This thesis presents a novel design for a pipe inspection robot. The main aim of the design has been to allow the robot to operate in a water pipe while it is still in service. Water pipes form a very crucial part of the infrastructure of the world we live in today. Despite their importance, water leakage is a major problem suffered by water companies worldwide, costing them billions of dollars every year. There are a wide variety of different techniques used for leak detection and localisation, but no one method is capable of accurately pinpointing the leak location and severity in all pipe conditions with minimal labour. A survey of existing pipe inspection robots showed that there have been many designs implemented that are capable of navigating the pipeline environment. However, none of these were capable of fully autonomous control in a live water pipe. It was concluded that an autonomous pipe inspection robot capable of working in active pipelines would be of great industrial benefit as it would be able to carry a wide range of sensors directly to the source of the leak with minimal, if any, human intervention. An inchworm robot prototype was constructed based on a Gough-Stewart parallel platform. The robot’s inverse kinematics equations were derived and a simulation model of the robot was constructed. These were verified using a motion capture suite, confirming that they are valid representations of the robot. The simulation was used to determine the robot’s movement limitations and minimum bend radius it could navigate. Several CFD simulations were carried out in order to estimate the maximum fluid force exerted on the robot. It was found that the robot’s design successfully minimised the fluid force such that off-the-shelf actuators had the capability to overcome it. The prototype was successfully tested in both a straight and bent pipe, demonstrating its ability to navigate a dry pipe environment. Overall, the robot prototype served as a successful proof of concept for a design of pipe inspection robot that would be capable of operating in active pipelines.

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Traditionally, solid axle railway wheelsets are stabilised by using passive suspensions on a conventional rail vehicle, but such additional stiffness affects the pure rolling action of the wheelset around the curve. It has been theoretically proven that this design conflict between stability and curving performance can be solved by applying active control instead of conventional passive components, resulting in the reduction of the wear of the wheels and track by minimising the track shifting forces. In the active approach, the use of actuators, sensors and data processors to replace the traditional passive suspension raises the issue of the system safety in the event of a failure of the active control, which could result in the loss of stability and in more severe cases, derailment. Further on, in active control systems for railway vehicles the actuators tend to be significantly more expensive and require more additional space than sensors, and an electronic control unit. Therefore, developing an analytical redundancy-based fault tolerance technique for an actively controlled wheelset that minimises the number of actuators will clearly be more beneficial. Thus the emphasis of this research is to develop a fault-tolerant system of active control for a railway vehicle in the event of actuator malfunction in order to guarantee stability and good curving performance without using additional actuators. The key achievements of this research can be summarised as follows: • The research considers three of the most common types of actuator failure for the electro-mechanical actuators: fail-hard (FH), short circuit (SC) and open circuit (OC). The fail-hard is a failure condition when the motor shaft of the actuator becomes immovable, whereas the short circuit and open circuit are failures that occur in the electrical parts of the actuator which correspond to zero voltage and zero current in the motor respectively. • The research investigates and develops a thorough understanding of the effect of actuator faults and failure modes on the vehicle behaviour that provides the necessary foundation for the development of the proposed fault-tolerant strategy. • An effective fault detection and isolation methods for actuator faults through two different approaches is developed; the vehicle model-based approach and the actuator model-based approach. Additionally, the research takes into account the reliability and robustness of the FDI schemes in the presence of sensor failures and parameter uncertainties in the system. • The research develops the control re-configuration in order to cope with the identified failure mode of the actuator in order to maintain the vehicle stability and desired curving performance.

