By understanding and mimicking characteristics of postural control used by animals, scientist and engineers may develop standing autonomous robots that work safely within home environments, and treatment strategies that help people overcome postural impairments. To increase our understanding of postural control we developed physical and computational models of standing posture to explain the interrelation of stance width and feedback gain in controlling the stability and dynamics of the postural response. These models facilitated precise analysis of mechanical dynamics and their effects on compliant feedback control, and provided a physical implementation to verify predictions developed from simulation. We show that a scaling of active feedback gain is required to maintain postural stability. These results are consistent with previous studies that have shown that a correlation exists between increased stance width and decreased postural responses. However, these studies have not quantified the relation between stance and the active control of standing posture. This scaling of gains that we show is dependent on the changing kinematic relations of the mechanical structure as it undergoes stance width adjustments. Specifically, we show that increasing stance width increases the leverage of the mechanical system. Feedback gains must be reduced by the reciprocal of the increase in mechanical leverage in order to maintain a consistent postural response; otherwise, the system may become unstable with increasing oscillations. We also showed that increasing magnitudes of intrinsic stiffness increases postural stability by facilitating stable responses over larger ranges of active feedback gain and increasing the stability of responses by decreasing settling time, oscillations, and displacement magnitude. The conclusions of this study were that the variation of mechanical leverage is responsible for changing the dynamics of the response during stance width variation, and that scaling of feedback gains with the changing mechanical leverage of stance width variations is required to maintain consistent response dynamics across stance widths.

Wireless Sensor and Actor Networks (WSANs) are distributed systems of heterogeneous devices, referred to as sensors and actors, which sense, control, and interact with the physical environment. Sensors are low-cost, low-power, multi-functional devices that communicate untethered in short distances. Actors are resource-rich devices that collect and process sensor data and consequently perform actions on the environment. This thesis is concerned with coordination and communication problems in WSANs, in datacentric and multimedia application scenarios. First, communication and coordination problems are jointly addressed in a unifying framework for the case of static actors. A sensor-actor coordination model is proposed, based on an event-driven partitioning paradigm. Sensors are partitioned into different sets and each set is associated with a different actor. Data delivery trees are created to optimally react to the event and timely deliver event data with minimum energy expenditure. The optimal partitioning strategy is determined bymathematical programming, and a distributed solution is also proposed. Furthermore, the actor-actor coordination problem is formulated as an optimal task assignment problem, and a distributed solution of the problem based on an analogy with a one-shot auction is presented. Application scenarios for WSANs with mobile actors are then studied. A location management scheme is introduced to handle the mobility of actors with minimal energy consumption for resource-constrained sensors. The proposed scheme, which is the first localization scheme specifically designed for WSANs, is shown to consistently reduce the energy consumption with respect to existing localization services for ad hoc and sensor networks. An optimal energy-aware forwarding rule is then derived for sensor-actor communication in fast varying Rayleigh channels. The proposed scheme allows controlling the delay of the data-delivery process based on power control, and reacts to network congestion by diverting traffic from congested to lightly-loaded actors. The mobility of actors is coordinated to optimally accomplish application-specific tasks, based on a nonlinear optimization model that accounts for location and capabilities of heterogeneous actors. The research challenges for delivery of multimedia traffic in wireless sensor and actor networks are then outlined. Finally, a cross-layer communication architecture based on Ultra Wide Band communications is described, whose design objective is to reliably and flexibly deliver QoS to multimedia applications in WSANs, by carefully leveraging and controlling interactions among layers according to application requirements. Performance evaluation shows how the proposed solution achieves the performance objectives of wireless sensor and actor networks.

