Title :
3-D Mapping With an RGB-D Camera
Author :
Endres, Felix ; Hess, Jurgen ; Sturm, Jurgen ; Cremers, Daniel ; Burgard, Wolfram
Author_Institution :
Dept. of Comput. Sci., Univ. of Freiburg, Freiburg, Germany
Abstract :
In this paper, we present a novel mapping system that robustly generates highly accurate 3-D maps using an RGB-D camera. Our approach requires no further sensors or odometry. With the availability of low-cost and light-weight RGB-D sensors such as the Microsoft Kinect, our approach applies to small domestic robots such as vacuum cleaners, as well as flying robots such as quadrocopters. Furthermore, our system can also be used for free-hand reconstruction of detailed 3-D models. In addition to the system itself, we present a thorough experimental evaluation on a publicly available benchmark dataset. We analyze and discuss the influence of several parameters such as the choice of the feature descriptor, the number of visual features, and validation methods. The results of the experiments demonstrate that our system can robustly deal with challenging scenarios such as fast camera motions and feature-poor environments while being fast enough for online operation. Our system is fully available as open source and has already been widely adopted by the robotics community.
Keywords :
feature extraction; image colour analysis; image motion analysis; image sensors; mobile robots; robot vision; 3-D mapping; Microsoft Kinect; RGB-D camera; RGB-D sensors; detailed 3-D models; domestic robots; fast camera motions; feature descriptor; feature-poor environments; flying robots; free-hand reconstruction; online operation; open source; quadrocopters; robotics community; vacuum cleaners; validation methods; visual features; Cameras; Estimation; Robot vision systems; Simultaneous localization and mapping; Visualization; Localization; RGB-D; mapping; open source; simultaneous localization and mapping (SLAM);
Journal_Title :
Robotics, IEEE Transactions on
DOI :
10.1109/TRO.2013.2279412