Many robotic navigation tasks assume that a static map of the environment is sufficient for all future navigation tasks. This paper describes a method to detect the case where some features in the environment have changed with respect to the original map. The proposed method runs a localization filter and a mapping filter in parallel and finds discrepancies based on differences between the two map representations. Then, the map is repaired online to reflect the current environment.
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Online Detection of Map Discrepancies in Landmark-Based Robotic Localization
Semantic Scholar · Computer Science · 2019
Abstract
Many robotic navigation tasks assume that a static map of the environment is sufficient for all future navigation tasks. This paper describes a method to detect the case where some features in the environment have changed with respect to the original map. The proposed method runs a localization filter and a mapping filter in parallel and finds discrepancies based on differences between the two map representations. Then, the map is repaired online to reflect the current environment.