Evolutionary swarm robotics: a theoretical and methodological itinerary from individual neuro-controllers to collective behaviours

In the last decade, swarm robotics gathered much attention in the research community. By drawing inspiration from social insects and other self-organizing systems, it focuses on large robot groups featuring distributed control, adaptation, high robustness, and flexibility. Various reasons lay behind this interest in similar multi-robot systems. Above all, inspiration comes from the observation of social activities, which are based on concepts like division of labor, cooperation, and communication. If societies are organized in such a way in order to be more efficient, then robotic groups also could benefit from similar paradigms

Out of reach out of touch? The impact of flexible work arrangement use on collaboration within teams

Organisations are faced with a growing interest in flexible work arrangements that enable employees to control where, when and for how long they work and need to find ways to adapt and integrate these practices into work routines and processes. Because these arrangements reduce employees’ facetime at the office, doubts remain regarding their impact on collaboration within teams. In this thesis I explore the impact of the use of part-time work, telework and flexible working hours on collaboration within teams and the contextual features that explain this relationship. Seven case studies were conducted in software development teams in three organisations in The Netherlands and Belgium. Findings suggest that telework, part-time work and flexible working hours impact on collaboration within teams because of reduced passive facetime – passive presence of team members at the office without necessarily engaging in interactions with each other. Passive facetime was interpreted as availability to others and an enabler to collaboration. A theoretical framework is put forth outlining six sets of contextual features that impact on this relationship. At the team-level, these included skill differentiation, task characteristics (task complexity and goal clarity), temporal characteristics (temporal stability and task urgency) and structural characteristics (regular face-to-face meetings, amount of absence, predictability of absence and synchronisation of presence). At the individual level, proactive behaviours were found to have an impact. Finally, the whole framework is nested in and dependent on environmental characteristics, in particular the organisational setting. This thesis contributes to theory by outlining the double-faceted role of passive facetime in the relationship between FWA use and collaboration, by delineating how structural characteristics can provide teams with sufficient passive facetime, and by presenting a framework explaining the influence of FWA use on collaboration and the features that explain how and when this happens

Capturing interpersonal coordination processes in association football : from dyads to collectives

Doutoramento em Motricidade Humana, na especialidade de Ciências do DesportoThe purpose of this thesis was to investigate how football performers coordinate their behaviours in different levels of social organisation. We began with a position paper proposing the re-conceptualisation of sport teams as functional integrated superorganisms to frame a deeper understanding of the interpersonal coordination processes emerging between team players. Time-motion analysis procedures and innovative tools were developed and presented in order to capture the superorganismic properties of sports teams and the interpersonal coordination tendencies developed by players. These tendencies were captured and analysed in representative 1vs1 and 3vs3 sub-phases, as well as in the 11-a-side game format. Data showed higher levels of variability at the individual level compared to the team level. This finding suggested that micro-variability may contribute to stabilise the behavioural dynamics at the collective level. Moreover, the specificities of the interpersonal coordination tendencies displayed within attacking-defending dyads demonstrated to have influenced the performance outcome. Attacking players tend to succeed when they were more synchronised in space and time with the defenders, and their interaction were more unpredictable/irregular. Besides, the time-evolving dynamics of the collective behaviours (i.e., at 11-a-side level) during competitive football performance indicated a tendency for an increase in the predictability (i.e., more regularity). These data were interpreted as evidencing co-adaptation processes between opponent players, which suggest that team players may shift from prevalent explorative and irregular behaviours to more predictable behaviours emerging due changes in their functional movement possibilities. However, some game events such as goals scored, halftime and stoppages in play seemed to break this continuum and acted as relevant performance constraints.FCT - Fundação para Ciência e a Tecnologi

Fault Recovery in Swarm Robotics Systems using Learning Algorithms

When faults occur in swarm robotic systems they can have a detrimental effect on collective behaviours, to the point that failed individuals may jeopardise the swarm's ability to complete its task. Although fault tolerance is a desirable property of swarm robotic systems, fault recovery mechanisms have not yet been thoroughly explored. Individual robots may suffer a variety of faults, which will affect collective behaviours in different ways, therefore a recovery process is required that can cope with many different failure scenarios. In this thesis, we propose a novel approach for fault recovery in robot swarms that uses Reinforcement Learning and Self-Organising Maps to select the most appropriate recovery strategy for any given scenario. The learning process is evaluated in both centralised and distributed settings. Additionally, we experimentally evaluate the performance of this approach in comparison to random selection of fault recovery strategies, using simulated collective phototaxis, aggregation and foraging tasks as case studies. Our results show that this machine learning approach outperforms random selection, and allows swarm robotic systems to recover from faults that would otherwise prevent the swarm from completing its mission. This work builds upon existing research in fault detection and diagnosis in robot swarms, with the aim of creating a fully fault-tolerant swarm capable of long-term autonomy

Simulation based team training in surgery - A review

The healthcare environment in surgery is complex, dynamic and often ambiguous. Besides subject knowledge and technical skills, other competencies, such as team work, communication skills and situation awareness, are required to ensure better patient-related outcome. Teams that demonstrate poor non-technical skills make more technical errors, often resulting in patient morbidity or mortality. Different hospital-based locations, such as operating rooms, intensive care units, emergency rooms and surgical wards, are the areas where poor team dynamics prevail. Simulation-based team training is a strategy to provide inter-professional training and experiential learning opportunities for surgeons, anaesthetists and allied health professionals. It helps them to effectively respond in complex situations in complex surgical environment. Simulation-based team training has 3 components; didactics, simulation itself, and debriefing. Literature has shown that simulation-based team training in surgery improves identification of team-based behaviours, improves team performance and overall patient safety

Collective behaviour monitoring in football using spatial temporal and network analysis: application and evaluations.

