A Modular Optimization Framework for Localization and Mapping
Identifiers
Share
Metadata
Show full item recordAuthor/s
Blanco Claraco, José LuisDate
2019Abstract
This work approaches the challenge of how to
divide the problem of Simultaneous Localization and Mapping
(SLAM) into its smallest possible constituents, in such a way
that the reusability and interchangeability of each such module
is maximized. In particular, most components in the proposed
system should be not aware of details such that whether the map
comprises a single global map or a set of local submaps, whether
the state vector is defined in SE(2) or SE(3), with or without
velocity, etc. Any number of heterogeneous sensors should be
used together and their information fused seamlessly into a
consistent localization solution. The resulting system would be
useful for researchers, easing the development of reproducible
research and enabling the quick adoption of state-of-the-art
algorithms into product prototypes. Our implementation has
been tested with different sensors against the KITTI, EuRoC,
and KAIST datasets. In this paper we focus on an introduction
to the fr...
Palabra/s clave
mobile robotics
SLAM