Relevant bibliographies by topics / Robot Networks / Dissertations / Theses
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Dissertations / Theses on the topic 'Robot Networks'

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Published: 2 June 2025
Last updated: 31 July 2025

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1

Bishop, Russell C. "A Method for Generating Robot Control Systems." Connect to resource online, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1222394834.

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2

Smith, Brian Stephen. "Automatic coordination and deployment of multi-robot systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28248.

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Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Dr. Magnus Egerstedt; Committee Co-Chair: Dr. Ayanna Howard; Committee Member: Dr. David Taylor; Committee Member: Dr. Frank Dellaert; Committee Member: Dr. Ian Akyildiz; Committee Member: Dr. Jeff Shamma.
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3

Zhong, Xiaolin. "Robot calibration using artificial neural networks." Thesis, Edinburgh Napier University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.295387.

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4

Cupitt, Rebekah. "We Are the Robots : An anthropological perspective on human-robot interaction." Thesis, Socialantropologiska institutionen, Stockholms universitetet, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-49557.

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Abstract How do we cope with technology today? We are surrounded by machines, computers and technological devices from mobile phones to automated check- outs. These types of machines are no longer exotic in Sweden where today the average person is usually fluent in their use. But do we really have an understanding of how these objects work, is understanding necessary and how do we cope when our knowledge is lacking? This thesis is intended as an introduction to an anthropological way of look- ing at strategies people develop for understanding, using and interacting with technological objects,
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Rush, Jonathan Reginald. "Evolving cellular neural networks for autonomous robot control." Thesis, University of Salford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.308293.

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6

rahman, md mahbubur. "Efficient Mission Planning for Robot Networks in Communication Constrained Environments." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3484.

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Many robotic systems are remotely operated nowadays that require uninterrupted connection and safe mission planning. Such systems are commonly found in military drones, search and rescue operations, mining robotics, agriculture, and environmental monitoring. Different robotic systems may employ disparate communication modalities such as radio network, visible light communication, satellite, infrared, Wi-Fi. However, in an autonomous mission where the robots are expected to be interconnected, communication constrained environment frequently arises due to the out of range problem or unavailabili
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7

Vestheim, Siri. "Pruning of RBF Networks in Robot Manipulator Learning Control." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for teknisk kybernetikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18591.

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Radial Basis Function Neural Networks are well suited for learning the systemdynamics of a robot manipulator and implementation of these networks in thecontrol scheme for a manipulator is a good way to deal with the system uncertaintiesand modeling errors which often occur. The problem with RBF networkshowever is to nd a network with suitable size, not too computational demandingand able to give accurate approximations. In general two methods for creating anappropriate RBF network has been developed, 1) Growing and 2) Pruning.In this report two dierent pruning methods which are suitable for us
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Wei, Zhouping, University of Western Sydney, and of Mechatronic Computer and Electrical Engineering School. "Model predictive control of a robot using neural networks." THESIS_XXX_MCEE_Wei_Z.xml, 1999. http://handle.uws.edu.au:8081/1959.7/323.

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The aim of the thesis is to develop a model-based control strategy, namely, the Model Predictive Control (MPC) method, for robot position control using artificial neural networks. MPC is primarily developed for process control. Therefore its application in robot control has been less reported. In addition, conventional MPC uses linear model of the system for prediction which leads to inaccuracy for highly non-linear systems, such as robot. In this thesis a simulation model of a modified PUMA robot is constructed. This model is built using both MATLAB/SIMULINK and FORTRAN languages. In this mod
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9

Künzle, Philippe. "Building topological maps for robot navigation using neural networks." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82266.

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Robots carrying tasks in an unknown environment often need to build a map in order to be able to navigate. One approach is to create a detailed map of the environment containing the position of obstacles. But this option can use a large amount of memory, especially if the environment is large. Another approach, closer to how people build a mental map, is the topological map. A topological map contains only places that are easy to recognize (landmarks) and links them together.<br>In this thesis, we explore the issue of creating a topological map from range data. A robot in a simulated en
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10

Xie, Wei. "KNN Query Processing in Wireless Sensor and Robot Networks." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30673.

