: The Fiducial Map Metric
Schwertfeger, Sören Jacoff, Adam Scrapper, Chris Pellenz, Johannes 2010 (English)In: Proc. of the Int. Workshop on Performance Metrics for Intelligent Systems (PerMIS), NIST, 2010, 344-351Konferensbidrag (Refereed)
Mapping is an important task for mobile robots. Assessing the quality of those maps is an open topic. A new approach on map evaluation is presented here. It makes use of artificial objects placed in the environment named "Fiducials". Using the known ground-truth positions and the positions of the fiducials identified in the map, a number of quality attributes can be assigned to that map. Depending on the application domain those attributes are weighed to compute a final score. During the 2010 NIST Response Robot Evaluation Exercise at Disaster City an area was populated with fiducials and different mapping runs were performed. The maps generated there are assessed in this paper demonstrating the Fiducial approach. Finally this map scoring algorithm is compared to other approaches found in literature.
Identifiersurn:nbn:se:liu:diva-72524 (URN)oai:DiVA.org:liu-72524 (OAI)
ProjectsArtificial Intelligence & Integrated Computer Systems