It is often the case that robotic systems require models, in order to successfully control themselves, and to interact with the world. Models take many forms and include kinematic models to plan motions, dynamics models to understand the interaction of forces, and models of 3D geometry to check for collisions, to name but a few. Traditionally, models are provided to the robotic system by the designers that build the system. However, for long-term autonomy it becomes important for the robot to be able to build and maintain models of itself, and of objects it might encounter. In this thesis, the argument for enabling robotic systems to autonomously build models is advanced and explored. The main contribution of this research is to show how a layered approach can be taken to building models. Thus a robot, starting with a limited amount of information, can autonomously build a number of models, including a kinematic model, which describes the robot’s body, and allows it to plan and perform future movements. Key to the incremental, autonomous approach is the use of exploratory actions. These are actions that the robot can perform in order to gain some more information, either about itself, or about an object with which it is interacting. A method is then presented whereby a robot, after being powered on, can home its joints using just vision, i.e. traditional methods such as absolute encoders, or limit switches are not required. The ability to interact with objects in order to extract information is one of the main advantages that a robotic system has over a purely passive system, when attempting to learn about or build models of objects. In light of this, the next contribution of this research is to look beyond the robot’s body and to present methods with which a robot can autonomously build models of objects in the world around it. The first class of objects examined are flat pack cardboard boxes, a class of articulated objects with a number of interesting properties. It is shown how exploratory actions can be used to build a model of a flat pack cardboard box and to locate any hinges the box may have. Specifically, it is shown how when interacting with an object, a robot can combine haptic feedback from force sensors, with visual feedback from a camera to get more information from an object than would be possible using just a single sensor modality. The final contribution of this research is to present a series of exploratory actions for a robotic text reading system that allow text to be found and read from an object. The text reading system highlights how models of objects can take many forms, from a representation of their physical extents, to the text that is written on them.

Development of behavioural strategies for indoor mobile navigation has become a challenging and practical issue in a cluttered indoor environment, such as a hospital or factory, where there are many static and moving objects, including humans and other robots, all of which trying to complete their own specific tasks; some objects may be moving in a similar direction to the robot, whereas others may be moving in the opposite direction. The key requirement for any mobile robot is to avoid colliding with any object which may prevent it from reaching its goal, or as a consequence bring harm to any individual within its workspace. This challenge is further complicated by unobserved objects suddenly appearing in the robots path, particularly when the robot crosses a corridor or an open doorway. Therefore the mobile robot must be able to anticipate such scenarios and manoeuvre quickly to avoid collisions. In this project, a hybrid control architecture has been designed to navigate within dynamic environments. The control system includes three levels namely: deliberative, intermediate and reactive, which work together to achieve short, fast and safe navigation. The deliberative level creates a short and safe path from the current position of the mobile robot to its goal using the wavefront algorithm, estimates the current location of the mobile robot, and extracts the region from which unobserved objects may appear. The intermediate level links the deliberative level and the reactive level, that includes several behaviours for implementing the global path in such a way to avoid any collision. In avoiding dynamic obstacles, the controller has to identify and extract obstacles from the sensor data, estimate their speeds, and then regular its speed and direction to minimize the collision risk and maximize the speed to the goal. The velocity obstacle approach (VO) is considered an easy and simple method for avoiding dynamic obstacles, whilst the collision cone principle is used to detect the collision situation between two circular-shaped objects. However the VO approach has two challenges when applied in indoor environments. The first challenge is extraction of collision cones of non-circular objects from sensor data, in which applying fitting circle methods generally produces large and inaccurate collision cones especially for line-shaped obstacle such as walls. The second challenge is that the mobile robot cannot sometimes move to its goal because all its velocities to the goal are located within collision cones. In this project, a method has been demonstrated to extract the colliii sion cones of circular and non-circular objects using a laser sensor, where the obstacle size and the collision time are considered to weigh the robot velocities. In addition the principle of the virtual obstacle was proposed to minimize the collision risk with unobserved moving obstacles. The simulation and experiments using the proposed control system on a Pioneer mobile robot showed that the mobile robot can successfully avoid static and dynamic obstacles. Furthermore the mobile robot was able to reach its target within an indoor environment without causing any collision or missing the target.

