Evolutionary Robot Swarms Under Real-World Constraints

Tese de doutoramento em Engenharia Electrotécnica e de Computadores, na especialidade de Automação e Robótica, apresentada ao Departamento de Engenharia Electrotécnica e de Computadores da Faculdade de Ciências e Tecnologia da Universidade de CoimbraNas últimas décadas, vários cientistas e engenheiros têm vindo a estudar as estratégias provenientes da natureza. Dentro das arquiteturas biológicas, as sociedades que vivem em enxames revelam que agentes simplistas, tais como formigas ou pássaros, são capazes de realizar tarefas complexas usufruindo de mecanismos de cooperação. Estes sistemas abrangem todas as condições necessárias para a sobrevivência, incorporando comportamentos de cooperação, competição e adaptação. Na “batalha” sem fim em prol do progresso dos mecanismos artificiais desenvolvidos pelo homem, a ciência conseguiu simular o primeiro comportamento em enxame no final dos anos oitenta. Desde então, muitas outras áreas, entre as quais a robótica, beneficiaram de mecanismos de tolerância a falhas inerentes da inteligência coletiva de enxames. A área de investigação deste estudo incide na robótica de enxame, consistindo num domínio particular dos sistemas robóticos cooperativos que incorpora os mecanismos de inteligência coletiva de enxames na robótica. Mais especificamente, propõe-se uma solução completa de robótica de enxames a ser aplicada em contexto real. Nesta ótica, as operações de busca e salvamento foram consideradas como o caso de estudo principal devido ao nível de complexidade associado às mesmas. Tais operações ocorrem tipicamente em cenários dinâmicos de elevadas dimensões, com condições adversas que colocam em causa a aplicabilidade dos sistemas robóticos cooperativos. Este estudo centra-se nestes problemas, procurando novos desafios que não podem ser ultrapassados através da simples adaptação da literatura da especialidade em algoritmos de enxame, planeamento, controlo e técnicas de tomada de decisão. As contribuições deste trabalho sustentam-se em torno da extensão do método Particle Swarm Optimization (PSO) aplicado a sistemas robóticos cooperativos, denominado de Robotic Darwinian Particle Swarm Optimization (RDPSO). O RDPSO consiste numa arquitetura robótica de enxame distribuída que beneficia do particionamento dinâmico da população de robôs utilizando mecanismos evolucionários de exclusão social baseados na sobrevivência do mais forte de Darwin. No entanto, apesar de estar assente no caso de estudo do RDPSO, a aplicabilidade dos conceitos aqui propostos não se encontra restrita ao mesmo, visto que todos os algoritmos parametrizáveis de enxame de robôs podem beneficiar de uma abordagem idêntica. Os fundamentos em torno do RDPSO são introduzidos, focando-se na dinâmica dos robôs, nos constrangimentos introduzidos pelos obstáculos e pela comunicação, e nas suas propriedades evolucionárias. Considerando a colocação inicial dos robôs no ambiente como algo fundamental para aplicar sistemas de enxames em aplicações reais, é assim introduzida uma estratégia de colocação de robôs realista. Para tal, a população de robôs é dividida de forma hierárquica, em que são utilizadas plataformas mais robustas para colocar as plataformas de enxame no cenário de forma autónoma. Após a colocação dos robôs no cenário, é apresentada uma estratégia para permitir a criação e manutenção de uma rede de comunicação móvel ad hoc com tolerância a falhas. Esta estratégia não considera somente a distância entre robôs, mas também a qualidade do nível de sinal rádio frequência, redefinindo assim a sua aplicabilidade em cenários reais. Os aspetos anteriormente mencionados estão sujeitos a uma análise detalhada do sistema de comunicação inerente ao algoritmo, para atingir uma implementação mais escalável do RDPSO a cenários de elevada complexidade. Esta elevada complexidade inerente à dinâmica dos cenários motivaram a ultimar o desenvolvimento do RDPSO, integrando para o efeito um mecanismo adaptativo baseado em informação contextual (e.g., nível de atividade do grupo). Face a estas considerações, o presente estudo pode contribuir para expandir o estado-da-arte em robótica de enxame com algoritmos inovadores aplicados em contexto real. Neste sentido, todos os métodos propostos foram extensivamente validados e comparados com alternativas, tanto em simulação como com robôs reais. Para além disso, e dadas as limitações destes (e.g., número limitado de robôs, cenários de dimensões limitadas, constrangimentos reais limitados), este trabalho contribui ainda para um maior aprofundamento do estado-da-arte, onde se propõe um modelo macroscópico capaz de capturar a dinâmica inerente ao RDPSO e, até certo ponto, estimar analiticamente o desempenho coletivo dos robôs perante determinada tarefa. Em suma, esta investigação pode ter aplicabilidade prática ao colmatar