Autonomous mobile robots - both aerial and terrestrial vehicles - have gained immense importance due to the broad spectrum of their potential military and civilian applications. One of the indispensable requirements for the autonomy of a mobile vehicle is the vehicle's capability of planning and executing its motion, that is, finding appropriate control inputs for the vehicle such that the resulting vehicle motion satisfies the requirements of the vehicular task. The motion planning and control problem is inherently complex because it involves two disparate sub-problems: (1) satisfaction of the vehicular task requirements, which requires tools from combinatorics and/or formal methods, and (2) design of the vehicle control laws, which requires tools from dynamical systems and control theory. Accordingly, this problem is usually decomposed and solved over two levels of hierarchy. The higher level, called the geometric path planning level, finds a geometric path that satisfies the vehicular task requirements, e.g., obstacle avoidance. The lower level, called the trajectory planning level, involves sufficient smoothening of this geometric path followed by a suitable time parametrization to obtain a reference trajectory for the vehicle. Although simple and efficient, such hierarchical separation suffers a serious drawback: the geometric path planner has no information of the kinematic and dynamic constraints of the vehicle. Consequently, the geometric planner may produce paths that the trajectory planner cannot transform into a feasible reference trajectory. Two main ideas appear in the literature to remedy this problem: (a) randomized sampling-based planning, which eliminates altogether the geometric planner by planning in the vehicle state space, and (b) geometric planning supported by feedback control laws. The former class of methods suffer from a lack of optimality of the resultant trajectory, while the latter class of methods makes a restrictive assumption concerning the vehicle kinematic model. In this thesis, we propose a hierarchical motion planning framework based on a novel mode of interaction between these two levels of planning. This interaction rests on the solution of a special shortest-path problem on graphs, namely, one using costs defined on multiple edge transitions in the path instead of the usual single edge transition costs. These costs are provided by a local trajectory generation algorithm, which we implement using model predictive control and the concept of effective target sets for simplifying the non-convex constraints involved in the problem. The proposed motion planner ensures "consistency" between the two levels of planning, i.e., a guarantee that the higher level geometric path is always associated with a kinematically and dynamically feasible trajectory. We show that the proposed motion planning approach offers distinct advantages in comparison with the competing approaches of discretization of the state space, of randomized sampling-based motion planning, and of local feedback-based, decoupled hierarchical motion planning. Finally, we propose a multi-resolution implementation of the proposed motion planner, which requires accurate descriptions of the environment and the vehicle only for short-term, local motion planning in the immediate vicinity of the vehicle.

An indoor environment could be defined by a complex layout in a compact space. Since mobile robots can be used as substitute for human beings to access harmful and inaccessible locations, the research of autonomous indoor navigation has attracted much interest. In general, a mobile robot navigates in an indoor environment where acquired data are limited. Furthermore, sensor measurements may contain errors in a number of situations. Therefore, the complexity of indoor environment and ability of sensors have determined that it is an insufficient to merely compute with data. This thesis presents a new rough-fuzzy approach to perception-based computing for an indoor navigation algorithm. This approach to perceptual computing is being developed to store, analyze and summarize existing experience in given environment so that the machine is able to detect current situation and respond optimally. To improve uncertainty reasoning of fuzzy logic control, a rough set theory is integrated to regulate inputs before applying fuzzy inference rules. The behaviour extraction is evaluated and adjusted through entropy-based measures and multi-scale analysis. The rough-fuzzy based control algorithm aims to minimize overshoot and optimize transient-state period during navigation. The proposed algorithm is tested through simulations and experiments using practical common situations. The performance is evaluated with respect to desired path keeping and transient-state adaptability.