Accurate control techniques for pinpoint planetary landing - i.e., the goal of achieving landing errors in the order of 100m for unmanned missions - is a complex problem that have been tackled in different ways in the available literature. Among other challenges, this kind of control is also affected by the well known trade-off in UAV control that for complex underlying models the control is sub-optimal, while optimal control is applied to simplifed models. The goal of this research has been the development new control algorithms that would be able to tackle these challenges and the result are two novel optimal control algorithms namely: OQTAL and HEX2OQTAL. These controllers share three key properties that are thoroughly proven and shown in this thesis; stability, accuracy and adaptability. Stability is rigorously demonstrated for both controllers. Accuracy is shown in results of comparing these novel controllers with other industry standard algorithms in several different scenarios: there is a gain in accuracy of at least 15% for each controller, and in many cases much more than that. A new tuning algorithm based on swarm heuristics optimisation was developed as well as part of this research in order to tune in an online manner the standard Proportional-Integral-Derivative (PID) controllers used for benchmarking. Finally, adaptability of these controllers can be seen as a combination of four elements: mathematical model extensibility, cost matrices tuning, reduced computation time required and finally no prior knowledge of the navigation or guidance strategies needed. Further simulations in real planetary landing trajectories has shown that these controllers have the capacity of achieving landing errors in the order of pinpoint landing requirements, making them not only very precise UAV controllers, but also potential candidates for pinpoint landing unmanned missions.

There is a surge of research interest in the field of “continuum robotics”. Robots created under this paradigm offer many advantages and represent unique features in terms of flexibility, dexterity, safety and weight reduction. In the thesis, a novel continuum manipulator that integrates multiple layers of compliant planar springs is introduced – a structure that provides several notable advantages over existing designs. It possesses precise linear large-displacement motion and demonstrates effectively decoupling bending from contraction and thus reduces the uncontrolled compression when generating normal deflections; besides, an enlarged workspace of the end-effector is achieved by varying the length of the continuum manipulator via contraction. The mechanics of the proposed continuum manipulator is investigated. An analytical method is provided to study the compliance characteristics of planar springs and derive the unified compliance matrix to represent the force-deflection relationships, allowing an accurate motion prediction. Differences of the compliance characteristics with respect to design variations of planar springs are discussed. An analysis regarding behaviours of the full continuum manipulator is given. According to the constantcurvature approximation, two kinematic models corresponding to three-tendon-driven and single-tendondriven continuum manipulators are presented. This modelling methodology permits closed-form kinematics and also facilitates the derivation of differential kinematics and real-time control. In view of the model’s complexity and uncertainty of the continuum manipulator, a fuzzy control approach is implemented for autonomous execution of end-effector motion tasks. The system state-space model is constructed using the general continuum manipulator kinematics with the constant-curvature assumption. The fuzzy controller is designed utilizing state-feedback control techniques. Thus, this control methodology enables a low-computation solution to this motion control problem without the need for continuously updating the Jacobian of the continuum manipulator. Besides, compared to traditional Jacobian-based controllers that suffer from model inaccuracies, the fuzzy control exhibits superior performances with respect to a specified cost function.

Being the cornerstone of today's Industry, Industrial Control Systems (ICSs) play an important role in the overall function and quality of modern society. Their use to control critical processes within the Industry (power production, transportation, manufacturing etc.) makes them an integral part of the Critical National Infrastructure (CNI), as defined by the European Council (2008), rendering thereby their protection a process of critical importance. Traditionally, ICSs have been operated as closed, isolated systems. However, the connection of contemporary ICS installations with external networks, including the corporate network and the Internet, along with the introduction of conventional off-the-self technologies, has exposed the once isolated systems to a rapidly evolving yet new to them cyberthreat landscape. Their critical nature further complicates the situation making them an attractive target for various attack vectors and threat agents. Traditional cyber-security methods seem inadequate since they are tailored to the specific corporate needs ignoring the demanding nature of ICSs. Nevertheless, due to the increased cost of designing and applying new cyber-protection methods, the majority of cyber-security solutions used nowadays in the Industry are mainly adaptations of traditional corporate-oriented methods (Giannopoulos et aI., 2012), raising thus significant challenges that the research community has to address. This thesis presents novel cyber-security approaches, tailored to the particular nature of ICSs. The developed methods take into account both the increased cybersecurity needs in this critical area and the related costs, offering optimal cost efficient cyber-security solutions. Stafford Beer's Viable System Model (VSM) was used as a vehicle to analyse the behaviour of ICSs and identify the areas where cost-efficient cyber-protection methods are in need (Stafford, 1984). Driving the research into those areas a series of cyber-protection methods were developed using system theory-base.d techniques such as game theory and system dynamics. Those methods include a cost-efficient cyber-security model against the malware spread within ICSs and a cost-efficient model for the protection against Denial of Service (DoS)/ Distributed Denial of Service (DDoS) attacks. Building on the same premises a novel ICS-oriented cyber-security risk management method was developed based on the Viable System Model and game theory. i

