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gtsam package

gtsam 4.2~9+dfsg-6build1 source package in Ubuntu

Changelog

gtsam (4.2~9+dfsg-6build1) noble; urgency=medium

  * No-change rebuild to build with python3.12 as supported.

 -- Matthias Klose <email address hidden>  Thu, 02 Nov 2023 09:20:41 +0100

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Uploaded by:
Matthias Klose
Uploaded to:
Noble
Original maintainer:
Debian Science Team
Architectures:
any all
Section:
misc
Urgency:
Medium Urgency

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Series Pocket Published Component Section

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File Size SHA-256 Checksum
gtsam_4.2~9+dfsg.orig.tar.xz 10.9 MiB 38a26c43a8513c57a5d56041ca9394a6b60fedf59593792753c5ec1619b7c093
gtsam_4.2~9+dfsg-6build1.debian.tar.xz 19.2 KiB f1e6210258c7d5fd3eeff11e4498e5af63d65b756613cf3416a99d0a206eda31
gtsam_4.2~9+dfsg-6build1.dsc 2.6 KiB daa6d4390ed319cb90d6d4d9d06ded8fea779efa2f91907782e7d89aa85c0945

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Binary packages built by this source

libgtsam-dev: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.
 .
 Development files

libgtsam-doc: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.
 .
 Documentation

libgtsam4: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.

libgtsam4-dbgsym: debug symbols for libgtsam4
python3-gtsam: Factor graphs for sensor fusion in robotics

 GTSAM is a C++ library that implements sensor fusion for robotics and computer
 vision applications, including SLAM (Simultaneous Localization and Mapping), VO
 (Visual Odometry), and SFM (Structure from Motion). It uses factor graphs and
 Bayes networks as the underlying computing paradigm rather than sparse matrices
 to optimize for the most probable configuration or an optimal plan. Coupled
 with a capable sensor front-end (not provided here), GTSAM powers many
 impressive autonomous systems, in both academia and industry.
 .
 Python library

python3-gtsam-dbgsym: debug symbols for python3-gtsam