Titlebook: Design and Control of Intelligent Robotic Systems; Dikai Liu,Lingfeng Wang,Kay Chen Tan Book 2009 Springer-Verlag Berlin Heidelberg 2009 A

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https://doi.org/10.1007/978-3-322-91769-0ot to physically execute multitudes of trial solutions. Neither approach is very suitable for dynamic unstructured environments in which a robot is sent to explore and gather information prior to human entry. This chapter presents a new approach, ‘memory-based learning’, in which a robot is provided

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Strukturieren, Formalisieren, Axiomatisierenuncertainty are major obstacles for control in real robots. When programming a real robot in unstructured dynamic environments, it is impossible to predict all the potential situation robots may encounter and specify all robot behaviors optimally in advance. Robots have to learn from, and adapt to t

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https://doi.org/10.1007/978-3-030-70629-6s and localizing that robot within this map. The ultimate goal of SLAM is to operate anywhere, allowing a robot to navigate autonomously and producing a meaningful purposeful map. Research in SLAM to date has focused on improving the localization part of SLAM, while lagging in the ability to produce

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