This thesis is concerned with the challenge of creating a robot which is capable of natural, verbal communication with humans. More specifically, it considers the task of categorising objects according to sensory stimuli. We focus on tactile texture perception, a sensory feature which has received relatively little attention in artificial intelligence, in comparison with vision and audition. Through a multidisciplinary approach involving sensory feature extraction, computer simulations, and psychophysical experiments, we compare texture perception and categorisation between human and robot, and consider the problem of enabling communication between them. We begin by presenting TacTip, an artificial fingertip sensor which we apply to the task of texture recognition. We describe a feature extraction process used to specify a textural feature space for the sensor, which is then used for texture recognition and categorisation. Next, we present a framework for robotic communication and learning. This framework consists of two main parts, the first of which is the representational model used by the robot to categorise perceived stimuli. We present a model based on random set theory and prototype theory, and compare this with a similar model based on Bayesian statistics. The second part of the framework is the context in which the robots communicate and learn. In our case this consists of a multi-agent simulation in which robots communicate with each other through pairwise interactions called language games, and thereby develop a shared set of categories. Finally, we consider how our robot might communicate with and learn from humans. We describe two psychophysical experiments, the first of which studies how humans naturally classify textures, the second investigating whether humans can learn specific categorisations presented to them. Each experiment can be interpreted as one part of a language game interaction between human and robot. We discuss our results in the context of human-robot communication.

Humans are extremely adept at interacting with the world through touch and eliciting meaningful information through touch. Current handheld and wearable electronic devices provide very limited tactile feedback to the user. The ultimate tactile device should be able to stimulate the full range of mechanoreceptors in the skin, to elicit any sensation. Our skin is soft and compliant, so wearable devices should be soft, conform to and move with the user. Smart materials could hold the key to development of low-cost high-resolution soft tactile devices. This thesis is working towards a vision of entirely soft and compliant tactile devices using smart materials. Laterotactile stimulation, where tactile elements move parallel to the skin surface to create regions of stretching and compression in the skin, would seem perfectly suited for such applications. Although there are examples of laterotactile stimulation in the literature, this area is largely unexplored. We present a psychophysical study comparing the tactile sensitivity to normal and lateral stimuli. We present and characterise a compliant laterotactile display prototype for stimulation of the glabrous skin, using Dielectric Elastomer Actuators. This technology will readily scale up to large arrays and large devices and scale down to micro-stimulators. Real-world tactile interaction often conveys inherent meaning and affect. Taking inspiration from recent work in neuroscience, we have developed the Tickler; a soft laterotactile display that strokes the wrist. The Tickler creates natural-feeling sensations, and highlights opportunities for soft technologies in haptics. We show that the perceived sensation of affective haptic devices can be modulated by the context in which it is presented, and the nature of the modulation is stimulus dependent. This has significant implications for the evaluation of affective haptic devices. We consider how follicular structures in Nature can be mimicked in robotic skin and haptic devices, and present a first example of a follicular skin device for two-way gesture-based tactile communication. These developments provide the important foundations for new devices that mark a paradigm shift in our physical interactions with technology and the virtual world.