Naive but Efficient - Using Greedy Strategies for Exploration, Inspection and Search

For operating in initially unknown and dynamic environments, autonomous mobile robots need abilities to explore their workspace and construct an environment model as well as to perform searches in that model and re-explore the environment to keep the model up-to-date. This paper focuses on the efficiency of using simple frontier-based greedy strategies for exploration and search that provide an autonomous mobile robot with these abilities.

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