987 resultados para Dort Motor Car Company


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论文分两部分:第一部分在参阅大量文献的基础上,对海洋声信道的特性及其对声遥控的影响做了分析和总结,并根据FSK调制信号的传播实验,对海洋声信道的一些特性进行了定性分析。第二部分详细地分析了CAR型声释放器的电路特性,并结合海洋声信道的特性及海上实验情况分析了CAR型声释放器的工作性能。

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The goal of this thesis is to apply the computational approach to motor learning, i.e., describe the constraints that enable performance improvement with experience and also the constraints that must be satisfied by a motor learning system, describe what is being computed in order to achieve learning, and why it is being computed. The particular tasks used to assess motor learning are loaded and unloaded free arm movement, and the thesis includes work on rigid body load estimation, arm model estimation, optimal filtering for model parameter estimation, and trajectory learning from practice. Learning algorithms have been developed and implemented in the context of robot arm control. The thesis demonstrates some of the roles of knowledge in learning. Powerful generalizations can be made on the basis of knowledge of system structure, as is demonstrated in the load and arm model estimation algorithms. Improving the performance of parameter estimation algorithms used in learning involves knowledge of the measurement noise characteristics, as is shown in the derivation of optimal filters. Using trajectory errors to correct commands requires knowledge of how command errors are transformed into performance errors, i.e., an accurate model of the dynamics of the controlled system, as is demonstrated in the trajectory learning work. The performance demonstrated by the algorithms developed in this thesis should be compared with algorithms that use less knowledge, such as table based schemes to learn arm dynamics, previous single trajectory learning algorithms, and much of traditional adaptive control.

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A model is presented that deals with problems of motor control, motor learning, and sensorimotor integration. The equations of motion for a limb are parameterized and used in conjunction with a quantized, multi-dimensional memory organized by state variables. Descriptions of desired trajectories are translated into motor commands which will replicate the specified motions. The initial specification of a movement is free of information regarding the mechanics of the effector system. Learning occurs without the use of error correction when practice data are collected and analyzed.

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Introdução; Clima; Solos; Sistema de plantio; Propagação; Época de plantio; Variedades; Adubação; Cobertura morta; Tutoramento; Doenças; Pragas; Colheita.

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Is it conceivable to contemplate a future without the car as the center of an urban transportation system? Can emerging economies grow without concomitant growth in car usage? San Pedro Sula, Honduras, is one city at a critical decision point about the future of transportation and mobility. Will it be a sustainable transport future that balances economic, environmental and social needs or will it be the traditional “predict and provide” approach that attempts to expand the capacity of the road system to meet future travel demand. This paper provides some background into the issue for this Central American city by describing the current urban transport system, current plans for improvement and outlines a process for defining a vision for a sustainable transport future in San Pedro Sula. The paper concludes with a challenge to all cities that currently have low automobile ownership rates to consider a sustainable transport system in order to “thrive” with transport choices for all residents rather than “choke” on congestion and the negative side effects thereof.

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M. H. Lee and Q. Meng, Growth of Motor Coordination in Early Robot Learning, IJCAI-05, 2005.

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M.H. Lee, Q. Meng and F. Chao, 'A Content-Neutral Approach for Sensory-Motor Learning in Developmental Robotics', EpiRob'06: Sixth International Conference on Epigenetic Robotics, Paris, 55-62, 2006.

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M.H. Lee and Q. Meng, 'Staged development of Robot Motor Coordination', IEEE International Conference on Systems, Man and Cybernetics, (IEEE SMC 05), Hawaii, USA, v3, 2917-2922, 2005.

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Lee, M., Meng, Q. (2005). Psychologically Inspired Sensory-Motor Development in Early Robot Learning. International Journal of Advanced Robotic Systems, 325-334.

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M.H. Lee and Q. Meng, 'Psychologically Inspired Sensory-Motor Development in Early Robot Learning', in proceedings of Towards Autonomous Robotic Systems 2005 (TAROS-05), Nehmzow, U., Melhuish, C. and Witkowski, M. (Eds.), Imperial College London, 157-163, September 2005. See published version: http://hdl.handle.net/2160/485

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De acuerdo a la normativa de TFEs el repositorio no puede dar acceso a este trabajo. Para consultarlo póngase en contacto con el tutor del trabajo. Puede acceder al resumen del mismo pinchando en el pdf adjunto.

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Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências Empresariais

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http://www.archive.org/details/acrosstheprairie00haseuoft