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In Wireless Sensor and Robot Networks (WSRNs), static sensors report event information to one of the robots. In the k nearest neighbour query processing problem in WSRNs, the robot receives event report needs to find exact k nearest robots (KNN) to react to the event, among those connected to it. We are interested in localized solutions, which avoid message flooding to the whole network. Several existing methods restrict the search within a predetermined boundary. Some network density-based estimation algorithms were proposed but they either result in large message transmission or require the
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11

Smith, Tom. "The evolvability of artificial neural networks for robot control." Thesis, University of Sussex, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.270392.

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12

Wei, Zhouping. "Model predictive control of a robot using neural networks." Thesis, View thesis, 1999. http://handle.uws.edu.au:8081/1959.7/323.

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The aim of the thesis is to develop a model-based control strategy, namely, the Model Predictive Control (MPC) method, for robot position control using artificial neural networks. MPC is primarily developed for process control. Therefore its application in robot control has been less reported. In addition, conventional MPC uses linear model of the system for prediction which leads to inaccuracy for highly non-linear systems, such as robot. In this thesis a simulation model of a modified PUMA robot is constructed. This model is built using both MATLAB/SIMULINK and FORTRAN languages. In this mod
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13

Wei, Zhouping. "Model predictive control of a robot using neural networks /." View thesis, 1999. http://library.uws.edu.au/adt-NUWS/public/adt-NUWS20030903.140951/index.html.

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Thesis (M.Sc. (Hons.)) -- University of Western Sydney, Nepean, 1999.<br>"A thesis submitted to the School of Mechatronic, Computer and Electrical Engineering, the University of Western Sydney, Nepean in fulfilment of the requirements for the degree of Master of Engineering (Honours)" Bibliography : leaves 119-123.
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14

Buchi, Baptiste. "Learning system for self-reconfiguration of micro-robot networks." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2023. http://www.theses.fr/2023UBFCA017.

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Le problème d'auto-reconfiguration des réseaux de micro-robots est l'un des défis majeurs de la robotique modulaire. Un ensemble de micro-robots reliés par des liens électromagnétiques ou mécaniques se réorganisent afin d'atteindre des formes cibles données. Le problème d'auto-reconfiguration est un problème complexe pour trois raisons. Premièrement, le nombre de configurations distinctes d'un réseau de robots modulaires est très élevé. Deuxièmement, comme les modules sont libres de se mouvoir indépendamment les uns des autres, à partir de chaque configuration il est possible d'atteindre un no
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15

Gonçalves, João Bosco. "Desenvolvimento de um sistema de controle adaptativo e integrado para locomoção de um robo bipede com tronco." [s.n.], 2004. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263888.

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Orientador: Douglas Eduardo Zampieri<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica<br>Made available in DSpace on 2018-08-04T03:12:52Z (GMT). No. of bitstreams: 1 Goncalves_JoaoBosco_D.pdf: 9689870 bytes, checksum: db2fb279a1080765ab5bddf9068a356d (MD5) Previous issue date: 2004<br>Resumo: Este trabalho concebeu um robô bípede composto por uma sucessão de elos rígidos interconectados por 12 articulações rotativas, permitindo movimentos tridimensionais. O robô bípede é constituído por dois subsistemas: tronco e membros inferiores. A modelagem matemá
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Pac, Muhammed Rasid. "A Fluid Dynamics Framework For Control Of Mobile Robot Networks." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608599/index.pdf.

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This thesis proposes a framework for controlling mobile robot networks based on a fluid dynamics paradigm. The approach is inspired by natural behaviors of fluids demonstrating desirable characteristics for collective robots. The underlying mathematical formalism is developed through establishing analogies between fluid bodies and multi-robot systems such that robots are modeled as fluid elements that constitute a fluid body. The governing equations of fluid dynamics are adapted to multi-robot systems and applied on control of robots. The model governs flow of a robot based on its local intera
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17

Franklin, D. R. "Neural networks for visual feedback control of an industrial robot." Thesis, University of Cambridge, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.599180.

