Coordination and Control of Autonomous Mobile Robots Swarms by using Particle Swarm Optimization Algorithm and Consensus Theory

This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.

Nonlinear Control Strategies for Cooperative Control of Multi-Robot Systems

This thesis deals with distributed control strategies for cooperative control of multi-robot systems. Specifically, distributed coordination strategies are presented for groups of mobile robots. The formation control problem is initially solved exploiting artificial potential fields. The purpose of the presented formation control algorithm is to drive a group of mobile robots to create a completely arbitrarily shaped formation. Robots are initially controlled to create a regular polygon formation. A bijective coordinate transformation is then exploited to extend the scope of this strategy, to obtain arbitrarily shaped formations. For this purpose, artificial potential fields are specifically designed, and robots are driven to follow their negative gradient. Artificial potential fields are then subsequently exploited to solve the coordinated path tracking problem, thus making the robots autonomously spread along predefined paths, and move along them in a coordinated way. Formation control problem is then solved exploiting a consensus based approach. Specifically, weighted graphs are used both to define the desired formation, and to implement collision avoidance. As expected for consensus based algorithms, this control strategy is experimentally shown to be robust to the presence of communication delays. The global connectivity maintenance issue is then considered. Specifically, an estimation procedure is introduced to allow each agent to compute its own estimate of the algebraic connectivity of the communication graph, in a distributed manner. This estimate is then exploited to develop a gradient based control strategy that ensures that the communication graph remains connected, as the system evolves. The proposed control strategy is developed initially for single-integrator kinematic agents, and is then extended to Lagrangian dynamical systems.

Kinematics and statics of cable-driven parallel robots by interval-analysis-based methods

In the past two decades the work of a growing portion of researchers in robotics focused on a particular group of machines, belonging to the family of parallel manipulators: the cable robots. Although these robots share several theoretical elements with the better known parallel robots, they still present completely (or partly) unsolved issues. In particular, the study of their kinematic, already a difficult subject for conventional parallel manipulators, is further complicated by the non-linear nature of cables, which can exert only efforts of pure traction. The work presented in this thesis therefore focuses on the study of the kinematics of these robots and on the development of numerical techniques able to address some of the problems related to it. Most of the work is focused on the development of an interval-analysis based procedure for the solution of the direct geometric problem of a generic cable manipulator. This technique, as well as allowing for a rapid solution of the problem, also guarantees the results obtained against rounding and elimination errors and can take into account any uncertainties in the model of the problem. The developed code has been tested with the help of a small manipulator whose realization is described in this dissertation together with the auxiliary work done during its design and simulation phases.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Coordinated Control of Robotic Swarms in Unknown Environments

This thesis gathers the work carried out by the author in the last three years of research and it concerns the study and implementation of algorithms to coordinate and control a swarm of mobile robots moving in unknown environments. In particular, the author's attention is focused on two different approaches in order to solve two different problems. The first algorithm considered in this work deals with the possibility of decomposing a main complex task in many simple subtasks by exploiting the decentralized implementation of the so called \emph{Null Space Behavioral} paradigm. This approach to the problem of merging different subtasks with assigned priority is slightly modified in order to handle critical situations that can be detected when robots are moving through an unknown environment. In fact, issues can occur when one or more robots got stuck in local minima: a smart strategy to avoid deadlock situations is provided by the author and the algorithm is validated by simulative analysis. The second problem deals with the use of concepts borrowed from \emph{graph theory} to control a group differential wheel robots by exploiting the Laplacian solution of the consensus problem. Constraints on the swarm communication topology have been introduced by the use of a range and bearing platform developed at the Distributed Intelligent Systems and Algorithms Laboratory (DISAL), EPFL (Lausanne, CH) where part of author's work has been carried out. The control algorithm is validated by demonstration and simulation analysis and, later, is performed by a team of four robots engaged in a formation mission. To conclude, the capabilities of the algorithm based on the local solution of the consensus problem for differential wheel robots are demonstrated with an application scenario, where nine robots are engaged in a hunting task.

