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

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機(jī)械

Engulf

Coordinated Multi-Robot Exploration to compensate for sensor uncertainty. As a result, the map can be expected to be more accurate. Multiple robots have also been shown to localize themselves more efficiently, especially when they have different sensor capabilities [42, 122].

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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 ac

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Recovering Particle Diversitylity of a map constructed by a mobile robot depends on its trajectory during data acquisition. This is due to the fact that the vehicle needs to relocalize itself during exploration in order to build an accurate model of the environment. Our loop-closing technique uses a heuristic stopping criterion

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