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The majority of industrial robots in use today are configured by on-line programming at the start of each production run. The workpieces are located using precision indexing. The robots have little or no sensory input, other than joint position feedback, and are unable to operate in changing or loosely constrained environments. To overcome these constraints and to increase the range of practical applications, robots need to be able to apply adaptive intelligence to manufacturing operations. This calls for enhanced sensory capabilities. Vision systems have been introduced successfully into many
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18

Smith, Alan. "Myoelectric control techniques for a rehabilitation robot /." Online version of thesis, 2009. http://hdl.handle.net/1850/10893.

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19

Bainbridge, Christopher James. "Digital control networks for virtual creatures." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4812.

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Robot control systems evolved with genetic algorithms traditionally take the form of floating-point neural network models. This thesis proposes that digital control systems, such as quantised neural networks and logical networks, may also be used for the task of robot control. The inspiration for this is the observation that the dynamics of discrete networks may contain cyclic attractors which generate rhythmic behaviour, and that rhythmic behaviour underlies the central pattern generators which drive lowlevel motor activity in the biological world. To investigate this a series of experiments
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20

Antonucci, Alessandro. "Socially aware robot navigation." Doctoral thesis, Università degli studi di Trento, 2022. https://hdl.handle.net/11572/356142.

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A growing number of applications involving autonomous mobile robots will require their navigation across environments in which spaces are shared with humans. In those situations, the robot’s actions are socially acceptable if they reflect the behaviours that humans would generate in similar conditions. Therefore, the robot must perceive people in the environment and correctly react based on their actions and relevance to its mission. In order to give a push forward to human-robot interaction, the proposed research is focused on efficient robot motion algorithms, covering all the tasks needed i
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21

Tuci, Elio. "An exploration on the evolution of learning behaviour using robot-based models." Thesis, University of Sussex, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288147.

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The work described in this thesis concerns the study of the evolution of simple forms of learning behaviour in artificial agents. Our interest in the phylogeny of learning has been developed within the theoretical framework provided by the "ecological approach" to the study of learning. The latter is a recent theoretical and methodological perspective which, contrary to that suggested by the classical approaches in animal and comparative psychology, has reconsidered the importance of the evolutionary analysis of learning as a species- niche-specific adaptive process, which should be investigat
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22

Wang, Mingwei. "Performance analysis of neural networks applied to robot trajectory following systems." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ59017.pdf.

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23

Townsend, Neil William. "Neural networks for mobile robot localisation using infra-red range sensing." Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260753.

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24

Sölch, Maximilian. "Detecting anomalies in robot time series data using stochastic recurrent networks." Thesis, KTH, Optimeringslära och systemteori, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-180473.

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This thesis proposes a novel anomaly detection algorithm for detect-ing anomalies in high-dimensional, multimodal, real-valued time se-ries data. The approach, requiring no domain knowledge, is based on Stochastic Recurrent Networks (STORNs), a universal distribution approximator for sequential data leveraging the power of Recurrent Neural Networks (RNNs) and Variational Auto-Encoders (VAEs). The detection algorithm is evaluated on real robot time series data in order to prove that the method robustly detects anomalies off- and on-line.<br>Detta arbete förslår en ny detektionsalgoritm för anom
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25

Chancan, Leon Marvin Aldo. "The role of motion-and-visual perception in robot place learning and navigation." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/229769/8/Marvin%20Aldo_Chancan%20Leon_Thesis.pdf.

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This thesis was a step forward in developing new robot learning-based localisation and navigation systems using real world data and simulation environments. Three new methods were proposed to provide new insights on the role of joint motion-and-vision-based end-to-end robot learning in both place recognition and navigation tasks, within modern reinforcement learning and deep learning frameworks. Inspired by biological neural circuits underlying these complex tasks in insect and rat mammalian brains, these methods were shown to be orders of magnitude faster than classical techniques, while sett
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26

Desjardins, Benjamin. "Reliable Robot-Assisted Sensor Relocation via Multi-Objective Optimization." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35034.

