Algorithms for Robot Navigation

CS 480: Robotics & 3D Printing Lecture, Dr. Lawlor

Iterative Closest Point: match up two point clouds by aligning each point with the closest point on the other mesh.  Useful for correlating point clouds from Kinect or other depth scanners.  (Free implementation in MeshLab.)

Random Sample Consensus (RANSAC): avoid outliers, by randomly picking points until you find a set that is self-consistent.

Simultaneous Localization and Mapping (SLAM): match up series of LIDAR scans using RANSAC.