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

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https://doi.org/10.1007/978-3-642-01097-2autonom; autonomous robot; knowledge; learning; mobile robot; robot; uncertainty

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Multi-Robot Exploration Using Semantic Place LabelsIn the previous chapter, we introduced a technique to efficiently coordinate a team of exploring robots. So far, we made no assumption about the environment itself. In this chapter, we extend our coordination approach presented in Chapter 4 so that it takes into account additional information about the environment.

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Cyrill StachnissRecent research in the area of self-localization and mapping (SLAM) for autonomous robots.The presented solutions include uncertainty-driven exploration, active loop closing, coordination of multiple

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Basic Techniquescle filter is a recursive Bayesian technique for estimating the state of a dynamic system. We then explain the ideas of grid maps and “mapping with known poses”. Note that elementary laws in the context of probability theory can be found in the Appendix.

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Actively Closing Loops During Explorationring models of unknown environments requires to simultaneously address three tasks, which are mapping, localization, and path planning. In the this chapter as well as in the two following ones, we focus on integrated approaches which aim to solve these three tasks simultaneously in order to build accurate models of the environment.

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