a lacuna que se faz sentir no âmbito das estratégias de enxames de robôs em contexto real e, em particular, em cenários de busca e salvamento.Over the past decades, many scientists and engineers have been studying nature’s best and time-tested patterns and strategies. Within the existing biological architectures, swarm societies revealed that relatively unsophisticated agents with limited capabilities, such as ants or birds, were able to cooperatively accomplish complex tasks necessary for their survival. Those simplistic systems embrace all the conditions necessary to survive, thus embodying cooperative, competitive and adaptive behaviours. In the never-ending battle to advance artificial manmade mechanisms, computer scientists simulated the first swarm behaviour designed to mimic the flocking behaviour of birds in the late eighties. Ever since, many other fields, such as robotics, have benefited from the fault-tolerant mechanism inherent to swarm intelligence. The area of research presented in this Ph.D. Thesis focuses on swarm robotics, which is a particular domain of multi-robot systems (MRS) that embodies the mechanisms of swarm intelligence into robotics. More specifically, this Thesis proposes a complete swarm robotic solution that can be applied to real-world missions. Although the proposed methods do not depend on any particular application, search and rescue (SaR) operations were considered as the main case study due to their inherent level of complexity. Such operations often occur in highly dynamic and large scenarios, with harsh and faulty conditions, that pose several problems to MRS applicability. This Thesis focuses on these problems raising new challenges that cannot be handled appropriately by simple adaptation of state-of-the-art swarm algorithms, planning, control and decision-making techniques. The contributions of this Thesis revolve around an extension of the Particle Swarm Optimization (PSO) to MRS, denoted as Robotic Darwinian Particle Swarm Optimization (RDPSO). The RDPSO is a distributed swarm robotic architecture that benefits from the dynamical partitioning of the whole swarm of robots by means of an evolutionary social exclusion mechanism based on Darwin’s survival-of-the-fittest. Nevertheless, although currently applied solely to the RDPSO case study, the applicability of all concepts herein proposed is not restricted to it, since all parameterized swarm robotic algorithms may benefit from a similar approach The RDPSO is then proposed and used to devise the applicability of novel approaches. The fundamentals around the RDPSO are introduced by focusing on robots’ dynamics, obstacle avoidance, communication constraints and its evolutionary properties. Afterwards, taking the initial deployment of robots within the environment as a basis for applying swarm robotics systems into real-world applications, the development of a realistic deployment strategy is proposed. For that end, the population of robots is hierarchically divided, wherein larger support platforms autonomously deploy smaller exploring platforms in the scenario, while considering communication constraints and obstacles. After the deployment, a way of ensuring a fault-tolerant multi-hop mobile ad hoc communication network (MANET) is introduced to explicitly exchange information needed in a collaborative realworld task execution. Such strategy not only considers the maximum communication range between robots, but also the minimum signal quality, thus refining the applicability to real-world context. This is naturally followed by a deep analysis of the RDPSO communication system, describing the dynamics of the communication data packet structure shared between teammates. Such procedure is a first step to achieving a more scalable implementation by optimizing the communication procedure between robots. The highly dynamic characteristics of real-world applications motivated us to ultimate the RDPSO development with an adaptive strategy based on a set of context-based evaluation metrics. This thesis contributes to the state-of-the-art in swarm robotics with novel algorithms for realworld applications. All of the proposed approaches have been extensively validated in benchmarking tasks, in simulation, and with real robots. On top of that, and due to the limitations inherent to those (e.g., number of robots, scenario dimensions, real-world constraints), this Thesis further contributes to the state-of-the-art by proposing a macroscopic model able to capture the RDPSO dynamics and, to some extent, analytically estimate the collective performance of robots under a certain task. It is the author’s expectation that this Ph.D. Thesis may shed some light into bridging the reality gap inherent to the applicability of swarm strategies to real-world scenarios, and in particular to SaR operations.FCT - SFRH/BD /73382/201

