StanfordVL/iai_kinect2

Name: iai_kinect2

Owner: Stanford Vision and Learning Group

Description: Tools for using the Kinect One (Kinect v2) in ROS

Created: 2018-02-11 03:13:23.0

Updated: 2018-02-11 03:13:24.0

Pushed: 2018-02-03 23:26:52.0

Homepage: null

Size: 508

Language: C++

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README

IAI Kinect2

Maintainer
Read this first

Please read this README and the ones of the individual components throughly before asking questions. We get a lot of repeated questions, so when you have a problem, we urge everyone to check the github issues (including closed ones). Your issue is very likely discussed there already.

The goal of this project is to give you a driver and the tools needed to receive data from the Kinect-2 sensor, in a way useful for robotics. You will still need to know how to use ROS to make use of it. Please follow the ROS tutorials. You will also need to learn how to work with point-clouds, or depth-clouds, or images (computer vision) to do useful things with the data.

Note: Please use the GitHub issues for questions and problems regarding the iai_kinect2 package and its components. Do not write emails.

Table of contents
Description

This is a collection of tools and libraries for a ROS Interface to the Kinect One (Kinect v2).

It contains:

FAQ
If I have any question or someting is not working, what should I do first?

First you should look at this FAQ and the FAQ from libfreenect2. Secondly, look at issue page from libfreenect2 and the issue page of iai_kinect2 for similar issues and solutions.

Point clouds are not being published?

Point clouds are only published when the launch file is used. Make sure to start kinect2_bridge with roslaunch kinect2_bridge kinect2_bridge.launch.

Will it work with OpenCV 3.0

Short answer: No.

Long answer: Yes, it is possible to compile this package with OpenCV 3.0, but it will not work. This is because cv_bridge is used, which itself is compiled with OpenCV 2.4.x in ROS Indigo/Jade and linking against both OpenCV versions is not possible. Working support for OpenCV 3.0 might come with a future ROS release.

kinect2_bridge is not working / crashing, what is wrong?

There are many reasons why kinect2_bridge might not working. The first thing to find out whether the problem is related to kinect2_bridge or libfreenect2. A good tool for testing is Protonect, it is a binary located in libfreenect2/build/bin/Protonect. It uses libfreenect2 directly with a minimal dependency on other libraries, so it is a good tool for the first tests.

Execute:

Before running kinect2_bridge please make sure Protonect is working and showing color, depth and ir images. If some of them are black, than there is a problem not related to kinect2_bridge and you should look at the issues from the libfreenect2 GitHub page for help.

If one of them works, try out the one that worked with kinect2_bridge: rosrun kinect2_bridge kinect2_bridge _depth_method:=<opengl|opencl|cpu>. You can also change the registration method with _reg_method:=<cpu|opencl>.

Protonect works fine, but kinect2_bridge is still not working / crashing.

If that is the case, you have to make sure that Protonect uses the same version of libfreenect2 as kinect2_bridge does. To do so, run make and sudo make install in the build folder again. And try out kinect2_bridge again.

ibfreenect2/build
 & sudo make install

Also make sure that you are not using OpenCV 3.0.

If it is still crashing, compile it in debug and run it with gdb:

catkin_ws>
in_make -DCMAKE_BUILD_TYPE="Debug"
evel/lib/kinect2_bridge
kinect2_bridge
nside gdb: run until it crashes and do a backtrace

Open an issue and post the problem description and the output from the backtrace (bt).

kinect2_bridge hangs and prints “waiting for clients to connect”

This is the normal behavior. 'kinect2_bridge' will only process data when clients are connected (ROS nodes listening to at least one of the topics). This saves CPU and GPU resources. As soon as you start the kinect_viewer or rostopic hz on one of the topics, processing should start.

rosdep: Cannot locate rosdep definition for [kinect2_bridge] or [kinect2_registration]

rosdep will output errors on not being able to locate [kinect2_bridge] and [kinect2_registration]. That is fine because they are all part of the iai_kinect2 package and rosdep does not know these packages.

