maplab: An Open Framework for Research in Visual-inertial Mapping and Localization

Github:
github.com/ethz-asl/maplab
ResearchGate:
www.researchgate.net/publicat...
Abstract- Robust and accurate visual-inertial estimation is
crucial to many of today’s challenges in robotics. Being able
to localize against a prior map and obtain accurate and drift-
free pose estimates can push the applicability of such systems
even further. Most of the currently available solutions, however,
either focus on a single session use-case, lack localization
capabilities or an end-to-end pipeline. We believe that only
a complete system, combining state-of-the-art algorithms, scal-
able multi-session mapping tools, and a flexible user interface,
can become an efficient research platform.
We therefore present maplab, an open, research-oriented
visual-inertial mapping framework for processing and ma-
nipulating multi-session maps, written in C++. On the one
hand, maplab can be seen as a ready-to-use visual-inertial
mapping and localization system. On the other hand, maplab
provides the research community with a collection of multi-
session mapping tools that include map merging, visual-inertial
batch optimization, and loop closure. Furthermore, it includes
an online frontend that can create visual-inertial maps and also
track a global drift-free pose within a localization map. In this
paper, we present the system architecture, five use-cases, and
evaluations of the system on public datasets. The source code
of maplab is freely available for the benefit of the robotics
research community.

[@florentinalexandruiftimie8214]

this is very cool. very great of you guys that you open source the project

[@itamarcus]

excellent work!!

[@gunhatornie]

I'm sure ilness can gather the rest