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Tracking 3D objects in continuous point cloud data sequences is an important research topic for mobile robots: it allows robots to monitor the environment and make decisions and adapt their motions according to the changes in the world. An example of such a typical application is visual servoing, with its key challenge to estimate the three dimensional pose of an object in real-time.

During his internship at Willow Garage, Ryohei Ueda from the JSK laboratory at University of Tokyo, worked on a novel 3D tracking library for the Point Cloud Library (PCL) project. The purpose of the library is to provide a comprehensive algorithmic base for the estimation of 3D object poses using Monte Carlo sampling techniques and for calculating the likelihood using combined weighted metrics for hyper-dimensional spaces including Cartesian data, colors, and surface normals. The libpcl_tracking library is optimized to perform computations in real-time, by employing multi CPU cores optimization, adaptive particle filtering (KLD sampling) and other modern techniques.

To find out more about Ryohei's…