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Robotic Mapping in the Real World: Performance Evaluation and System Integration

Mapping is an important task for mobile robots. The assessment of the quality of maps in a simple, efficient and automated way is not trivial and an ongoing research topic. In this thesis, evaluation methods for the maps produced by robotic systems are developed. The algorithm has to analyze and evaluate the maps in a systematic, repeatable and reproducible way. The problem is approached systematically: First the different terms and concepts are introduced and the state of the art in map evaluation is presented. Then a special type of mapping using video data is introduced and a path-based evaluation of the performance of this mapping approach is made. Afterwards a number of algorithms to process those maps are presented. Then the first novel map evaluation method, the Fiducial algorithm, is developed. In this place-based method, artificial markers that are distributed in the environment are detected in the map. The errors of the positions of those markers with respect to the known ground truth positions are used to calculate a number of attributes of the map. The main contribution of this thesis is the second novel map evaluation algorithm, that uses a graph that is representing the environment topologically. This structure-based approach abstracts from all other information in the map and just uses the topological information about which areas are directly connected to asses the quality of the map. Different ways to compare the similarity of two vertices from two graphs are presented and compared. This is needed to match two graphs to each other - the graph from the map to be evaluated and the graph of a known ground truth map. Using this match, a number of map attributes can be computed, including the interesting the map brokenness. Experiments made on many maps from different environments are then performed for both map metrics.