Lifelines in case of Natural Disaster Emergencies

In order to handle Natural disasters, emergency areas are often individuated over the territory, close to populated centres. In these areas, rescue services are located which respond with resources and materials for population relief. A method of automatic positioning of these centres in case of a flood or an earthquake is presented. The positioning procedure consists of two distinct parts developed by the research group of Prof Michael G. H. Bell of Imperial College, London, refined and applied to real cases at the University of Bologna under the coordination of Prof Ezio Todini. There are certain requirements that need to be observed such as the maximum number of rescue points as well as the number of people involved. Initially, the candidate points are decided according to the ones proposed by the local civil protection services. We then calculate all possible routes from each candidate rescue point to all other points, generally using the concept of the "hyperpath", namely a set of paths each one of which may be optimal. The attributes of the road network are of fundamental importance, both for the calculation of the ideal distance and eventual delays due to the event measured in travel time units. In a second phase, the distances are used to decide the optimum rescue point positions using heuristics. This second part functions by "elimination". In the beginning, all points are considered rescue centres. During every interaction we wish to delete one point and calculate the impact it creates. In each case, we delete the point that creates less impact until we reach the number of rescue centres we wish to keep.

The European External Action Service and the Implementation of the 'Union Method' in European Foreign Policy

The European External Action Service (EEAS or Service) is one of the most significant and most debated innovations introduced by the Lisbon Treaty. This analysis intends to explain the anomalous design of the EEAS in light of its function, which consists in the promotion of external action coherence. Coherence is a principle of the EU legal system, which requires synergy in the external actions of the Union and its Members. It can be enforced only through the coordination of European policy-makers' initiatives, by bridging the gap between the 'Communitarian' and intergovernmental approaches. This is the 'Union method' envisaged by A. Merkel: "coordinated action in a spirit of solidarity - each of us in the area for which we are responsible but all working towards the same goal". The EEAS embodies the 'Union method', since it is institutionally linked to both Union organs and Member States. It is also capable of enhancing synergy in policy management and promoting unity in international representation, since its field of action is delimited not by an abstract concern for institutional balance but by a pragmatic assessment of the need for coordination in each sector. The challenge is now to make sure that this pragmatic approach is applied with respect to all the activities of the Service, in order to reinforce its effectiveness. The coordination brought by the EEAS is in fact the only means through which a European foreign policy can come into being: the choice is not between the Community method and the intergovernmental method, but between a coordinated position and nothing at all.

"Tra centro e periferia" Istituzioni e processi di industrializzazione nella Sicilia del secondo dopoguerra

In Sicilia lo strumento principale che ha caratterizzato le modalità d’intervento dei poteri pubblici in economia è stato quello della partecipazione diretta o indiretta, quello cioè della Regione che si propone come ente fautore del sostegno allo sviluppo dell’industria e successivamente come soggetto imprenditore. Le formule organizzative attraverso le quali si è concretizzato l’intervento regionale in economia furono la società per azioni a partecipazione regionale, l’azienda autonoma regionale e l’ente pubblico regionale1. La storia dello sviluppo economico siciliano nel secondo dopoguerra conferma come il ricorso allo strumento dell’ente pubblico economico sia stato molto frequente nella realtà locale come, peraltro, anche in altre Regioni d’Italia. Tracce, queste, di una vicenda storica che intuiamo subito avere complesse implicazioni tali da generare la necessità di interrogarsi sul modo nel quale le istituzioni politiche hanno influito sulle dinamiche economiche siciliane nel secondo dopoguerra; per quanto noti e approfonditi siano stati infatti gli elementi caratterizzanti e i percorsi peculiari dello sviluppo economico siciliano, rimangono scarsamente approfonditi il tenore dei rapporti e i nessi politici, istituzionali ed economici tra centro e periferia, in altre parole rimane ancora parzialmente inesplorata quella parte dell’indagine inerente l’evoluzione dei processi di industrializzazione della Sicilia nel secondo dopoguerra attuata parallelamente dalle autorità regionali e dallo Stato attraverso i loro enti e strumenti. È lecito chiedersi quali siano stati i tempi, le modalità, gli ostacoli e gli eventuali risultati delle azioni di pianificazione intraprese dai poteri pubblici centrali e regionali nella prospettiva dello sviluppo economico del territorio; il coordinamento delle azioni di promozione del progresso industriale si presentava in tal senso, sin dall’inizio, come una delle sfide fondamentali per un adeguato e consistente rilancio economico delle aree più arretrate del Mezzogiorno italiano; ecco che lo studio dei provvedimenti legislativi emanati rappresenta un approfondimento indispensabile e obiettivo primario di questo lavoro.

