20 resultados para Mobile Robot Navigation

em University of Queensland eSpace - Australia


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Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

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The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robot’s action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robot’s navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

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The UQ RoboRoos have been developed to participate in the RoboCup robot soccer small size league over several years. RoboCup 2001 saw a focus on the mechanical design of the RoboRoos, with the introduction of an omni-directional drive system and a high power kicker. The change in mechanical design had implications for the rest of the system particularly navigation and multi-robot planning. In addition, the overhead vision system was upgraded to improve reliability and robustness.

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In the developing vertebrate brain, growing axons establish a scaffold of axon tracts connected across the midline via commissures. We have previously identified a population of telencephalic neurons that express NOC-2, a novel glycoform of the neural cell adhesion molecule N-CAM that is involved in axon guidance in the forebrain. These axons arise from the presumptive telencephalic nucleus, course caudally along the principal longitudinal tract of the forebrain, cross the ventral midline in the midbrain, and then project to the contralateral side of the brain. In the present study we have investigated mechanisms controlling the growth of these axons across the ventral midline of the midbrain. The axon guidance receptor DCC is expressed by the NOC-2 population of axons both within the longitudinal tract and within the ventral midbrain commissure. Disruption of DCC-dependent interactions, both in vitro and in vivo, inhibited the NOC-2 axons from crossing the ventral midbrain. Instead, these axons grew along aberrant trajectories away from the midline, suggesting that DCC-dependent interactions are important for overcoming inhibitory mechanisms within the midbrain of the embryonic vertebrate brain. Thus, coordinated responsiveness of forebrain axons to both chemostimulatory and chemorepulsive cues appears to determine whether they cross the ventral midline in the midbrain, (C) 2000 Academic Press.

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Many Archean cratons are surrounded by Proterozoic mobile belts that have experienced episodes of tectonic re-activation over their lifetimes. This suggests that mobile belt lithosphere may be associated with long lived, inherited weakness. It is proposed that the proximity of this weakness can increase the longevity of deep Archean lithosphere by buffering Archean cratons from mantle derived stresses. The physical plausibility of this idea is explored through numerical simulations of mantle convection that include continents and allow for material rheologies that model the combined brittle and ductile behavior of the lithosphere. Within the simulations, the longevity of deep cratonic lithosphere does increase if it is buffered by mobile belts that can fail at relatively low stress levels.

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Mobile Lipids detected using H-1-NMR in stimulated lymphocytes were correlated with cell cycle phase, expression of the interleukin-2 receptor alpha and proliferation to assess the activation status of the lymphocytes. Mobile lipid levels, IL-2R alpha expression and proliferation increased after treatment with PMA and ionomycin. PMA or ionomycin stimulation alone induced increased IL-2R alpha expressiom but not proliferation, PMA- but not ionomycin-stimulation generated mobile lipid, Treatment with anti-CD3 antibody did not increase IL-2R alpha expression or proliferation but did generate increased amounts of mobile lipid, The cell cycle status of thymocytes treated with anti-CD3, PMA or ionomycin alone indicated an. accumulation of the cells in the G(1) phase of the cell cycle, The generation of mobile lipid was abrogated in anti-CD3 antibody-stimulated thymic lymphocytes but not in splenic lymphocytes, using a phosphatidylcholine-specific phospholipase C (PC-PLC) inhibitor which blocked cells in the G(1)/S phase of the cell cycle, This suggests that the H-1-NMR-detectable mobile Lipid may be generated in anti-CD3 antibody-stimulated thymic lymphocytes by the action of PC-PLC activity via the catabolism of PC, in the absence of classical signs of activation. (C) 1997 Academic Press.

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