News Articles

JediBot powered by PCL

JediBot is an autonomous robot designed to duel with humans in simulated sword fights. It was created by a group of four students in Stanford University's Experimental Robotics class, who combined a KUKA Light-Weight Robot arm for manipulation and a Microsoft Kinect for 3D sensing, along with custom software that leverages several open source libraries, including the Point Cloud Library (PCL) for 3D perception, the Reflexxes Motion Library for motion planning, and the Fast Research Interface Library for low-level control.

When facing off against a human combatant, the JediBot's software starts by analyzing the point cloud data acquired from its Microsoft Kinect 3D-camera. The Point Cloud Library is used to robustly find the pose of an opponent's sword in real time. The JediBot then quickly plans its response. Depending on the current strategy (attack or defense) an appropriate pose of the robot's sword is calculated. This pose is then sent to the Reflexxes Motion Library, which continuously plans a smooth sequence of arm motions. The resulting robot motions are directly sent to the Fast Research Interface Library, which provides low-level access to the…

Urban Robotics Extends Octree Format to PCL Open Source Community

Urban Robotics Inc., a leading provider of three-dimensional (3D) imaging sensors, software and algorithms, today announced it is making its highly scalable, spatially searchable and colorized 3D octree-based point cloud format available to the Point Cloud Library (PCL) community.

Willow Garage launched PCL in March 2011, to help accelerate 3D algorithmic work related to robotic applications. It is free for research and commercial use. The addition of Urban Robotics's software code to PCL lays the foundation for the creation of a standardized format for large-scale 3D applications. An example of such large-scale dataset representing a reconstruction of Mount St. Helens is shown in the video below.

Urban Robotics developed its octree-based format to efficiently store and manage point cloud data, and to address challenges related to the rapid processing of massive 3D images during daily operations.

"The main challenge with supported LAS and XYZ point cloud file formats is that…

An open source implementation of KinectFusion

We are happy to announce the development of a new open source implementation of KinectFusion, a simple system for 3D local mapping with an OpenNI-compatible camera. Below you can find the original SIGGRAPH video, together with a complete description of the algorithm presented in KinectFusion: Real-Time Dense Surface Mapping and Tracking.

For a quick comparison, here's a demonstration of our current implementation's capabilities:

The preliminary source code is currently available in our SVN repository's trunk in the CUDA/KinFu module. Since this code is still unreleased and under active development, we won't be able to provide support via our forums yet; however, advanced users are free to check out the code and give it a try. Be advised that this code relies heavily on the NVidia CUDA development libraries for GPU optimizations and will require a compatible GPU for best results.

Moving forward, we continue to refine and improve the system, and we are hoping to improve upon the original…

PCL 1.3.1!

PCL 1.3.1

A new version of PCL is ready! PCL 1.3.1 includes lots of bug-fixes, and you can check out the complete list here:

The source code is ready to download now from

and if you prefer binary installers, we'll have those posted on the downloads page sometime in the next few days.

And as always, a big thanks to all the users and developers who helped us track down and fix these bugs.

PCL wins the 2011 OSS World Challenge Grand Prize

Point Cloud Library (PCL) has been recognized with the Grand Prize of the 2011 Open Source Software (OSS) World Challenge ( This is the 5th year for the World Challenge, whose purpose is to promote the development of open source software and to expand the interaction between open source communities all over the world. An international committee evaluated a total of 56 open source projects from 22 countries for this year's World Challenge. Their job must have been difficult because of the overall high quality of projects. The winners of the other four prizes were:

  • the Shark Machine Learning Library project (a collaboration between the Institute for Neural Computation at Ruhr University Bochum, nisys Gmbh, the University of Copenhagen, and Honda Research Institute Europe)
  • DIADEM (Oxford University, UK)
  • USM Extract (University of Science, Malaysia)
  • Meego Photo Sharing (Jiao Tong University, Shanghai)

The awards were announced at an inspirational event hosted by the Ministry of Knowledge and Economy in Seoul, South Korea. High ranking officials from the Ministry and other parts of the government participated, gave talks, and handed out the prizes. Deborah Bryant gave the keynote talk on "Open Governments" and…

PCL and Trimble Code Sprint 2012

It is our immense pleasure to announce the beginning of a new PCL Code Sprint sponsored by Trimble: PCL-TRCS!

