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Titlebook: Robotic Mapping and Exploration; Cyrill Stachniss Book 2009 Springer-Verlag Berlin Heidelberg 2009 autonom.autonomous robot.knowledge.lear

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Mapping and Localization in Non-Static Environmentsecially for environments populated by humans. People typically walk around, open and close doors, add or remove things, or even move objects like furniture. In the literature, most of the approaches to mapping with mobile robots are based on the assumption that the environment is static. As reported
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Conclusionccurate map of the environment on their own are regarded as fulfilling a major precondition of truly autonomous mobile vehicles. The autonomous map learning problem has several important aspects that need to be solved simultaneously in order to come up with accurate models. These problems are mappin
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Information Gain-based Exploration system that takes into account the pose uncertainty and carries out loop-closing actions in order to relocalize the robot. This has been shown to provide better maps than exploration approaches focusing on new terrain acquisition only.
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Book 2009background knowledge, and dealing with dynamic environments. Results are accompanied by a rich set of experiments, revealing a promising outlook toward the application to a wide range of mobile robots and field settings, such as search and rescue, transportation tasks, or automated vacuum cleaning..
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Recovering Particle Diversityparticle diversity of the filter before entering a loop. When leaving the loop, the robot is then able to recover that diversity and continue the exploration process. This technique allows a mobile robot to stay - at least theoretically - arbitrarily long in a loop without depleting hypotheses neede
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Cyrill Stachniss existence of material substances and claimed that sensible objects are mere bundles of qualities. But to the extent Berkeley can account for the difference between appearance and reality and the transpersonal, cross-temporal perceptibility of objects he may well be able to account for dispositional
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