Thesis (MScEng)-- Stellenbosch University, 2013. / ENGLISH ABSTRACT: This thesis presents the development of a flight control system (FCS) for an unmanned, unpowered parafoil and the integration with an existing parafoil system in collaboration with a team at the University of Cape Town (UCT). The main goal of the FCS is to autonomously guide the parafoil from an arbitrary deployment position to a desired landing target. A nonlinear 8 degrees of freedom (8-DOF) parafoil model by C. Redelinghuys is incorporated into a MATLAB Simulink simulation environment. The non-linear model is numerically linearised and modal decomposition techniques are used to analyse the natural modes of motion. All modes are determined to be stable but a poorly damped lateral payload relative twist mode is present which causes large payload yaw oscillations. The FCS is divided into stability augmentation, control and guidance subcomponents. Stability augmentation is proposed in the form of a yaw rate damper which provides artificial damping for the oscillatory payload twist mode. For control, a yaw rate controller is designed with the aim of a fast response while not exciting the payload twist oscillation. Subsequently, an existing guidance method is implemented for path following. Autonomous path planning and mission control logic is created, including an energy management (EM) method to eliminate excess height and a terminal guidance (TG) phase. The TG phase is the final turn before landing and is the last chance to influence landing accuracy. A TG algorithm is implemented which generates an optimal final turn and can be replanned en route to compensate for unknown wind and other disturbances. The FCS is implemented on existing avionics, integrated with the parafoil system and verified with hardware in the loop (HIL) simulations. Flight tests are presented but are limited to remote control (RC) tests that verify the integration of the avionics and the parafoil system and test preliminary FCS components. / AFRIKAANSE OPSOMMING: Hierdie tesis dra die ontwikkeling voor van ‘n vlug-beheerstelsel (VBS) vir ’n onbemande, onaangedrewe valskerm-sweeftuig (parafoil), asook die integrasie daarvan met ’n bestaande stelsel. Die projek is in samewerking met ’n span van die Universiteit van Kaapstad (UCT) uitgevoer. Die VBS se hoof doel is om die sweeftuig outonoom vanaf ’n arbitrêre beginpunt na ’n gewensde landingsteiken te lei. ’n Nie-lineêre 8 grade van vryheid sweeftuig model deur C. Redelinghuys is in die MATLAB Simulink omgewing geïnkorporeer. Die nie-lineêre model is numeries gelineariseer om ’n lineêre model te verkry, waarna die natuurlike gedrag van die tuig geanaliseer is. ’n Swak gedempte laterale draai ossillasie van die loonvrag is geïdentifiseer. Die VBS is opgedeel in stabiliteitstoevoeging, beheer en leiding. ’n Giertempo-demper (yaw rate damper) is as stabiliteitstoevoeging om die loonvrag ossillasie kunsmatig te demp, voorgestel. ’n Giertempo-beheerder is ontwerp met die klem op ’n vinnige reaksie terwyl die opwekking van die loonvrag ossillasie terselfdetyd verhoed word. Daarna is ’n bestaande metode vir trajekvolging geïmplementeer. Outonome padbeplanning en oorhoofse vlugplan logika is ontwikkel, insluitend ’n energie-bestuur (EB) metode, om van oortollige hoogte ontslae te raak, asook ’n terminale leiding (TL) metode. Die TL fase verwys na die finale draai voor landing en is die laaste kans om die landingsakkuraatheid te beïnvloed. ’n Bestaande TL algoritme is geïmplementeer wat ’n optimale trajek genereer en in staat is om vir wind en ander versteurings te kompenseer deur die trajek deurgaans te herbeplan. Die VBS is op bestaande avionika geïmplementeer, met die sweeftuigstelsel geïntegreer en met behulp van hardeware in die lus (HIL) simulasies geverifieer. Vlugtoetse is voorgedra, maar is egter beperk tot radio beheer vlugte wat die korrekte integrasie van die avionika en die voertuig toets, asook ’n beperkte aantal voormalige VBS toetse.

Internal Models (IMs) play a significant role in autonomous robotics. They are mechanisms able to represent the input-output characteristics of the sensorimotor loop. In developmental robotics, open-ended learning of skills and knowledge serves the purpose of reaction to unexpected inputs, to explore the environment and to acquire new behaviours. The development of the robot includes self-exploration of the state-action space and learning of the environmental dynamics. In this dissertation, we explore the properties and benefits of the self-organisation of robot behaviour based on the homeokinetic learning paradigm. A homeokinetic robot explores the environment in a coherent way without prior knowledge of its configuration or the environment itself. First, we propose a novel approach to self-organisation of behaviour by artificial curiosity in the sensorimotor loop. Second, we study how different forward models settings alter the behaviour of both exploratory and goal-oriented robots. Diverse complexity, size and learning rules are compared to assess the importance in the robot’s exploratory behaviour. We define the self-organised behaviour performance in terms of simultaneous environment coverage and best prediction of future sensori inputs. Among the findings, we have encountered that models with a fast response and a minimisation of the prediction error by local gradients achieve the best performance. Third, we study how self-organisation of behaviour can be exploited to learn IMs for goal-oriented tasks. An IM acquires coherent self-organised behaviours that are then used to achieve high-level goals by reinforcement learning (RL). Our results demonstrate that learning of an inverse model in this context yields faster reward maximisation and a higher final reward. We show that an initial exploration of the environment in a goal-less yet coherent way improves learning. In the same context, we analyse the self-organisation of central pattern generators (CPG) by reward maximisation. Our results show that CPGs can learn favourable reward behaviour on high-dimensional robots using the self-organised interaction between degrees of freedom. Finally, we examine an on-line dual control architecture where we combine an Actor-Critic RL and the homeokinetic controller. With this configuration, the probing signal is generated by the exertion of the embodied robot experience with the environment. This set-up solves the problem of designing task-dependant probing signals by the emergence of intrinsically motivated comprehensible behaviour. Faster improvement of the reward signal compared to classic RL is achievable with this configuration.