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Wireless sensor networks (WSNs) are an emerging area of technology that have applications across many domains. By adding a mobile platform to the WSN we can increase its capabilities. One such scenario involves a mobile platform relocating sensors to fill sensing holes that are the result of sensor failure. We examine this problem, known as robot-assisted sensor relocation (RASR), and propose our own, multi-objective version, that we call reliable robot-assisted sensor relocation. We solve this problem using a set of state-of-the-art evolutionary multi-objective optimization algorithms. Additi
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27

Aldana, López Carlos Iván. "Consensus control in robot networks and cooperative teleoperation : an operational space approach." Doctoral thesis, Universitat Politècnica de Catalunya, 2015. http://hdl.handle.net/10803/287975.

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An interesting approach in cooperative control is to design distributed control strategies which use only local information so that a multi-agent system achieves specified behaviors. A basic behavior in cooperative control is the consensus. Given a multi-agent system, like a multiple robot network, it is said that the agents reach a consensus if the state of each agent converges to a common state. Examples of cooperative tasks in which consensus algorithms are employed include formation control, flocking theory, rendezvous problems and synchronization. These cooperative tasks have several pos
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Akin, Berkant. "Fault Tolerant Deployment, Search, And Task Cooperative Contol Of Robot/sensor Networks." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606574/index.pdf.

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This thesis focuses on developing of a distributed, efficient and fault tolerant multiresolutional architecture for sensor networks. For demonstrative purpose, a powerful simulation environment using 3D environment model has been developed. The robot network is composed of autonomous robots capable of working cooperatively equipped with single typed simple sensor. The developed layered control architecture is hybrid including both subsumption and motor schema control strategies. In this proposed control method, behaviors in different or in same layer are coordinated with an evaluator unit that
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Kiguchi, Kazuo. "Robot contact motion control using environment impedance identification: Application of neural networks." Thesis, University of Ottawa (Canada), 1993. http://hdl.handle.net/10393/6852.

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The robot manipulators must have capability of controlling mechanical interaction with objects which are involved in various tasks. In order to control the mechanical interaction, the environment impedance which is not always known has to be identified. In this thesis, environment impedance on-line identification methods based on Recursive Least Squares Estimation and Neural Networks approach are investigated in order to achieve an efficient force control. Experiments were done for both methods with the 3-DOF Direct-Drive planer robot manipulator, by applying a force on the environment with a
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Glöde, Isabella. "Autonomous control of a mobile robot with incremental deep learning neural networks." Master's thesis, Pontificia Universidad Católica del Perú, 2021. http://hdl.handle.net/20.500.12404/18676.

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Over the last few years autonomous driving had an increasingly strong impact on the automotive industry. This created an increased need for artificial intelligence algo- rithms which allow for computers to make human-like decisions. However, a compro- mise between the computational power drawn by these algorithms and their subsequent performance must be found to fulfil production requirements. In this thesis incremental deep learning strategies are used for the control of a mobile robot such as a four wheel steering vehicle. This strategy is similar to the human approach of learning. In many
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31

Rathbone, Kevin. "Evolving visually guided neural network robot arm controllers for lifetime learning." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.327646.

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32

Yap, Teddy. "Mobile robot navigation with low-cost sensors." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://proquest.umi.com/pqdweb?index=0&did=1957353711&SrchMode=2&sid=1&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1268419222&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2009.<br>Includes abstract. Title from first page of PDF file (viewed March 12, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 138-144). Also issued in print.
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33

Valtazanos, Aris. "Decision shaping and strategy learning in multi-robot interactions." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8091.

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Recent developments in robot technology have contributed to the advancement of autonomous behaviours in human-robot systems; for example, in following instructions received from an interacting human partner. Nevertheless, increasingly many systems are moving towards more seamless forms of interaction, where factors such as implicit trust and persuasion between humans and robots are brought to the fore. In this context, the problem of attaining, through suitable computational models and algorithms, more complex strategic behaviours that can influence human decisions and actions during an intera
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34

Feng, Shumin. "Mobile Robot Obstacle Avoidance based on Deep Reinforcement Learning." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/87059.