PCL Code Sprints are intended to rapidly advance the capabilities of the Point Cloud Library in a certain area/subject by offering stipends to talented student developers and pairing them with knowledgeable mentors for several months of accelerated software development. These sprints have been inspired by the Google Summer Of Code (GSOC) initiative, and we will be following the same basic model. Projects will run for an initial period of 3-6 months with the same structure and performance evaluations as the GSOC program, and all of the code produced will be open source.

For this winter's PCL-Trimble Code Sprint, we have identified the following important areas for further development in PCL, and we are therefore searching for outstanding candidates (and mentors) to work on the following projects:

  1. Automated decimation: automatically reduce the number of points in the point cloud based upon the definition of a feature (i.e., not a generic spatial sampling). For example reduce the number of points used to define simple surfaces, such as…

PCL 1.3.0!

We're thrilled to announce that Point Cloud Library (PCL) version 1.3.0 has been released!

PCL 1.3

You can find the latest source and binaries on our download page:

Thanks to the hard work of all of our awesome contributors, we've got a big list of new features. From 1.3 we are constructing the Changelist for each library separately, as they can in theory be mixed and matched with older versions (though we officially do not support this yet). The most notable overall changes are:

  • removed wxWidgets as a dependency from PCL and implemented the Image visualization classes using VTK
  • removed cminpack as a dependency from PCL and implemented the LM optimization functionality using Eigen
  • added a new library called PCL Search (libpcl_search) that has a more uniform API for nearest neighbor searches and stripped the unneeded functionality from libpcl_kdtree and libpcl_octree. Search now wraps KdTree and Octree for NN calls. This is a MINOR API BREAKING CHANGE. To change your code switch from:
    pcl::KdTree -> pcl::Search (if the purpose is to use one of its children for search)
    pcl::KdTreeFLANN -> pcl::search::KdTree
    pcl::OrganizedDataIndex -> pcl::search::OrganizedNeighbor
  • improved…

Large Scale 3D Point Cloud Mapping in PCL

Jochen Sprickerhof from the Knowledge-Based Systems Group of University of Osnabrück (Germany) visited Willow Garage this summer to do an internship on 3D registration and mapping.

Assembling massive datasets from a large number of individual point clouds is an important part of mobile robotics research. This allows robots to see beyond their immediate surroundings, localize in both 2D and 3D, and share large-scale maps built by other robots. One of the challenges here is how to efficiently estimate and correct the pose error in the trajectory of the robot, without sacrificing accuracy. For example, correcting high-dimensional registration data graphs that represent a large building or a city can take a very long time.

During his internship, Jochen ported his registration framework called ELCH (Explicit Loop Closing Heuristic) into the Point Cloud Library framework. ELCH tries to correct collected sensor data by finding loops in the robot trajectory, estimating the pose error the robot accumulated while driving along the loop, using point cloud registration,…

PCL-TOCS kickstart!

When we announced PCL-TOCS just a few weeks ago, we had no idea about the amazing level of interest that we would get from the community. After much deliberation, we realized that while we would like to accept more than half of the submissions, we would have to make a decision and select two for this first PCL code sprint. It is therefore our pleasure to announce the official start and the candidates that will be working on TOCS for the next 3 months:


Scene Simulation for RGB-D Camera Localization

Maurice Fallon, Hordur Johannsson and John Leonard in MIT have been working on methods for 3D localization using RGB-D data from the Microsoft Kinect - KMCL.

First an entire building floor of the Stata Center was captured using a Kinect. The data was then used to build a simple plane-based 3D model using PCL (and sensor poses from Lidar-based SLAM) of about 1MB in size.

They then developed a robust algorithm for localization within the model in real-time using a particle filter.

The approach works by generating simulated range images using the 3D model for a virtual camera located the different particle poses. This approach correctly simulates the image formation model and allows for a disparity parameterized likelihood function. This allows the filter to correctly utilize the very noisy RGB-D points up to 20 meters away - data that has usually been discarded up to this.

Particles are propagated using the FOVIS…

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