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Titlebook: ICT Innovations 2009; Danco Davcev,Jorge Marx Gómez Conference proceedings 2010 Springer-Verlag Berlin Heidelberg 2010 Artificial Intellig

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發(fā)表于 2025-3-28 16:18:16 | 只看該作者
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發(fā)表于 2025-3-29 01:05:00 | 只看該作者
44#
發(fā)表于 2025-3-29 06:31:28 | 只看該作者
Position Estimation of Mobile Robots Using Unsupervised Learning Algorithmsent state and to make the problem of generating command sequences for achieving a certain goal an easier task. The robot learns the environment using an unsupervised learning method and generates a percept – action- percept graph, based on the readings of an ultrasound sensor. The graph is then used
45#
發(fā)表于 2025-3-29 08:33:59 | 只看該作者
Practical Method for Real-Time Path Planning and Optimization for Mobile RobotsManeuvering the vehicle safely around obstacles is essential, and the ability to generate safe paths in a real time environment is crucial for vehicle viability. A method for developing feasible paths through complicated environments using a baseline smooth path based on Hermite cubic splines is pre
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發(fā)表于 2025-3-29 12:46:51 | 只看該作者
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49#
發(fā)表于 2025-3-30 03:51:59 | 只看該作者
Wireless Sensor Networks Localization Methods: Multidimensional Scaling vs. Semidefinite Programminglications, military applications, agriculture monitoring, home and office applications, environmental monitoring, etc. Knowing the location of a sensor is important, but GPS receivers and sophisticated sensors are too expensive and require processing power. Therefore, the localization wireless senso
50#
發(fā)表于 2025-3-30 05:28:37 | 只看該作者
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