Essa dissertação propõe um algoritmo e um equipamento (hardware) para captação de imagens da pupila do olho humano e processamento das mesmas a fim de obter, de forma portátil, autônoma, segura, não invasiva e em tempo real, informações sobre a pupila. Mais especificamente, o objetivo é obter informações que permitam determinar o diâmetro da pupila, tanto de forma estática (pupila com tamanho estável, sem a incidência intencional de luz) quanto dinâmica (pupila variando devido à aplicação de luz com intensidade variável). Tal sistema pode ser utilizado no setor da saúde, por exemplo, para realização da pupilometria, exame feito na área de oftalmologia, ou para medição da velocidade de expansão da pupila, exame auxiliar no diagnóstico de uma série de doenças que afetam o sistema nervoso. / This dissertation proposes an algorithm and a corresponding hardware implementation capable of capturing images from the human eye and processing these images to obtain, in a portable, autonomous, secure, and non-invasive way, in real time, information regarding the pupil. More specifically, the objective is to obtain information that allows the equipment to determine the pupil's diameter, both in static form (i.e., with constant light intensity) and in dynamic form (pupil under varying light intensity). Such a system can be used in the health sector, for example, in exams such as pupillometry, a test done by ophthalmologists, or for measuring the pupil's expansion rate, a test used in the diagnosis of a series of diseases that affect the nervous system.

Essa dissertação propõe um algoritmo e um equipamento (hardware) para captação de imagens da pupila do olho humano e processamento das mesmas a fim de obter, de forma portátil, autônoma, segura, não invasiva e em tempo real, informações sobre a pupila. Mais especificamente, o objetivo é obter informações que permitam determinar o diâmetro da pupila, tanto de forma estática (pupila com tamanho estável, sem a incidência intencional de luz) quanto dinâmica (pupila variando devido à aplicação de luz com intensidade variável). Tal sistema pode ser utilizado no setor da saúde, por exemplo, para realização da pupilometria, exame feito na área de oftalmologia, ou para medição da velocidade de expansão da pupila, exame auxiliar no diagnóstico de uma série de doenças que afetam o sistema nervoso. / This dissertation proposes an algorithm and a corresponding hardware implementation capable of capturing images from the human eye and processing these images to obtain, in a portable, autonomous, secure, and non-invasive way, in real time, information regarding the pupil. More specifically, the objective is to obtain information that allows the equipment to determine the pupil's diameter, both in static form (i.e., with constant light intensity) and in dynamic form (pupil under varying light intensity). Such a system can be used in the health sector, for example, in exams such as pupillometry, a test done by ophthalmologists, or for measuring the pupil's expansion rate, a test used in the diagnosis of a series of diseases that affect the nervous system.