Protonect or kinect2_bridge outputs [TransferPool::submit] failed to submit transfer

This indicates problems with the USB connection.

I still have an issue, what should I do?

First of all, check the issue pages on GitHub for similar issues, as they might contain solutions for them. By default you will only see the open issues, but if you click on closed you will the the ones solved. There is also a search field which helps to find similar issues.

If you found no solution in the issues, feel free to open a new issue for your problem. Please describe your problem in detail and provide error messages and log output.

Dependencies
Install

  1. Install the ROS. Instructions for Ubuntu 14.04

  2. Setup your ROS environment

  3. Install libfreenect2:

    Follow the instructions and enable C++11 by using cmake .. -DENABLE_CXX11=ON instead of cmake ..

    If something is not working, check out the latest stable release, for example git checkout v0.2.0.

  4. Clone this repository into your catkin workspace, install the dependencies and build it:

/catkin_ws/src/
clone https://github.com/code-iai/iai_kinect2.git
ai_kinect2
ep install -r --from-paths .
/catkin_ws
in_make -DCMAKE_BUILD_TYPE="Release"

Note: rosdep will output errors on not being able to locate [kinect2_bridge] and [depth_registration]. That is fine because they are all part of the iai_kinect2 package and rosdep does not know these packages.

Note: If you installed libfreenect2 somewhere else than in $HOME/freenect2 or a standard location like /usr/local you have to specify the path to it by adding -Dfreenect2_DIR=path_to_freenect2/lib/cmake/freenect2 to catkin_make.

  1. Connect your sensor and run kinect2_bridge:
aunch kinect2_bridge kinect2_bridge.launch
  1. Calibrate your sensor using the kinect2_calibration. Further details
  2. Add the calibration files to the kinect2_bridge/data/<serialnumber> folder. Further details
  3. Restart kinect2_bridge and view the results using rosrun kinect2_viewer kinect2_viewer kinect2 sd cloud.
GPU acceleration
OpenCL with AMD

Install the latest version of the AMD Catalyst drivers from https://support.amd.com and follow the instructions. Also install opencl-headers.

 apt-get install opencl-headers
OpenCL/CUDA with Nvidia

Go to developer.nvidia.com/cuda-downloads and select linux, x86_64, Ubuntu, 14.04, deb(network). Download the file and follow the instructions. Also install nvidia-modprobe and opencl-headers.

 apt-get install nvidia-modprobe opencl-headers

You also need to add CUDA paths to the system environment, add these lines to you ~/.bashrc:

rt LD_LIBRARY_PATH="/usr/local/cuda/lib64:${LD_LIBRARY_PATH}"
rt PATH="/usr/local/cuda/bin:${PATH}"

A system-wide configuration of the libary path can be created with the following commands:

 "/usr/local/cuda/lib64" | sudo tee /etc/ld.so.conf.d/cuda.conf
 ldconfig
OpenCL with Intel

You can either install a binary package from a PPA like ppa:floe/beignet, or build beignet yourself. It's recommended to use the binary from the PPA.

 add-apt-repository ppa:floe/beignet && sudo apt-get update
 apt-get install beignet beignet-dev opencl-headers
Citation

If you used iai_kinect2 for your work, please cite it.

c{iai_kinect2,
thor = {Wiedemeyer, Thiemo},
tle = {{IAI Kinect2}},
ganization = {Institute for Artificial Intelligence},
dress = {University Bremen},
ar = {2014 -- 2015},
wpublished = {\url{https://github.com/code-iai/iai\_kinect2}},
te = {Accessed June 12, 2015}

The result should look something similar to this (may depend on the bibliography style used):

iedemeyer, ?IAI Kinect2,? https://github.com/code-iai/iai_kinect2,
itute for Artificial Intelligence, University Bremen, 2014 ? 2015,
ssed June 12, 2015.
Screenshots

Here are some screenshots from our toolkit: color image depth image point cloud image viewer

This work is supported by the National Institutes of Health's National Center for Advancing Translational Sciences, Grant Number U24TR002306. This work is solely the responsibility of the creators and does not necessarily represent the official views of the National Institutes of Health.