A Novel Feature Selection Approach Based on FODPSO and SVM

A novel feature selection approach is proposed to address the curse of dimensionality and reduce the redundancy of hyperspectral data. The proposed approach is based on a new binary optimization method inspired by fractional-order Darwinian particle swarm optimization (FODPSO). The overall accuracy (OA) of a support vector machine (SVM) classifier on validation samples is used as fitness values in order to evaluate the informativity of different groups of bands. In order to show the capability of the proposed method, two different applications are considered. In the first application, the proposed feature selection approach is directly carried out on the input hyperspectral data. The most informative bands selected from this step are classified by the SVM. In the second application, the main shortcoming of using attribute profiles (APs) for spectral-spatial classification is addressed. In this case, a stacked vector of the input data and an AP with all widely used attributes are created. Then, the proposed feature selection approach automatically chooses the most informative features from the stacked vector. Experimental results successfully confirm that the proposed feature selection technique works better in terms of classification accuracies and CPU processing time than other studied methods without requiring the number of desired features to be set a priori by users.IEEE Geoscience and Remote Sensing SocietyRitrýnt tímaritPeer Reviewe

Dispositivo eletrónico para aquisição e processamento de múltiplos sinais fisiológicos e ambientais

Os sistemas de saúde atuais estão estruturados e otimizados para reagir a crises e para a gestão de doenças, no entanto enfrentam atualmente um novo desafio, a crescente população idosa (Carrilho, 2015). Este facto sugere que a prestação de cuidados de saúde requer uma mudança significativa na direção de soluções mais flexíveis e adaptáveis às necessidades emergentes. A reestruturação dos sistemas de cuidados de saúde poderá permitir, uma mudança de foco para uma gestão mais pró-ativa do bem-estar, em vez da gestão da doença. Deste modo, poderá ser possível a intervenção de profissionais na prevenção e deteção precoce das patologias. Os sistemas portáteis para a monitorização contínua de saúde poderão ser, portanto, uma tecnologia chave para ajudar na transição para cuidados de saúde mais preventivos, mais acessíveis por contraponto com os cuidados de saúde curativos e tendencialmente mais caros. Este projeto discute a implementação e descrição da arquitetura de um protótipo de uma rede de sensores para monitorização de sinais fisiológicos e ambientais com base em componentes comerciais. Os nós da rede são compatíveis com redes de sensores sem fio Bluetooth 4.0 Low Energy. Este trabalho, apresenta ainda a arquitetura do sistema em termos de hardware bem como a arquitetura de firmware e software implementada. É apresentada também uma possível solução de software para visualização dos dados adquiridos. Foi igualmente realizada uma introdução ao processo de certificação e qualificação, de um dispositivo com a tecnologia Bluetooth. Este processo de certificação é um conjunto de procedimentos necessário para permitir colocar no mercado qualquer dispositivo baseado neste protocolo

The ARCANE Project: how an ecological dynamics framework can enhance performance assessment and prediction in football

This paper discusses how an ecological dynamics framework can be implemented to interpret data, design practice tasks and interpret athletic performance in collective sports, exemplified here by research ideas within the Augmented peRCeption ANalysis framEwork for Football (ARCANE) project promoting an augmented perception of football teams for scientists and practitioners. An ecological dynamics rationale can provide an interpretation of athletes’ positional and physiological data during performance, using new methods to assess athletes’ behaviours in real-time and, to some extent, predict health and performance outcomes. The proposed approach signals practical applications for coaches, sports analysts, exercise physiologists and practitioners through merging a large volume of data into a smaller set of variables, resulting in a deeper analysis than typical measures of performance outcomes of competitive games

Towards a new method to analyze the soccer teams tactical behaviour : measuring the effective area of play

Recently, new tactical metrics have been developed to increase the match analysis’ potential. Naturally, innovate metrics need some updates in order to improve the utility to the soccer coaches. Thus, this paper aims to update the surface area metric, proposing the effective area of play given some efficacy information’s about team players’ positioning. Furthermore, aim analyzes the effective area of play of each team depending on the state of ball possession and a full match of 7-a-side soccer game in the district final was also analysed. Results showed an inverse correlation between teams’ opposite effective areas of play(rp = -0.681), suggesting the expansion-contraction relationship. Furthermore, was analyzed statistical differences with large effect between the moments with and without ball possession for the team A (F(1; 1506) = 1343.893; p-value ≤ 0.001; η2 = 0.472; Power = 1.000) and B (F(1; 1506) = 968.500; p-value ≤ 0.001; η2 = 0.391; Power = 1.000).info:eu-repo/semantics/publishedVersio

Soccer teams behaviors : analysis if the team distribution in function to ball possession

