975 resultados para Navigating robots


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Lee, M., Barnes, D. P., Hardy, N. (1985). Research into error recovery for sensory robots. Sensor Review, 5 (4), 194-197.

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M. H. Lee, D. P. Barnes, and N. W. Hardy. Knowledge based error recovery in industrial robots. In Proc. 8th. Int. Joint Conf. Artificial Intelligence, pages 824-826, Karlsruhe, FDR., 1983.

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Barnes, D. P., Lee, M. H., Hardy, N. W. (1983). A control and monitoring system for multiple-sensor industrial robots. In Proc. 3rd. Int. Conf. Robot Vision and Sensory Controls, Cambridge, MA. USA., 471-479.

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M.H.Lee, Q. Meng and H. Holstein, ?Learning and Reuse of Experience in Behavior-Based Service Robots?, Seventh International Conference on Control, Automation, Robotics and Vision (ICARCV2002), pp1019-24, December 2002, Singapore

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Meng Q. and Lee M.H., Automatic Error Recovery in Behaviour-Based Assistive Robots with Learning from Experience, in Proc. INES 2001, 5th IEEE Int. Conf. on Intelligent Engineering Systems, Helsinki, Finland, Sept 2001, pp291-296.

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Walker,J. and Garrett,S. and Wilson,M.S., 'Evolving Controllers for Real Robots: A Survey of the Literature', Adaptive Behavior, 2003, volume 11, number 3, pp 179--203, Sage

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Pattison,T. and Wilson,M.S., 'Flocking in Simulation and Robots - A Review', Towards Intelligent Mobile Robots; Proceedings of the 4th annual British conference on autonomous mobile robotics and autonomous systems (TIMR'03), 2003, pp 90-99

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Walker,J. and Wilson,M.S., 'Lifelong Evolution for Adaptive Robots', Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2002, October, pp 984--989

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M.H. Lee, Q. Meng and F. Chao, 'Developmental Learning for Autonomous Robots', Robotics and Autonomous Systems, 55(9), pp 750-759, 2007.

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ROSSI: Emergence of communication in Robots through Sensorimotor and Social Interaction, T. Ziemke, A. Borghi, F. Anelli, C. Gianelli, F. Binkovski, G. Buccino, V. Gallese, M. Huelse, M. Lee, R. Nicoletti, D. Parisi, L. Riggio, A. Tessari, E. Sahin, International Conference on Cognitive Systems (CogSys 2008), University of Karlsruhe, Karlsruhe, Germany, 2008 Sponsorship: EU-FP7

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An active, attentionally-modulated recognition architecture is proposed for object recognition and scene analysis. The proposed architecture forms part of navigation and trajectory planning modules for mobile robots. Key characteristics of the system include movement planning and execution based on environmental factors and internal goal definitions. Real-time implementation of the system is based on space-variant representation of the visual field, as well as an optimal visual processing scheme utilizing separate and parallel channels for the extraction of boundaries and stimulus qualities. A spatial and temporal grouping module (VWM) allows for scene scanning, multi-object segmentation, and featural/object priming. VWM is used to modulate a tn~ectory formation module capable of redirecting the focus of spatial attention. Finally, an object recognition module based on adaptive resonance theory is interfaced through VWM to the visual processing module. The system is capable of using information from different modalities to disambiguate sensory input.