rosR

Overview

This package provides an simple interface of standard ros-functionalities for the programming language R. We hope that it might be useful to make the R capabilities for statistical analyses and visualization also usable for the robotic community. In contrast to other language implementations, such as rospy, rosjava, etc. this is not a pure R implementation, it is a mixture of pure R, SWIG generated functions, and system commands. This combination was required to overcome some limitations of R, such as single threaded, lacking support for sockets and handling of raw streams. Nevertheless, this package can be used to define and use typical ROS publishers and subscribers in R, messages are automatically and online generated from the definition files, and it integrates the possibility to read and therefore analyse bag-files in R. We will explain this in more detail within the next sections.

See also rosR_demos.

Installation

We divided this section into two parts. For those who come from the ROS side, it will be probably easy to install and to use this packet (of course they will probably have to cope with the R-code). Coming from the R side with no experience about ROS, it will be hard to install and run this package.

ROS-Side

If you have already some expertise on working with ROS, then you can install rosR just like any ordinary ros-package. Three additional dependencies are required before you can compile it:

• Swig3.0 is required for interfacing C code, and only swig3.0 can generate appropriate code for R.

  $ sudo apt-get install swig3.0
  

• The second part is an R base installation

  $ sudo apt-get install r-base
  

• r-cran-rcpp includes all required C source to develop R packages

  $ sudo apt-get install r-cran-rcpp
  

Afterwards compile this package with catkin_make… That’s all folks!

If the compilation fails, because lib lRcpp was not found, search for it:

$ locate Rcpp.so
/usr/lib/R/site-library/Rcpp/libs/Rcpp.so

enter the directory and create a symbolic link:

$ cd /lib/R/site-library/Rcpp/libs
$ sudo ln -s Rcpp.so libRcpp.so
$ cd -

and run catkin_make again …

R-Side

Within this subsection we will describe all steps that are required to install ros-indigo under an Ubuntu 14.04 32-bit (with long time support) and then our extension for the R-programming language (especially for users with totally no ROS experience). The first steps were taken from the manual (http://www.ros.org/wiki/indigo/Installation/Ubuntu) and we guess, you already have installed Ubuntu on your PC.

Publish Subscribe

R–Publisher

Defining a publisher in R is nearly as simple as in Python. First of all you will have to load this package into your R environment, what can be done with the following command:

> source(paste(system("rospack find rosR",intern=T),"/lib/ros.R",sep=""),chdir=T)

This looks a bit complex, but have trust, this is the only complex command that is required. We did not develop a package that can be directly installed in R but more a ros package and therefore it can be somewhere on your systems, as ros packages do it normaly. Therefore the commandline program rospack is involved to find the location of your rosR installation. But thats all, now you can use all of our ros-functions in R.

As in most programs you start with the initialization of your new ros node and so we do:

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