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Obstacle avoidance is one of the core problems in the field of autonomous navigation. An obstacle avoidance approach is developed for the navigation task of a reconfigurable multi-robot system named STORM, which stands for Self-configurable and Transformable Omni-Directional Robotic Modules. Various mathematical models have been developed in previous work in this field to avoid collision for such robots. In this work, the proposed collision avoidance algorithm is trained via Deep Reinforcement Learning, which enables the robot to learn by itself from its experiences, and then fit a mathematica
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35

Veerapuneni, Satish Kumar. "Benchmarking smart homes using a humanoid robot approach." [Gainesville, Fla.] : University of Florida, 2004. http://purl.fcla.edu/fcla/etd/UFE0006467.

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36

Bettaieb, Luc Alexandre. "A Deep Learning Approach To Coarse Robot Localization." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1493646936728041.

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37

Stuart, Daniel Scott. "Implementation of Robot Arm Networks and Experimental Analysis of Consensus-Based Collective Motion." DigitalCommons@USU, 2009. https://digitalcommons.usu.edu/etd/440.

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Within the field of multi-robot control, there is a large focus in research involving consensus. In this thesis two parts will be studied. The first development of this thesis is a consensus-based robot arm platform. To implement, two robotic arms are developed and studied. The most effective robot arm is then utilized to create a robot arm network testbed. Consensus is used to coordinate several robot arms and decentralize system computation. The research explores a platform to facilitate consensus on a group of robotic arms. The second development is in Cartesian coordinate collective motion
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38

Di, Stefano Alberto. "Convolutional neural networks for bin picking applications with a collaborative robot and a 2D camera." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24127/.

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In bin picking applications, robots manipulate randomized objects placed in a bin. For that, the objects must be located before picking. The procedure of localization relies heavily on data from cameras. In the literature many approaches are available by means of the traditional computer vision approaches that work very well in an industrial scenario, while for more challenging situations artificial intelligence must be adopted. So, this thesis addresses this problem by presenting a possible solution for detecting objects and estimating their poses. Many convolutional neural networks exist to
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Aronsson, Claes. "Evolution of Neural Controllers for Robot Teams." Thesis, University of Skövde, Department of Computer Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-732.

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<p>This dissertation evaluates evolutionary methods for evolving cooperative teams of robots. Cooperative robotics is a challenging research area in the field of artificial intelligence. Individual and autonomous robots may by cooperation enhance their performance compared to what they can achieve separately. The challenge of cooperative robotics is that performance relies on interactions between robots. The interactions are not always fully understood, which makes the designing process of hardware and software systems complex. Robotic soccer, such as the RoboCup competitions, offers an unpred
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Lou, Yaolong. "Compensation for nonlinearities in robot manipulators by on-line learning multilayer neural networks /." Düsseldorf : VDI-Verl, 1999. http://www.gbv.de/dms/ilmenau/toc/266816657.PDF.

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41

Poonawala, Hasan A. "Formation control and connectivity control for mobile robot networks using vision based measurements." Thesis, The University of Texas at Dallas, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3629039.

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<p> Several algorithms for multi-robot coordination assume that the communication network of a team of mobile robots is connected, so that information can be exchanged between any two robots in the team. The network topology is often state-dependent, and thus the robots may move in a way that causes the network to become disconnected. This dissertation proposes continuous time control laws that preserve the connectivity for both undirected and directed mobile robot networks, which can be used along with additional task-dependent control actions. An additional aim of the dissertation is to prov
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42

Lones, John. "Hormonal modulation of developmental plasticity in an epigenetic robot." Thesis, University of Hertfordshire, 2017. http://hdl.handle.net/2299/17859.

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In autonomous robotics, there is still a trend to develop and tune controllers with highly explicit goals and environments in mind. However, this tuning means that these robotic models often lack the developmental and behavioral flexibility seen in biological organisms. The lack of flexibility in these controllers leaves the robot vulnerable to changes in environmental condition. Whereby any environmental change may lead to the behaviors of the robots becoming unsuitable or even dangerous. In this manuscript we look at a potential biologically plausible mechanism which may be used in robotic c
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43

Lin, Nanlin. "A neural-network approach to high-performance adaptive control for robot manipulators /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19852265.