Nous proposons une approche de planification unifiée pour robots humanoïdes réalisant des tâches de locomotion et de manipulation nécessitant une dextérité propre aux systèmes anthropomorphes. Ces tâches sont basées sur des transitions de contacts ; contacts entre les extrémités des membres locomoteurs et l'environnement dans le cas du problème de locomotion par exemple, ou entre les extrémités de l'organe préhensible effecteur et l'objet manipulé dans le cas du problème de manipulation. Nous planifions ces transitions de contacts pour des systèmes abstraits constitués d'autant de robots, d'objets, et de supports dans l'environnement que désiré/nécessaire pour la modélisation du problème. Cette approche permet de s'affranchir de la distinction de nature entre tâches de locomotion et de manipulation et s'étend à une variété d'autres problèmes tels que la coopération entre plusieurs agents. Nous introduisons notre paradigme de planification non-découplée de locomotion et de manipulation en exhibant la stratification induite dans l'espace des configurations de systèmes simplifiés pour lesquels nous résolvons analytiquement le problème en comparant des méthodes de planification géométrique, non-holonome, et dynamique. Nous présentons ensuite l'algorithme de planification de contacts basé sur une recherche best-first. Cet algorithme fait appel à un solveur de cinématique inverse qui prend en compte des configurations de contacts générales dans l'espace pouvant être établis entre robots, objets, et environnement dans toutes les combinaisons possibles, le tout sous contraintes d'équilibre statique et de respect des limitations mécaniques des robots. La génération de mouvement respectant l'équation de dynamique Lagrangienne est obtenue par une formulation en programme quadratique. Enfin nous envisageons une extension à des supports de contact déformables en considérant des comportements linéaires-élastiques résolus par éléments finis. / We propose a unified planning approach for autonomous humanoid robots that perform dexterous locomotion and manipulation tasks. These tasks are based on contact transitions; for instance between the locomotion limbs of the robot and the environment, or between the manipulation end-effector of the robot and the manipulated object. We plan these contact transitions for general abstract systems made of arbitrary numbers of robots, manipulated objects, and environment supports. This approach allows us to erase distinction between the locomotion and manipulation nature of the tasks and to extend the method to various other planning problems such as collaborative manipulation and locomotion between multiple agents. We introduce our non-decoupled locomotion-and-manipulation planning paradigm by exhibiting the induced stratification of the configuration space of example simplified systems for which we analytically solve the problem comparing geometric path planning, kinematic non-holonomic planning, and dynamic trajectory planning methods. We then present the contact planning algorithm based on best-first search. The algorithm relies on an inverse kinematics solver that handles general robot-robot, robot-object, robot-environment, object-environment, non-horizontal, non-coplanar, friction-based, multi-contact configurations, under static equilibrium and physical limitation constraints. The continuous dynamics-consistent motion is generated in the locomotion case using a quadratic programming formulation. We finally envision the extension to deformable environment contact support by considering linear elasticity behaviours solved using the finite element method.

The study of self-assembling robots represents a promising strand within the emerging field of modular robots research. Self-assembling robots have the potential to autonomously adapt their bodies to new tasks and changing environments long after their initial deployment by forming new or reorganizing existing physical connections to peer robots. In previous research, many approaches have been presented to enable self-assembling robots to form composite morphologies. Recent technological advances have also increased the number of robots able to form such morphologies by at least two orders of magnitude. However, to date, composite robot morphologies have not been able to solve real-world tasks nor have they been able to adapt to changing conditions entirely without human assistance or prior knowledge.In this thesis, we identify three reasons why self-assembling robots may not have been able to fully unleash their potential and propose appropriate solutions. First, composite morphologies are not able to show sensorimotor coordination similar to those seen in their monolithic counterparts. We propose "mergeable nervous systems" -- a novel methodology that unifies independent robotic units into a single holistic entity at the control level. Our experiments show that mergeable nervous systems can enable self-assembling robots to demonstrate feats that go beyond those seen in any engineered or biological system. Second, no proposal has been tabled to enable a robot in a decentralized multirobot system select its communication partners based on their location. We propose a new form of highly scalable mechanism to enable "spatially targeted communication" in such systems. Third, the question of when and how to trigger a self-assembly process has been ignored by researchers to a large extent. We propose "supervised morphogenesis" -- a control methodology that is based on spatially targeted communication and enables cooperation between aerial and ground-based self-assembling robots. We show that allocating self-assembly related decision-making to a robot with an aerial perspective of the environment can allow robots on the ground to operate in entirely unknown environments and to solve tasks that arise during mission time. For each of the three propositions put forward in this thesis, we present results of extensive experiments carried out on real robotic hardware. Our results confirm that we were able to substantially advance the state of the art in self-assembling robots by unleashing their potential for morphological adaptation through enhanced sensorimotor coordination and by improving their overall autonomy through cooperation with aerial robots. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished