots already have a strong presence in industrial environments, e.g., robotic arms for manufacturing, the average person still looks upon robots with suspicion, since they are not acquainted by such type of technology. In this thesis, the author deploys teams of mobile robots in indoor scenarios to cooperatively perform patrolling missions, which represents an effort to bring robots closer to humans and assist them in monotonous or repetitive tasks, such as supervising and monitoring indoor infrastructures or simply cooperatively cleaning floors. In this context, the team of robots should be able to sense the environment, localize and navigate autonomously between way points while avoiding obstacles, incorporate any number of robots, communicate actions in a distributed way and being robust not only to agent failures but also communication failures, so as to effectively coordinate to achieve optimal collective performance. The referred capabilities are an evidence that such systems can only prove their reliability in real-world environments if robots are endowed with intelligence and autonomy. Thus, the author follows a line of research where patrolling units have the necessary tools for intelligent decision-making, according to the information of the mission, the environment and teammates' actions, using distributed coordination architectures. An incremental approach is followed. Firstly, the problem is presented and the literature is deeply studied in order to identify potential weaknesses and research opportunities, backing up the objectives and contributions proposed in this thesis. Then, problem fundamentals are described and benchmarking of multi-robot patrolling algorithms in realistic conditions is conducted. In these earlier stages, the role of different parameters of the problem, like environment connectivity, team size and strategy philosophy, will become evident through extensive empirical results and statistical analysis. In addition, scalability is deeply analyzed and tied with inter-robot interference and coordination, imposed by each patrolling strategy. After gaining sensibility to the problem, preliminary models for multi-robot patrol with special focus on real-world application are presented, using a Bayesian inspired formalism. Based on these, distributed strategies that lead to superior team performance are described. Interference between autonomous agents is explicitly dealt with, and the approaches are shown to scale to large teams of robots. Additionally, the robustness to agent and communication failures is demonstrated, as well as the flexibility of the model proposed. In fact, by later generalizing the model with learning agents and maintaining memory of past events, it is then shown that these capabilities can be inherited, while at the same time increasing team performance even further and fostering adaptability. This is verified in simulation experiments and real-world results in a large indoor scenario. Furthermore, since the issue of team scalability is highly in focus in this thesis, a method for estimating the optimal team size in a patrolling mission, according to the environment topology is proposed. Upper bounds for team performance prior to the mission start are provided, supporting the choice of the number of robots to be used so that temporal constraints can be satisfied. All methods developed in this thesis are tested and corroborated by experimental results, showing the usefulness of employing cooperative teams of robots in real-world environments and the potential for similar systems to emerge in our society.FCT - SFRH/BD/64426/200

