基于优化方法的机器人同步定位与地图创建(SLAM)
后端(Back-end)设计技术收集
Sason@CSDN
持续更新中。
当前更新日期：2013.04.27
学习SLAM首推2个网站：
1. WIKI上的SLAM介绍与资源总结：http://en.wikipedia.org/wiki/Simultaneous_localization_and_mapping
2. http://www.openslam.org/
1. The pose graph of Olson
http://rvsn.csail.mit.edu/graphoptim/
2. TreeMap
http://www.openslam.org/treemap.html
Treemap is an algorithm for feature based Gaussian SLAM. Actually it is an algorithm for incremental probabilistic inference in a high dimensional Gaussian defined as the product of many low dimensional Gaussians (incremental least square). Treemap can handle different variants of SLAM. Everything, that's specific to a SLAM variant or even to SLAM as a problem is contained in a small driver layer that can be adapted by the user.
3. TORO
http://www.openslam.org/toro.html
TORO is an optimization approach for constraint-network. It provides an efficient, gradient descent-based error minimization procedure. There is a 2D and a 3D version of TORO available.
4. Square Root SAM
http://www.cc.gatech.edu/~kaess/pub/Dellaert06ijrr.html
5. iSAM and iSAM2
http://people.csail.mit.edu/kaess/isam/
http://people.csail.mit.edu/kaess/pub/Kaess12ijrr.html
iSAM is a general optimization library for incremental sparse nonlinear problems as encountered in simultaneous localization and mapping (SLAM).
6. Sparse Pose Ajustment
http://www.ros.org/research/2010/spa/
7. g2o
http://www.openslam.org/g2o.html
g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has been designed to be easily extensible to a wide range of problems and a new problem typically can be specified in a few lines of code. The current implementation provides solutions to several variants of SLAM and BA.
8. Vertigo
http://www.tu-chemnitz.de/etit/proaut/forschung/robustSLAM.html.en
欢迎来到我的CSDN博客：http://blog.csdn.net/anshan1984/