Transcriptional dynamics of the human DMD locus

The human DMD locus encodes dystrophin protein. Absence or reduced levels of dystrophin (DMD or BMD phenotype, respectively) lead to progressive muscle wasting. Little is known about the complex coordination of dystrophin expression and its transcriptional regulation is a field of intense interest. In this work we found that DMD locus harbours multiple long non coding RNAs which orchestrate and control transcription of muscle dystrophin mRNA isoforms. These lncRNAs are tissue-specific and highly expressed during myogenesis, suggesting a possible role in tissue-specific expression of DMD gene isoforms. Their forced ectopic expression in human muscle and neuronal cells leads to a specific and negative regulation of endogenous dystrophin full lenght isoforms. An intriguing aspect regarding the transcription of the DMD locus is the gene size (2.4Mb). The mechanism that ensures the complete synthesis of the primary transcript and the coordinated splicing of 79 exons is still completely unknown. By ChIP-on-chip analyses, we discovered novel regions never been involved before in the transcription regulation of the DMD locus. Specifically, we observed enrichments for Pol II, P-Ser2, P-Ser5, Ac-H3 and 2Me-H3K4 in an intronic region of 3Kb (approximately 21Kb) downstream of the end of DMD exon 52 and in a region of 4Kb spanning the DMD exon 62. Interestingly, this latter region and the TSS of Dp71 are strongly marked by 3Me-H3K36, an histone modification associated with the regulation of splicing process. Furthermore, we also observed strong presence of open chromatin marks (Ac-H3 and 2Me-H3K4) around intron 34 and the exon 45 without presence of RNA pol II. We speculate that these two regions may exert an enhancer-like function on Dp427m promoter, although further investigations are necessary. Finally, we investigated the nuclear-cytoplasmic compartmentalization of the muscular dystrophin mRNA and, specifically, we verified whether the exon skipping therapy could influence its cellular distribution.

Rural governance and livelihoods systems diversification in the Western Balkans: comparative case studies of Bosnia and Herzegovina, Montenegro and Serbia

Agriculture is still important for socio-economic development in rural areas of Bosnia, Montenegro and Serbia (BMS). However, for sustainable rural development rural economies should be diversified so attention should be paid also to off-farm and non-farm income-generating activities. Agricultural and rural development (ARD) processes and farm activity diversification initiatives should be well governed. The ultimate objective of this work is to explore linkages between ARD governance and rural livelihoods diversification in BMS. The thesis is based on an extended secondary data analysis and surveys. Questionnaires for ARD governance and coordination were sent via email to public, civil society and international organizations. Concerning rural livelihood diversification, the field questionnaire surveys were carried out in three rural regions of BMS. Results show that local rural livelihoods are increasingly diversified but a significant share of households are still engaged in agriculture. Diversification strategies have a chance to succeed taking into consideration the three rural regions’ assets. However, rural households have to tackle many problems for developing new income-generating activities such as the lack of financial resources. Weak business skills are also a limiting factor. Fully exploiting rural economy diversification potential in BMS requires many interventions including improving rural governance, enhancing service delivery in rural areas, upgrading rural people’s human capital, strengthening rural social capital and improving physical capital, access of the rural population to finance as well as creating a favourable and enabling legal and legislative environment fostering diversification. Governance and coordination of ARD policy design, implementation and evaluation is still challenging in the three Balkan countries and this has repercussions also on the pace of rural livelihoods diversification. Therefore, there is a strong and urgent need for mobilization of all rural stakeholders and actors through appropriate governance arrangements in order to foster rural livelihoods diversification and quality of life improvement.

Design and Control of Robotic Hands

The application of dexterous robotic hands out of research laboratories has been limited by the intrinsic complexity that these devices present. This is directly reflected as an economically unreasonable cost and a low overall reliability. Within the research reported in this thesis it is shown how the problem of complexity in the design of robotic hands can be tackled, taking advantage of modern technologies (i.e. rapid prototyping), leading to innovative concepts for the design of the mechanical structure, the actuation and sensory systems. The solutions adopted drastically reduce the prototyping and production costs and increase the reliability, reducing the number of parts required and averaging their single reliability factors. In order to get guidelines for the design process, the problem of robotic grasp and manipulation by a dual arm/hand system has been reviewed. In this way, the requirements that should be fulfilled at hardware level to guarantee successful execution of the task has been highlighted. The contribution of this research from the manipulation planning side focuses on the redundancy resolution that arise in the execution of the task in a dexterous arm/hand system. In literature the problem of coordination of arm and hand during manipulation of an object has been widely analyzed in theory but often experimentally demonstrated in simplified robotic setup. Our aim is to cover the lack in the study of this topic and experimentally evaluate it in a complex system as a anthropomorphic arm hand system.

