Image analysis, and its application to sensory input (computer vision) is a fairly mature field, so it is surprising that its techniques are not extensively used in robotic applications. The reason for this is that, traditionally, robots have been used in controlled environments where sophisticated computer vision was not necessary, for example in car manufacturing. As the field of robotics has moved toward providing general purpose robots that must function in the real world, it has become necessary that the robots be provided with robust sensors capable of understanding the complex world around them. However, when researchers apply techniques previously studied in image analysis literature to the field of robotics, several difficult problems emerge. In this thesis we examine four reasons why it is difficult to apply work in image analysis directly to real-time, general purpose computer vision applications. These are: improvement in the computational complexity of image analysis algorithms, robustness to dynamic and unpredictable visual conditions, independence from domain specific knowledge in object recognition and the development of debugging facilities. This thesis examines each of these areas making several innovative contributions in each area. We argue that, although each area is distinct, improvement must be made in all four areas before vision will be utilised as the primary sensory input for mobile, autonomous robotic applications. In the first area, the computational complexity of image analysis algorithms, we note the dependence of a large number of high-level processing routines on a small number of low-level algorithms. Therefore, improvement to a small set of highly utilised algorithms will yield benefits in a large number of applications. In this thesis we examine the common tasks of image segmentation, edge and straight line detection and vectorisation. In the second area, robustness to dynamic and unpredictable conditions, we examine how vision systems can be made more tolerant to changes of illumination in the visual scene. We examine the classical image segmentation task and present a method for illumination independence that builds on our work from the first area. The third area is the reliance on domain-specific knowledge in object recognition. Many current systems depend on a large amount of hard-coded domainspecific knowledge to understand the world around them. This makes the system hard to modify, even for slight changes in the environment, and very difficult to apply in a different context entirely. We present an XML-based language, the XML Object Definition (XOD) language, as a solution to this problem. The language is largely descriptive instead of imperative so, instead of describing how to locate objects within each image, the developer simply describes the properties of the objects. The final area is the development of support tools. Vision system programming is extremely difficult because large amounts of data are handled at a very fast rate. If the system is running on an embedded device (such as a robot) then locating defects in the code is a time consuming and frustrating task. Many development-support applications are available for specific applications. We present a general purpose development-support tool for embedded, real-time vision systems. The primary case study for this research is that of Robotic soccer, in the international RoboCup Four-Legged league. We utilise all of the research of this thesis to provide the first illumination-independent object recognition system for RoboCup. Furthermore we illustrate the flexibility of our system by applying it to several other tasks and to marked changes in the visual environment for RoboCup itself.

The purpose of the essay is to examine the possibilities for students to learn mathematics with a variety of senses through the tasks in the teaching materials Nya matematikboken, Singma and Favorit matematik during school year 1. The focus is on visual, auditory and kinesthetic/tactile support. Furthermore, the aim is to investigate the different elements of the teaching material and the extent of the different support in them. With categories based on different sensory input, a thorough content analysis has been made to compare the three chosen teaching materials. The result shows that there are good grounds for learning through many senses. However, the support varies in total and in the different elements. Both similarities and differences have been distinguished. The results also clearly show the benefits of using the teaching materials fully.

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Cortical representations are plastic and are allocated based on the proportional use or disuse of a pathway. A steady stream of sensory input maintains the integrity of cortical networks; while in contrast, alterations in afferent activation promote sensorimotor reorganization. After an incomplete spinal cord injury (SCI), damage to the ascending and/or descending pathways induces widespread modifications to the sensorimotor system. Strengthening these spared sensorimotor pathways may be therapeutic by promoting functional recovery after injury. Using a technique called transcranial magnetic stimulation (TMS), we show that the leg motor cortex is facilitated by peripheral sensory inputs via disinhibition and potentiation of excitatory intracortical circuits. Hence, in addition to its crucial role in sensory perception, excitation from peripheral sensory afferents can reinforce muscle activity by engaging, and possibly shaping, the activity of the human motor cortex. After SCI, the amount of excitation produced by afferent stimulation reaching the motor cortex is expectantly reduced and delayed. This reduction of sensory inflow to the motor cortex may contribute to our findings that cortical inhibition is down-regulated after SCI, and this compensation may aid in the recruitment of excitatory networks in the motor cortex as a result of the damage to its output neurons. By repeatedly pairing sensory inputs from a peripheral nerve in the leg with direct cortical activation by TMS, in an intervention called paired associative stimulation, we show that the motor system can be potentiated in both uninjured individuals and after SCI. In the uninjured subjects, we show that in order to produce associative facilitation, the time window required for coincident activation of the motor cortex by TMS and peripheral sensory inputs is not as narrow as previously thought (~100 vs. ~20 ms), likely due to the persistent activation of cortical neurons following activation by TMS. The potential to condition the nervous system with convergent afferent and cortical inputs suggests that paired associative stimulation may serve as a priming tool for motor plasticity and rehabilitation following SCI.

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Le contrôle postural fait intervenir l’intégration cérébelleuse de différentes entrées sensorielles (le vestibule, la vision, la somesthésie). Nous avons évalué le contrôle postural à l’aide de différents dispositifs : la plateforme Techno Concept®, le Multitest Framiral® et les mouvements oculaires avec l’oculomètre : le Mobile e(ye)BRAIN T2® chez des participants contrôles et des enfants présentant des déficits neuro-développementaux, troubles appartenant au spectre autistique et dyslexie. Au cours de nos travaux, nous avons décrit un aspect développemental physiologique des indices posturaux et oculomoteurs et également un déficit de ces indicateurs auprès d’enfants avec retards d’apprentissage. En effet, chez ces enfants, la stabilité posturale est déficitaire et les stratégies d’exploration sont différentes par rapport aux contrôles. Nous avons basé nos hypothèses sur le fait que ce déficit serait du à un défaut d’utilisation des informations sensorielles ainsi qu’à une mauvaise intégration cérébelleuse. Les résultats de nos études nous permettent de mieux préciser les caractéristiques neuropsychologiques impliquant les fonctions cérébelleuses chez ces enfants afin de pouvoir suggérer des prises en charge thérapeutiques multimodales capables d’entrainer simultanément plusieurs fonctions. Notre objectif final est de pouvoir identifier une médiation thérapeutique spécifique pour ces enfants. / Postural control involves cerebellar integration of several sensory inputs (vestibular, visual and somesthesic). We evaluated postural control with force plateform: Techno Concept®, Multitest Framiral® and the eye movements with the Mobile e(ye)BRAIN T2® in healthy children population as well as in children with developmental disorders (autistic spectrum desorders and dyslexia). The results of our studies showed a developmental aspect of postural and oculomotor factors in healthy children and a deficit of both postural and oculomotor control in children with autistic spectrum desorders and with dyslexia. Indeed, in these children postural stability is poor and visual strategy is different with respect to healthy children. Our hypothesis is that these deficits could be due to a lack in using appropriately sensory inputs and of their integration via cerebellar activity. The importance of these studies is to better understand the involvement of cerebellar function in such developmental disorders. Our final goal is to suggest new training tecniques to use sensory inputs more efficiently in these children with developmental disorders.