Innovative tools to soccer analysis are the main concern of the sport performance analysts. Considering team players occupation as one of the fundamental characteristics of soccer success, is too important generate new systems to interpret the post-match reality. These systems must be easy for the coach's applications. Thus, this study proposes an easy tool to understand the team’s collective behaviour in function to their ball possession status. Through the histograms of all team players will be possible understand the most occupied areas by each team, trying understand possible tendencies in the moments with and without ball possession. Were analyzed two teams during an official soccer match, collecting their positions at each instant. Using this tracking was possible perform two heat maps by each team, representing the moments with and without ball possession. Through this method was possible analyze different collective behaviors and explain how could coaches interpret outcomes.info:eu-repo/semantics/publishedVersio

Study of the heart rate and accuracy performance of archers

On archery performance, heart rate variability is associated to higher parasympathetic activity and a better balance of parasympathetic and sympathetic are beneficial to performance within the sport (Lo, Huang & Hung, 2008). The purpose of this study was to compare heart rate and archery accuracy in experienced and inexperienced archers as to determine if experience contributes to increased accuracy and decreased heart rate. Eighteen male individuals (23.2 ± 5.3 years) participated. The task consisted in the realization of archery, aiming to achieve higher scores corresponding to greater accuracy in target. Twelve trials were performed at two blocks (i.e., total of twenty-four trials) by each participant. At each archery attempt, we collected the heart rate immediately before the trial and the respectively accuracy of archery performance. The t-independent test showed significant statistical differences on heart rate (t(430) = - 4.135, p-value = 0.001) and score of archery performance (t(430) = 2.745, p-value = 0.006), between experienced and inexperienced archers. Experienced archers exhibit a better accuracy and at same time a less heart rate comparing to inexperienced archers. It is possible that the experience of the archers help to improve the arousal control and, consequently, balance between sympathetic and parasympathetic systems.info:eu-repo/semantics/publishedVersio

Fusing sonars and LRF data to perform SLAM in reduced visibility scenarios

Simultaneous Localization and Mapping (SLAM) approaches have evolved considerably in recent years. However, there are many situations which are not easily handled, such as the case of smoky, dusty, or foggy environments where commonly used range sensors for SLAM are highly disturbed by noise induced in the measurement process by particles of smoke, dust or steam. This work presents a sensor fusion method for range sensing in Simultaneous Localization and Mapping (SLAM) under reduced visibility conditions. The proposed method uses the complementary characteristics between a Laser Range Finder (LRF) and an array of sonars in order to ultimately map smoky environments. The method was validated through experiments in a smoky indoor scenario, and results showed that it is able to adequately cope with induced disturbances, thus decreasing the impact of smoke particles in the mapping task

A Novel Evolutionary Swarm Fuzzy Clustering Approach for Hyperspectral Imagery

In land cover assessment, classes often gradually change from one to another. Therefore, it is difficult to allocate sharp boundaries between different classes of interest. To overcome this issue and model such conditions, fuzzy techniques that resemble human reasoning have been proposed as alternatives. Fuzzy C-means is the most common fuzzy clustering technique, but its concept is based on a local search mechanism and its convergence rate is rather slow, especially considering high-dimensional problems (e.g., in processing of hyperspectral images). Here, in order to address those shortcomings of hard approaches, a new approach is proposed, i.e., fuzzy C-means which is optimized by fractional order Darwinian particle swarm optimization. In addition, to speed up the clustering process, the histogram of image intensities is used during the clustering process instead of the raw image data. Furthermore, the proposed clustering approach is combined with support vector machine classification to accurately classify hyperspectral images. The new classification framework is applied on two well-known hyperspectral data sets; Indian Pines and Salinas. Experimental results confirm that the proposed swarm-based clustering approach can group hyperspectral images accurately in a time-efficient manner compared to other existing clustering techniques.PostPrin

An online tactical metrics applied to football game

In collective sports, the match analysis is fundamental in order to improve the quality of coaches’ intervention. Nevertheless, the generality of the systems are based on notational analysis which does not allow a deep understanding about the collective behaviour of the team. Therefore, the main goal of this study is to update and design new tactical metrics that allows an improved online knowledge about the teams’ behaviour. Tactical metrics such as the teams’ centroid, teams’ stretch index and teams’ effective play area will be presented throughout this study, validated by means of a single match experimental case study. Results suggest the potential of the herein proposed tactical metrics, providing relevant and online information to the coaches over time, thus allowing new opportunities to improve the quality of their intervention.info:eu-repo/semantics/publishedVersio