Planning-to-Calibrate

This library is an implementation of the algorithm described in Active Planning Based Extrinsic Calibration of Exteroceptive Sensors in Unkown Environments (IROS 2016). The core library is developed in C++ and MATLAB.

Planning-to-Calibrate is developed by Varun Murali, Carlos Nieto and Siddharth Choudhary as part of their work at Georgia Tech.

Prerequisites

• CMake (Ubuntu: sudo apt-get install cmake), compilation configuration tool.
• Boost (Ubuntu: sudo apt-get install libboost-all-dev), portable C++ source libraries.
• GTSAM >= 3.0, a C++ library that implement smoothing and mapping (SAM) framework in robotics and vision. Here we use factor graph implementations and inference/optimization tools provided by GTSAM. Install the MATLAB wrapper as well.

Compilation & Installation

In the planning-to-calibrate folder excute:

$ mkdir build
$ cd build
$ cmake ..
$ make -j3
$ make check  # optonal, run unit tests
$ sudo make install # this will install the matlab wrapper

Run Experiments

$ cd matlab/PlanningToCalibrate
$ run SLAMGUI.m
$ press on Run Experiments

Questions & Bug reporting

Please use Github issue tracker to report bugs. For other questions please contact Varun Murali, Carlos Nieto and Siddharth Choudhary.

Acknowledgements

This work was partially funded by the ARL MAST CTA Project 1436607 “Autonomous Multifunctional Mobile Microsystems”

Citing

If you use this work, please cite following publication:

@inproceedings{Murali16iros,
  author    = {Varun Murali and
               Carlos Neito and
               Siddharth Choudhary and
               Henrik I. Christensen},
  title     = {Active Planning based Extrinsic Calibration of Exteroceptive Sensors in Unknown Environments},
  booktitle = {2016 {IEEE/RSJ} International Conference on Intelligent Robots and Systems, Hamburg, Germany},
  year      = {2016}
}

License

Planning-to-Calibrate is released under the BSD license, reproduced in the file LICENSE in this directory.