README.md

Iterative Probabilistic Data Association (IPDA)

Robust Point Cloud Registration Using One-To-Many Iterative Probabilistic Data Associations ("Robust ICP"). Contains wrappers for ICP, GICP, NDT as well as the source code for IPDA.

Authors

• Simone Fontana ([email protected])
• Timo Hinzmann ([email protected])
• Gabriel Agamennoni ([email protected])

Maintainers

• Timo Hinzmann ([email protected])

Getting started

• Dependencies
• Installation
• Samples
• Datasets
• Jenkins

Citing

The Iterative Probabilistic Data Association algorithm was introduced by the following paper:

G. Agamennoni, S. Fontana, R. Y. Siegwart and D. G. Sorrenti "Point Clouds Registration with Probabilistic Data Association", in International Conference on Intelligent Robots and Systems (IROS), 2016.

@INPROCEEDINGS{agamennoniIROS16,
   Author = {G. Agamennoni, S. Fontana, R. Y. Siegwart and D. G. Sorrenti},
   Title = {Point Clouds Registration with Probabilistic Data Association},
   Booktitle = {Proc. of The International Conference on Intelligent Robots and Systems (IROS)},
   Year = {2016}
}

The algorithm was successfully employed in the following publication:

T. Hinzmann, T. Stastny, G. Conte, P. Doherty, P. Rudol, M. Wzorek, E. Galceran, R. Siegwart, I. Gilitschenski "Collaborative 3D Reconstruction using Heterogeneous UAVs: System and Experiments", in The 15th International Symposium on Experimental Robotics (ISER), 2016.

@inproceedings{iser_2016_hinzmann,
  author    = {Timo Hinzmann and Thomas Stastny and Gianpaolo Conte and Patrick Doherty and Piotr Rudol and Marius Wzorek and Enric Galceran and Roland Siegwart and Igor Gilitschenski},
  title     = {Collaborative 3D Reconstruction using Heterogeneous UAVs: System and Experiments},
  booktitle = {Experimental Robotics - The 15th International Symposium on Experimental
               Robotics, {ISER} 2016, October 3-6, 2016, Tokyo, Japan},
  year      = {2016},
}