IRON: A Fast Interest Point Descriptor for Robust NDT-Map Matching - Reference Implementation

Features:

• IRON provides a simple interface for the alignment of 3D point clouds using 6 degrees of freedom (x, y, z, roll, pitch, yaw)
• Almost any given point cloud format can be directly used without expensive point cloud type conversion beforehand (see src/demo.cpp for an example)
• It's robust and insensitive to a large initial displacement between two point clouds (e.g. when they were captured from different locations)
• IRON uses NDT-maps as an efficient 3D data structure and is able to create them with sufficient accuracy in about 3 ms (average conversion time for a typical Kinect 1 / Asus Xtion point cloud)
• The complete alignment process takes only 10-20 ms on a single core of a modern i7 CPU (depending on registration parameters and map sizes) and is therefore well suited for real-time applications

For algorithmic details and benchmarking results please refer to the original paper:

Schmiedel, Th., Einhorn, E., Gross, H.-M. IRON: A Fast Interest Point Descriptor for Robust NDT-Map Matching and Its Application to Robot Localization. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), Hamburg, Germany, 2015

You may also visit my research page for a thorough introduction.

Required packages (Ubuntu 14.04; please install equivalent packages for your Linux distribution):

• build-essential
• libeigen3-dev
• gnuplot-x11

How to run demo?

• cd IRON
• make
• cd examples
• ./demo example1_cloud1.pcd example1_cloud2.pcd
• ./plot_means_keypoints.sh
• ./plot_result.sh

How to use the IRON registration pipeline?

• just include IRON.h into your project
• have a look at src/demo.cpp for a detailed explanation

Please contact me if you have any questions!

[email protected]