МОБІЛЬНА КІБЕРФІЗИЧНА СИСТЕМА ДЛЯ ДИНАМІЧНОГО ВІДОБРАЖЕННЯ ІНФОРМАЦІЇ ПРО ОБ'ЄКТИ НА ЦИФРОВІЙ КАРТІ МІСЦЕВОСТІ

Cyber-physical systems (CPS) refer to a promising class of systems featuring intimate coupling between the "cyber" intelligence and the "physical" world. Cyber-physical systems are advanced engineering systems where computing and communication are carefully designed to achieve intimate integration with the physical dynamics. One of the types of cyber-physical systems where system components are able to dynamically change your location is a mobile CPS. Computing platforms for implementing mobile CPS are personal mobile devices. Mobile CPS integrates distributed sensing with computing and ubiquitous connectivity of the Internet. Mobile CPS also coordinates computational, virtual, and physical resources and facilitates the interaction of digital world with physical world, potentially driving the pervasive effect in the citizens' everyday life anytime and anywhere. Thus, mobile CPS could provide a convenient and economical platform that facilitates sophisticated and ubiquitous intelligent applications between humans and the surrounding physical world. The paper solved a scientific and practical task to develop mathematical and software for dynamic representation of information about objects on digital maps; analysis approaches for visualization objects on a digital map and presented principles of data visualization using augmented reality technology. The authors proposed the method for dynamic representation of information about objects in the real world on digital map, through the prism of a personal mobile device (PMD) camera, which uses information from the sensors PMP and mapping services and representation of information using augmented reality technology. We also proposed the architecture and implemented a mobile cyber-physical system for dynamic representation of information about objects on the digital map areas for PMD an Android-based operating system, programming language Java, Android API and Google Maps API.С каждым годом реальный и виртуальный миры становятся все ближе друг к другу, образуя техническую базу киберфизических систем. Киберфизическая система объединяет кибернетическое и физическое пространства, интегрируя вычислительные и физические процессы с помощью датчиков и исполнительных устройств. Одним из видов киберфизических систем, в которых компоненты системы способны динамически изменять свое местоположение, являются мобильные киберфизические системы, а вычислительной платформой для их реализации служат персональные мобильные устройства. Решена научно-практическая задача по разработке математического и программного обеспечения для динамического отображении информации об объектах на цифровой карте местности; проведен анализ подходов к визуализации объектов на цифровой карте местности и представлены принципы визуализации данных с использованием технологии дополненной реальности; предложен метод для динамического отображения информации об объектах реального мира на цифровой карте местности, через призму камеры персонального мобильного устройства (ПМУ), использующий данные с картографических сервисов и датчиков ПМУ, отображая информацию с использованием технологии дополненной реальности; разработана архитектура и реализована мобильная киберфизическая система (МКФС) для динамического отображения информации об объектах на цифровой карте местности для ПМУ на базе операционной системы Android с использованием языка программирования Java, Android API и Google Maps API.З кожним роком реальний і віртуальний світи стають все ближчі один до одного, утворюючи технічну базу кіберфізичних систем. Кіберфізична система об'єднує кібернетичний та фізичний простори, інтегруючи обчислювальні та фізичні процеси за допомогою давачів і виконавчих пристроїв. Одним із видів кіберфізичних систем, у яких компоненти системи здатні динамічно змінювати своє місцезнаходження, є мобільні кіберфізичні системи, а обчислювальною платформою для їх реалізації слугують персональні мобільні пристрої. Розв'язано науково-практичну задачу щодо розроблення математичного та програмного забезпечення для динамічного відображення інформації про об'єкти на цифровій карті місцевості; проаналізовано підходи до візуалізації об'єктів на цифровій карті місцевості та подано принципи візуалізації даних із використанням технології доповненої реальності; запропоновано метод для динамічного відображення інформації про об'єкти реального світу на цифровій карті місцевості, через призму камери персонального мобільного пристрою (ПМП), що використовує дані із картографічних сервісів та давачів ПМП, відображаючи інформацію із використанням технології доповненої реальності; розроблено архітектуру та реалізовано мобільну кіберфізичну систему (МКФС) для динамічного відображення інформації про об'єкти на цифровій карті місцевості для ПМП на базі операційної системи Android із використанням мови програмування Java, Android API та Google Maps API

Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

Performance Guarantee of a Sub-Optimal Policy for a Discrete Markov Decision Process and Its Application to a Robotic Surveillance Problem

This dissertation deals with the development and analysis of sub-optimal decision algorithms for a collection of robots that assist a remotely located operator in perimeter surveillance. The operator is tasked with the classification of incursions across the perimeter. Whenever there is an incursion into the perimeter, a nearby Unattended Ground Sensor (UGS) signals an alert. A robot services the alert by visiting the alert location, collecting evidence in the form of video imagery, and transmitting it to the operator. The accuracy of operator's classification depends on the volume and freshness of information gathered and provided by the robots at locations where incursions occur. There are two competing needs for a robot: it needs to spend adequate time at an alert location to collect evidence for aiding the operator in accurate classification but it also needs to service other alerts as soon as possible, so that the evidence collected is relevant. The control problem is to determine the optimal amount of time a robot must spend servicing an alert. The incursions are stochastic and their statistics are assumed to be known. The control problem may be posed as a Markov Decision Problem (MDP). Dynamic Programming(DP) provides the optimal policy to the MDP. However, because of the "curse of dimensionality" of DP, finding the optimal policy is not practical in many applications. For a perimeter surveillance problem with two robots and five UGS locations, the number of states is of the order of billions. Approximate Dynamic Programming (ADP) via Linear Programming (LP) provides a way to approximate the value function and derive sub-optimal strategies. Using state partitioning and ADP, this dissertation provides different LP formulations for upper and lower bounds to the value function of the MDP, and shows the relationship between LPs and MDP. The novel features of this dissertation are (1) the derivation of a tractable lower bound via LP and state partitioning, (2) the construction of a sub-optimal policy whose performance exceeds the lower bound, and (3) the derivation of an upper bound using a non-linear programming formuation. The upper and lower bounds provides approximation ratio to the value function. Finally, illustrative perimeter surveillance examples corroborate the results derived in this dissertation