On the role of Computational Logic in Data Science: representing, learning, reasoning, and explaining knowledge

In this thesis we discuss in what ways computational logic (CL) and data science (DS) can jointly contribute to the management of knowledge within the scope of modern and future artificial intelligence (AI), and how technically-sound software technologies can be realised along the path. An agent-oriented mindset permeates the whole discussion, by stressing pivotal role of autonomous agents in exploiting both means to reach higher degrees of intelligence. Accordingly, the goals of this thesis are manifold. First, we elicit the analogies and differences among CL and DS, hence looking for possible synergies and complementarities along 4 major knowledge-related dimensions, namely representation, acquisition (a.k.a. learning), inference (a.k.a. reasoning), and explanation. In this regard, we propose a conceptual framework through which bridges these disciplines can be described and designed. We then survey the current state of the art of AI technologies, w.r.t. their capability to support bridging CL and DS in practice. After detecting lacks and opportunities, we propose the notion of logic ecosystem as the new conceptual, architectural, and technological solution supporting the incremental integration of symbolic and sub-symbolic AI. Finally, we discuss how our notion of logic ecosys- tem can be reified into actual software technology and extended towards many DS-related directions.

Design and characterization of automated agricultural vehicle systems

Nowadays, technological advancements have brought industry and research towards the automation of various processes. Automation brings a reduction in costs and an improvement in product quality. For this reason, companies are pushing research to investigate new technologies. The agriculture industry has always looked towards automating various processes, from product processing to storage. In the last years, the automation of harvest and cultivation phases also has become attractive, pushed by the advancement of autonomous driving. Nevertheless, ADAS systems are not enough. Merging different technologies will be the solution to obtain total automation of agriculture processes. For example, sensors that estimate products' physical and chemical properties can be used to evaluate the maturation level of fruit. Therefore, the fusion of these technologies has a key role in industrial process automation. In this dissertation, ADAS systems and sensors for precision agriculture will be both treated. Several measurement procedures for characterizing commercial 3D LiDARs will be proposed and tested to cope with the growing need for comparison tools. Axial errors and transversal errors have been investigated. Moreover, a measurement method and setup for evaluating the fog effect on 3D LiDARs will be proposed. Each presented measurement procedure has been tested. The obtained results highlight the versatility and the goodness of the proposed approaches. Regarding the precision agriculture sensors, a measurement approach for the Moisture Content and density estimation of crop directly on the field is presented. The approach regards the employment of a Near Infrared spectrometer jointly with Partial Least Square statistical analysis. The approach and the model will be described together with a first laboratory prototype used to evaluate the NIRS approach. Finally, a prototype for on the field analysis is realized and tested. The test results are promising, evidencing that the proposed approach is suitable for Moisture Content and density estimation.

Integrated communication and learning towards autonomous mobile radio networks

The integration of distributed and ubiquitous intelligence has emerged over the last years as the mainspring of transformative advancements in mobile radio networks. As we approach the era of “mobile for intelligence”, next-generation wireless networks are poised to undergo significant and profound changes. Notably, the overarching challenge that lies ahead is the development and implementation of integrated communication and learning mechanisms that will enable the realization of autonomous mobile radio networks. The ultimate pursuit of eliminating human-in-the-loop constitutes an ambitious challenge, necessitating a meticulous delineation of the fundamental characteristics that artificial intelligence (AI) should possess to effectively achieve this objective. This challenge represents a paradigm shift in the design, deployment, and operation of wireless networks, where conventional, static configurations give way to dynamic, adaptive, and AI-native systems capable of self-optimization, self-sustainment, and learning. This thesis aims to provide a comprehensive exploration of the fundamental principles and practical approaches required to create autonomous mobile radio networks that seamlessly integrate communication and learning components. The first chapter of this thesis introduces the notion of Predictive Quality of Service (PQoS) and adaptive optimization and expands upon the challenge to achieve adaptable, reliable, and robust network performance in dynamic and ever-changing environments. The subsequent chapter delves into the revolutionary role of generative AI in shaping next-generation autonomous networks. This chapter emphasizes achieving trustworthy uncertainty-aware generation processes with the use of approximate Bayesian methods and aims to show how generative AI can improve generalization while reducing data communication costs. Finally, the thesis embarks on the topic of distributed learning over wireless networks. Distributed learning and its declinations, including multi-agent reinforcement learning systems and federated learning, have the potential to meet the scalability demands of modern data-driven applications, enabling efficient and collaborative model training across dynamic scenarios while ensuring data privacy and reducing communication overhead.