Analysis is an important part of understanding and exploiting performance of football teams. Traditional approaches of analysis have centred around events that may not fully incorporate the highly dynamic nature of matches. To circumvent this weakness, applications of collective behaviour metrics applying spatial temporal and social network analyses to data in football have been trending over the last 10 years. The aims of this PhD were to: 1) establish the strengths and limitations of current research investigating collective behaviour in football applying novel analytical procedures; 2) investigate the credibility of present methods informing coaching practice; and 3) provide guidance for practitioners in implementing complex analytical procedures with current data collection methods. These aims were achieved through the completion of five interlinked studies. The first two studies comprised systematic reviews evaluating the quality of previous research investigating collective behaviours. The first systematic review focussed on spatial temporal metrics and the second systematic review focussed on social network analysis metrics. In addition to standard review procedures, both systematic reviews included analyses of author quotes regarding the metrics used within each study. These included description and conceptualisation of each metric, along with practical applications and measurements of reliability. The first systematic review identified several limitations in the current literature base of spatial temporal metrics investigating collective behaviour in football. These included a lack of conceptualisation of the metrics used, assumptions of metric reliability, frequent use of broad and non-actionable practical recommendations, failure to justify sample sizes and a bias towards including males. Similar findings were found in the social network analysis systematic review where authors also seldom conceptualised metrics, provided vague practical applications and often failed to justify sample size. Literature including social network analysis were also inconsistent with the metric calculations and nearly all studies investigated elite male matches. The third study in this PhD attempted to quantify the reliability of spatial temporal metrics by simulating expected error values on top of real-world data. Through fitting linear mixed effects models on signal to noise ratios, metrics were established to be reliable where positioning systems are accurate to 0.5 m or less. In situations where positioning systems errors were approached 2 m, only some were considered to produce reliable values, (e.g. team centroid), whereas metrics using distances and numerical relations were considered to produce unreliable values. After assessing the literature and reliability, the PhD focussed on implementation of common and reliable metrics, leading into the final study of the PhD which employed an iterative design comprising multiple interviews to investigate coach perceptions of collective behaviour metrics. A thematic analysis identified themes that closely resembled the 10 traditional principles of play in football, further establishing their validity. Moreover, coaches reacted positively to presented measurements, most notable network intensity, distance between defenders, triads, team length, and team depth. Coaches stated they trained players with the concepts these measurements represent as a central focus. The PhD work was concluded with a final chapter set as pedagogical support for practitioners wishing to implement these techniques providing a guide to measuring the tactical concepts discussed within this thesis. Collectively, this PhD highlights that novel collective behaviour metrics have a place in current performance analysis systems in football. Additionally, a methodology is presented for practitioners to apply to their own teams and generate specific metrics relevant to the teams own tactical principles

A generic holonic control architecture for heterogeneous multi-scale and multi-objective smart microgrids

Designing the control infrastructure of future “smart” power grids is a challenging task. Future grids will integrate a wide variety of heterogeneous producers and consumers that are unpredictable and operate at various scales. Information and Communication Technology (ICT) solutions will have to control these in order to attain global objectives at the macrolevel, while also considering private interests at the microlevel. This article proposes a generic holonic architecture to help the development of ICT control systems that meet these requirements. We show how this architecture can integrate heterogeneous control designs, including state-of-the-art smart grid solutions. To illustrate the applicability and utility of this generic architecture, we exemplify its use via a concrete proof-of-concept implementation for a holonic controller, which integrates two types of control solutions and manages a multiscale, multiobjective grid simulator in several scenarios. We believe that the proposed contribution is essential for helping to understand, to reason about, and to develop the “smart” side of future power grids

Harnessing Knowledge, Innovation and Competence in Engineering of Mission Critical Systems

This book explores the critical role of acquisition, application, enhancement, and management of knowledge and human competence in the context of the largely digital and data/information dominated modern world. Whilst humanity owes much of its achievements to the distinct capability to learn from observation, analyse data, gain insights, and perceive beyond original realities, the systematic treatment of knowledge as a core capability and driver of success has largely remained the forte of pedagogy. In an increasingly intertwined global community faced with existential challenges and risks, the significance of knowledge creation, innovation, and systematic understanding and treatment of human competence is likely to be humanity's greatest weapon against adversity. This book was conceived to inform the decision makers and practitioners about the best practice pertinent to many disciplines and sectors. The chapters fall into three broad categories to guide the readers to gain insight from generic fundamentals to discipline-specific case studies and of the latest practice in knowledge and competence management

A field-based computing approach to sensing-driven clustering in robot swarms

Swarm intelligence leverages collective behaviours emerging from interaction and activity of several “simple” agents to solve problems in various environments. One problem of interest in large swarms featuring a variety of sub-goals is swarm clustering, where the individuals of a swarm are assigned or choose to belong to zero or more groups, also called clusters. In this work, we address the sensing-based swarm clustering problem, where clusters are defined based on both the values sensed from the environment and the spatial distribution of the values and the agents. Moreover, we address it in a setting characterised by decentralisation of computation and interaction, and dynamicity of values and mobility of agents. For the solution, we propose to use the field-based computing paradigm, where computation and interaction are expressed in terms of a functional manipulation of fields, distributed and evolving data structures mapping each individual of the system to values over time. We devise a solution to sensing-based swarm clustering leveraging multiple concurrent field computations with limited domain and evaluate the approach experimentally by means of simulations, showing that the programmed swarms form clusters that well reflect the underlying environmental phenomena dynamics