P. Henry, M. Krainin, E. Herbst, X. Ren, and D. Fox.
RGB-D Mapping: Using Depth
Cameras for Dense 3D Modeling of Indoor Environments
Proc. of International Symposium on Experimental
Robotics (ISER), 2010
Abstract
RGB-D cameras are novel sensing systems that capture RGB images along
with per-pixel depth information. In this paper we investigate how
such cameras can be used in the context of robotics, specifically
for building dense 3D maps of indoor environments. Such maps have
applications in robot navigation, manip- ulation, semantic mapping,
and telepresence. We present RGB-D Mapping, a full 3D mapping system
that utilizes a novel joint optimization algorithm combining visual
features and shape-based alignment. Visual and depth information are
also combined for view-based loop closure detection, followed by pose
optimization to achieve globally consistent maps. We evaluate RGB-D
Mapping on two large indoor environments, and show that it effectively
combines the visual and shape information available from RGB-D cameras.