Added *.bib file and started adding citations to README.md

README.md

@@ -2,9 +2,9 @@
 
 **Important Note**
 
-As of August 1 2020, the `develop` branch is officially in "Pre 4.1" mode, and features deprecated in 4.0 have been removed. Please use the last [4.0.3 release](https://github.com/borglab/gtsam/releases/tag/4.0.3) if you need those features. 
+As of Dec 2021, the `develop` branch is officially in "Pre 4.2" mode. A great new feature we will be adding in 4.2 is *hybrid inference* a la DCSLAM (Kevin Doherty et al) and we envision several API-breaking changes will happen in the discrete folder.
 
-However, most are easily converted and can be tracked down (in 4.0.3) by disabling the cmake flag `GTSAM_ALLOW_DEPRECATED_SINCE_V4`.
+In addition, features deprecated in 4.1 will be removed. Please use the last [4.1.1 release](https://github.com/borglab/gtsam/releases/tag/4.1.1) if you need those features. However, most (not all, unfortunately) are easily converted and can be tracked down (in 4.1.1) by disabling the cmake flag `GTSAM_ALLOW_DEPRECATED_SINCE_V42`.
 
 ## What is GTSAM?
 
@@ -40,7 +40,7 @@ $ make install
 
 Prerequisites:
 
-- [Boost](http://www.boost.org/users/download/) >= 1.58 (Ubuntu: `sudo apt-get install libboost-all-dev`)
+- [Boost](http://www.boost.org/users/download/) >= 1.65 (Ubuntu: `sudo apt-get install libboost-all-dev`)
 - [CMake](http://www.cmake.org/cmake/resources/software.html) >= 3.0 (Ubuntu: `sudo apt-get install cmake`)
 - A modern compiler, i.e., at least gcc 4.7.3 on Linux.
 
@@ -55,29 +55,79 @@ Optional prerequisites - used automatically if findable by CMake:
 
 GTSAM 4 introduces several new features, most notably Expressions and a Python toolbox. It also introduces traits, a C++ technique that allows optimizing with non-GTSAM types. That opens the door to retiring geometric types such as Point2 and Point3 to pure Eigen types, which we also do. A significant change which will not trigger a compile error is that zero-initializing of Point2 and Point3 is deprecated, so please be aware that this might render functions using their default constructor incorrect.
 
-GTSAM 4 also deprecated some legacy functionality and wrongly named methods. If you are on a 4.0.X release, you can define the flag GTSAM_ALLOW_DEPRECATED_SINCE_V4 to use the deprecated methods.
+GTSAM 4 also deprecated some legacy functionality and wrongly named methods. If you are on a 4.0.X release, you can define the flag `GTSAM_ALLOW_DEPRECATED_SINCE_V4` to use the deprecated methods.
 
-GTSAM 4.1 added a new pybind wrapper, and **removed** the deprecated functionality. There is a flag GTSAM_ALLOW_DEPRECATED_SINCE_V41 for newly deprecated methods since the 4.1 release, which is on by default, allowing anyone to just pull version 4.1 and compile.
+GTSAM 4.1 added a new pybind wrapper, and **removed** the deprecated functionality. There is a flag `GTSAM_ALLOW_DEPRECATED_SINCE_V42` for newly deprecated methods since the 4.1 release, which is on by default, allowing anyone to just pull version 4.1 and compile.
 
 
 ## Wrappers
 
 We provide support for [MATLAB](matlab/README.md) and [Python](python/README.md) wrappers for GTSAM. Please refer to the linked documents for more details.
 
