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This paper presents a method of building a 3-D map that consists of 3-D object models. First, we build a 2-D map from laser range finder (LRF) scans, and detect objects by matching a scan template with the 2-D map. Then, we verify the detected object candidates using vision-based object recognition based on the constraint that the estimated pose of a true positive must be consistent between scan matching and object recognition. We have conducted an experiment in a room having desks and cabinets to show the effectiveness of the method.