Building Semantic Object Maps from Sparse and Noisy 3D Data
In Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2013), (IROS-2013), 03.11.-07.11.2013, Tokio, o.A., Nov/2013.
We present an approach to create a semantic map of an indoor environment, based on a series of 3D point clouds captured by a mobile robot using a Kinect camera. The proposed system reconstructs the surfaces in the point clouds, detects different types of furniture and estimates their pose. The result is a consistent mesh representation of the environment enriched by CAD models corresponding to the detected pieces of furniture. We evaluate our approach on two datasets totaling over 800 frames directly on each individual frame.