+## Citation
+
+If you are using GTSAM for academic work, please use the following citation:
+
+```
+@software{gtsam,
+  author       = {Frank Dellaert and Richard Roberts and Varun Agrawal and Alex Cunningham and Chris Beall and Duy-Nguyen Ta and Fan Jiang and lucacarlone and nikai and Jose Luis Blanco-Claraco and Stephen Williams and ydjian and John Lambert and Andy Melim and Zhaoyang Lv and Akshay Krishnan and Jing Dong and Gerry Chen and Krunal Chande and balderdash-devil and DiffDecisionTrees and Sungtae An and mpaluri and Ellon Paiva Mendes and Mike Bosse and Akash Patel and Ayush Baid and Paul Furgale and matthewbroadwaynavenio and roderick-koehle},
+  title        = {borglab/gtsam},
+  month        = may,
+  year         = 2022,
+  publisher    = {Zenodo},
+  version      = {4.2a7},
+  doi          = {10.5281/zenodo.5794541},
+  url          = {https://doi.org/10.5281/zenodo.5794541}
+}
+```
+
+You can also get the latest citation available from Zenodo below:
+
+[![DOI](https://zenodo.org/badge/86362856.svg)](https://doi.org/10.5281/zenodo.5794541)
+
+Specific formats are available in the bottom-right corner of the Zenodo page.
+
+Citation for IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation:
+```
+@book{imu_preintegration,
+    author={Christian Forster and Luca Carlone and Frank Dellaert and Davide Scaramuzza},
+    title={IMU preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation},
+    year={2015}
+}
+
+
+
+```
+
+
+Citation for Factor Graphs for Robot Perception:
+```
+@book{factor_graphs_for_robot_perception,
+    author={Frank Dellaert and Michael Kaess},
+    year={2017},
+    title={Factor Graphs for Robot Perception},
+    publisher={Foundations and Trends in Robotics, Vol. 6},
+    url={http://www.cs.cmu.edu/~kaess/pub/Dellaert17fnt.pdf}
+}
+
+
+```
+
+
 ## The Preintegrated IMU Factor
 
 GTSAM includes a state of the art IMU handling scheme based on
 
-- Todd Lupton and Salah Sukkarieh, "Visual-Inertial-Aided Navigation for High-Dynamic Motion in Built Environments Without Initial Conditions", TRO, 28(1):61-76, 2012. [[link]](https://ieeexplore.ieee.org/document/6092505)
+- Todd Lupton and Salah Sukkarieh, _"Visual-Inertial-Aided Navigation for High-Dynamic Motion in Built Environments Without Initial Conditions"_, TRO, 28(1):61-76, 2012. [[link]](https://ieeexplore.ieee.org/document/6092505)
 
 Our implementation improves on this using integration on the manifold, as detailed in
 
-- Luca Carlone, Zsolt Kira, Chris Beall, Vadim Indelman, and Frank Dellaert, "Eliminating conditionally independent sets in factor graphs: a unifying perspective based on smart factors", Int. Conf. on Robotics and Automation (ICRA), 2014. [[link]](https://ieeexplore.ieee.org/abstract/document/6907483)
-- Christian Forster, Luca Carlone, Frank Dellaert, and Davide Scaramuzza, "IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation", Robotics: Science and Systems (RSS), 2015. [[link]](http://www.roboticsproceedings.org/rss11/p06.pdf)
+- Luca Carlone, Zsolt Kira, Chris Beall, Vadim Indelman, and Frank Dellaert, _"Eliminating conditionally independent sets in factor graphs: a unifying perspective based on smart factors"_, Int. Conf. on Robotics and Automation (ICRA), 2014. [[link]](https://ieeexplore.ieee.org/abstract/document/6907483)
+- Christian Forster, Luca Carlone, Frank Dellaert, and Davide Scaramuzza, _"IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation"_, Robotics: Science and Systems (RSS), 2015. [[link]](http://www.roboticsproceedings.org/rss11/p06.pdf)
 
 If you are using the factor in academic work, please cite the publications above.
 
-In GTSAM 4 a new and more efficient implementation, based on integrating on the NavState tangent space and detailed in [this document](doc/ImuFactor.pdf), is enabled by default. To switch to the RSS 2015 version, set the flag **GTSAM_TANGENT_PREINTEGRATION** to OFF.
+In GTSAM 4 a new and more efficient implementation, based on integrating on the NavState tangent space and detailed in [this document](doc/ImuFactor.pdf), is enabled by default. To switch to the RSS 2015 version, set the flag `GTSAM_TANGENT_PREINTEGRATION` to OFF.
 
 
 ## Additional Information