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44

Pieropan, Alessandro. "Structure learning of graphical models for task-oriented robot grasping." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2010. http://amslaurea.unibo.it/1641/.

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In the collective imaginaries a robot is a human like machine as any androids in science fiction. However the type of robots that you will encounter most frequently are machinery that do work that is too dangerous, boring or onerous. Most of the robots in the world are of this type. They can be found in auto, medical, manufacturing and space industries. Therefore a robot is a system that contains sensors, control systems, manipulators, power supplies and software all working together to perform a task. The development and use of such a system is an active area of research and one of the mai
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45

Li, Haotian. "Market-Based Sensor Relocation by a Team of Robots in Wireless Sensor Networks." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30707.

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Randomly scattered sensors may cause sensing holes and redundant sensors. In carrier-based sensor relocation, mobile robots (with limited capacity to carry sensors) pick up additional or redundant sensors and relocate them at sensing holes. In the only known localized algorithm, robots randomly traverse field and act based on identified pair of spare sensor and coverage hole. We propose a Market-based Sensor Relocation (MSR) algorithm, which optimizes sensor deployment location, and introduces bidding and coordinating among neighboring robots. Sensors along the boundary of each hole elect one
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Ellis, Michael D. "Use of wireless sensors to improve robot lifetime for multi-threat containment /." Online version of thesis, 2009. http://hdl.handle.net/1850/10739.

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47

Al-Araji, Ahmed. "Design of a cognitive neural predictive controller for mobile robot." Thesis, Brunel University, 2012. http://bura.brunel.ac.uk/handle/2438/7068.

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In this thesis, a cognitive neural predictive controller system has been designed to guide a nonholonomic wheeled mobile robot during continuous and non-continuous trajectory tracking and to navigate through static obstacles with collision-free and minimum tracking error. The structure of the controller consists of two layers; the first layer is a neural network system that controls the mobile robot actuators in order to track a desired path. The second layer of the controller is cognitive layer that collects information from the environment and plans the optimal path. In addition to this, it
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48

Melidis, Christos. "Adaptive neural architectures for intuitive robot control." Thesis, University of Plymouth, 2017. http://hdl.handle.net/10026.1/9998.

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This thesis puts forward a novel way of control for robotic morphologies. Taking inspiration from Behaviour Based robotics and self-organisation principles, we present an interfacing mechanism, capable of adapting both to the user and the robot, while enabling a paradigm of intuitive control for the user. A transparent mechanism is presented, allowing for a seamless integration of control signals and robot behaviours. Instead of the user adapting to the interface and control paradigm, the proposed architecture allows the user to shape the control motifs in their way of preference, moving away
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Matteini, Michele. "Extracting FSA descriptions of robot behaviours from the dynamics of automatically designed controller networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8464/.

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Automatic design has become a common approach to evolve complex networks, such as artificial neural networks (ANNs) and random boolean networks (RBNs), and many evolutionary setups have been discussed to increase the efficiency of this process. However networks evolved in this way have few limitations that should not be overlooked. One of these limitations is the black-box problem that refers to the impossibility to analyze internal behaviour of complex networks in an efficient and meaningful way. The aim of this study is to develop a methodology that make it possible to extract finite-state a
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Camisa, Andrea <1992&gt. "Distributed Large-scale Mixed-Integer Optimization with Application to Energy and Multi-robot Networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amsdottorato.unibo.it/9748/1/main_phd_thesis.pdf.

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Several decision and control tasks in cyber-physical networks can be formulated as large- scale optimization problems with coupling constraints. In these "constraint-coupled" problems, each agent is associated to a local decision variable, subject to individual constraints. This thesis explores the use of primal decomposition techniques to develop tailored distributed algorithms for this challenging set-up over graphs. We first develop a distributed scheme for convex problems over random time-varying graphs with non-uniform edge probabilities. The approach is then extended to unknown cost func
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