[robotics-worldwide] multisensor datasets from project Rawseeds are online

The Rawseeds Project rawseeds at elet.polimi.it
Mon Jun 29 13:00:33 PDT 2009


Dear all,

the Rawseeds project (http://www.rawseeds.org/) is an 
EU-funded effort
aimed at building a high-quality "Benchmarking Toolkit" 
for Simultaneous
Localization And Mapping. The first element of the 
Toolkit, i.e., a set
of 11 multisensor datasets, can be reached from:

  http://www.rawseeds.org/home/category/benchmarking-toolkit/datasets/

All of the datasets include data from 4 LRF, a trinocular 
stereo rig, a
panoramic camera, an IMU, sonars (indoors only), a 
low-cost monocular
camera, and classical odometry.

Rawseeds' datasets cover indoor, outdoor and mixed 
environments. Each of
them includes the full output of the sensors during an 
uninterrupted
exploration session 20+ minutes long, plus suitable ground 
truth data
covering part of the explored areas: RTK GPS for outdoor 
datasets, and
~10cm-precision data in a "ground truth area" for indoor 
datasets.
Sensor streams and ground truth data are time-synchronized 
and have been
subjected to extensive validation.

In a few weeks the second part of the Benchmarking Toolkit 
will be
published. It is a set of problems, called "Benchmark 
Problems", which
use our datasets as their input. The key point is that 
each BP includes
a set of precisely defined *performance metrics*, to be 
used to evaluate
the output of any algorithm which solves the BP. The 
description of such
an algorithm, together with the value of the performance 
metrics and
other associated information, is called a "Benchmark 
Solution".
Rawseeds' BPs are presently focused on SLAM, but other 
types of problems
might be proposed in the future.

The third - and final - part of the Benchmarking Toolkit 
will be a set
of Benchmark Solutions based on state-of-the-art 
algorithms. These are
intended as examples and references for users: in fact, as 
soon as they
are online, Rawseeds will start asking the robotics 
community for the
submission of new BSs. Any algorithm which complies with 
the
specifications of a BS will be published along with the 
other BSs.

The key point is this: as all BSs associated to the same 
BP include
their own values for the performance metrics defined by 
the BP, so
*benchmarking of algorithms for autonomous robotics, and 
quantitative
comparison between different algorithms, will become 
feasible*. This
is, indeed, the goal of Rawseeds.

Publishing an algorithm (in the form of a BS) on Rawseeds' 
website
will be a good way to give it visibility *and*, at the 
same time,
will make its performances immediately and quantitatively 
comparable
with those of established algorithms. So we hope to 
quickly gather a
good number of users/contributors. By the way, 
transforming an
existing algorithm into a BS is a straightforward process; 
and a
flexible Intellectual Property Management system has been 
defined.

More information about Rawseeds and its Benchmarking 
Toolkit can of
course be found on the project's website,

  http://www.rawseeds.org/

along with a contact form, a forum, and more. We hope to 
see you there!

The Rawseeds Consortium


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