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RFS octomap



Dear people,

I am looking for a sponsor for my package octomap [1] . The package is hosted 
in our git:

ssh://git.debian.org/git/debian-science/packages/octomap.git

it's a part of the robotics blend and the SoB page is filled. [2]

The package seem lintian clean in my pbuilder environment.

Thanks in advance,


Leopold

[1] https://lists.debian.org/debian-devel/2014/03/msg00477.html
[2] https://wiki.debian.org/DebianPureBlends/SoB


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* Package name    : octomap
  Version         : 1.6.6
  Upstream Author : Armin Hornung, Kai M. Wurm, Maren Bennewitz, Cyrill 
Stachniss and Wolfram Burgard <octomap@googlegroups.com>
* URL             : http://octomap.github.io/
* License         : GPL-2 and BSD-3-Clause
  Programming Lang: C++
  Description     : An Efficient Probabilistic 3D Mapping Framework Based on 
Octrees

 The OctoMap library implements a 3D occupancy grid mapping approach,
providing data structures and mapping algorithms in C++ particularly suited
for robotics. The map implementation is based on an octree and is designed
to meet the following requirements:

 * Full 3D model. The map is able to model arbitrary environments without
prior assumptions about it. The representation models occupied areas as well
as free space. Unknown areas of the environment are implicitly encoded in
the map. While the distinction between free and occupied space is essential
for safe robot navigation, information about unknown areas is important,
e.g., for autonomous exploration of an environment.
 * Updatable. It is possible to add new information or sensor readings at
any time. Modeling and updating is done in a probabilistic fashion. This
accounts for sensor noise or measurements which result from dynamic changes
in the environment, e.g., because of dynamic objects. Furthermore, multiple
robots are able to contribute to the same map and a previously recorded map
is extendable when new areas are explored.
 * Flexible. The extent of the map does not have to be known in advance.
Instead, the map is dynamically expanded as needed. The map is
multi-resolution so that, for instance, a high-level planner is able to use
a coarse map, while a local planner may operate using a fine resolution.
This also allows for efficient visualizations which scale from coarse
overviews to detailed close-up views.
 * Compact. The map is stored efficiently, both in memory and on disk. It
is possible to generate compressed files for later usage or convenient
exchange between robots even under bandwidth constraints.




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