ChapterPDF Available
Cloud Simulations for RoboCup
Enric Cervera1, Gustavo Casa˜n1, and Ricardo Tellez2
1Robotic Intelligence Lab, Universitat Jaume I, 12006 Castell´o de la Plana, Spain
2The Construct Sim LTD, 08007 Barcelona, Spain
Abstract. Possibly the most appealing aspect of RoboCup is working
with real robots, specially for young people. Yet as the complexity of the
task increases, the effort in software development becomes higher, and
a simulation testbed can be a valuable tool for prototyping and testing
software solutions prior to their implementation on a real robot. In fact,
several RoboCup leagues feature both real and virtual competitions. In
addition, the RoboCup community could benefit from the cooperation
and sharing of experiences among users in an online worldwide platform.
We present a simulation tool based on the cloud, which can model com-
plex robots off the shelf by using only a web browser as the base system
for learning robotics, and running competitions. Such a platform mini-
mizes costs and the troubles associated with different operating systems,
while providing a rich experience of testing, with the possibility of a
straightforward transfer to a real robot. Moreover, users can easily share
their simulations for cooperative learning.
Keywords: cloud robotics, simulation
1 Introduction
With the advent of powerful computers and graphic cards, 3D realistic simulators
are becoming popular in RoboCup leagues. Yet programming and maintaining a
simulator is complex, hard, and time consuming. A prototypical example is the
RoboCup Rescue Virtual Robot Competition, launched in 2006, which uses a
simulation software, USARSim (Unified System for Automation and Robot Sim-
ulation) [2], built on top of the Unreal game engine1. This engine has evolved
along several versions (2004, UT3, UDK) that required to rewrite the simulation
software from scratch. Initially maintained by the National Institute of Stan-
dards and Technology (NIST), but no longer supported, it recently switched to
a different platform developed by the Open Source Robotics Foundation (OSRF)
Another example is the RoboCup Junior Rescue CoSpace [7], with a simu-
lator built on top of the Microsoft Robotics Developer Studio. This framework
has not been updated since 2014, as a result there are increasing difficulties in
fixing bugs, adding support for modern robots and sensors, or working with new
versions of operating systems.
2 Enric Cervera, Gustavo Casa˜n, and Ricardo Tellez
On the other hand, RoboCup Soccer uses an open source simulator, SimSpark
[17], in the 3D simulation league. We can only wonder how much effort is repli-
cated among those simulator platforms, which face similar problems (physical
engine, graphical visualization) in different yet related domains.
In recent years we have been working on web-based laboratories for both real
robots and simulators [4]. We have developed web interfaces for systems based
on the ROS middleware [12,3], which provides a hardware abstraction layer,
enabling the user to share the same code between a real robot and its simulated
model. Our aim is the development of a common platform for robotic simula-
tions, suitable for any RoboCup virtual competition, and even for replicating the
leagues that right now only use physical robots. Such platform would be based
on a cloud infrastructure, enabling the users to run their simulations from their
browsers, and to share their experiences with other users throughout the world.
The rest of the paper is organized as follows: Section 2 outlines our cloud
simulation platform, along with some demonstration examples in competitions
and education; in Section 3, we advocate for the adoption of a common, open-
source, cloud simulation platform in RoboCup leagues; finally, Section 4 draws
some conclusions and outlines some future lines of work.
2 Cloud Simulation Platform
RDS2(ROS Development Studio) is a web application for the simulation of
robots in the cloud. The platform consists of Virtual Machines (VMs) [16] run-
ning in the cloud infrastructure provided by Amazon Web Services (AWS) [8].
Each user connects to a single, dedicated VM, running a full-featured distri-
bution of Ubuntu Linux with all the necessary software already installed and
configured: ROS, simulators, and development tools.
An advantage of VMs is that they can be mapped to different physical ma-
chines based on the power and memory requirements, e.g., a low-complexity
simulation can run in single CPU with low memory, but a high-fidelity complex
environment may use a multi-CPU machine with one or several additional GPUs
and a larger amount of RAM. In any case, the user connects to the VM through
a client machine, with no special power or system requirements, since only a
browser is needed.
The user interface consists of a web page with a login and password, which
gives access to all the tools through the web browser: no other software is needed
in the client computer. Different windows in the browser are used for the compo-
nents of the platform (notebook, simulation view, file editor, shell) as depicted
in Fig. 1.
This interface works on top of any WebGL [9] enabled browser, like Safari,
Chrome or Firefox. It can be used with any computer or device running any
of those browsers, in any operating system, including Linux, Windows, Mac, or
even tablets and smartphones.
Cloud Simulations for RoboCup 3
Fig. 1. User interface: from left to right, notebook, simulator view, file editor (top)
and shell (bottom).
The Robot Operating System (ROS) has become a de-facto standard among
robotics researchers as an open source framework for robot programming and
control [12]. Currently, two simulators are supported in the cloud platform,
Gazebo [10] and Webots [11].
ROS supports several client libraries in different programming languages.
The main supported libraries are written in C++ and Python, but there is
also active development in Lisp, C#, Go, Haskell, Java, Javascript, Julia, Lua,
Matlab, Pharo, R, and Ruby.
The main programming interface of the cloud platform consists of the Jupyter
Notebook, an open-source web application for creating and sharing documents
that contain live code, data visualization and explanatory text [13], which sup-
ports over 40 programming languages, including most of the languages supported
in ROS.
A cloud platform provides the user with the infrastructure for creating a
social network that encourages the interaction between the community members
[1]. Users can share their simulations and code, collaborate or compete against
each other. Such communities, e.g. the Scratch platform [14], have an incredible
educational potential in computer and engineering disciplines.
In the following we present some working applications of the cloud platform:
two online competitions, and an online course.
2.1 Online Competitions
One way to encourage students and robotics research is by doing contests where
the participants have to compete against each other. Two competitions have
been organized using the cloud platform and simulations of humanoid robots: a
NAO robot race, and sumo fighting between two Darwin robots.
4 Enric Cervera, Gustavo Casa˜n, and Ricardo Tellez
In the racing competition (Fig. 2), a Nao humanoid has to be programmed
to walk 10 meters as fast as possible. Participants are given a standard walk-
ing controller, which can be modified and optimized for speed and robustness.
Modifications are uploaded to each user’s account, and the system performs the
simulations and compares the results.
Fig. 2. Nao race: the robot is programmed for walking 10 meters as fast as possible,
the time is measured by an automatic chronometer at the finish line.
The Sumo Challenge (Fig. 3) was a worldwide contest, consisting of two sim-
ulated Darwin humanoid robots that must fight against each other in a simulated
sumo dojo. Participants had to build a controller for their robot, trying to knock
out the opponent. The controllers were automatically taken each day and made
to fight against the rest of participants in a Bubble Sort style league.
2.2 Online Courses
We have recently used the cloud platform in a MOOC (Massive Open Online
Course) on Autonomous Mobile Robots, where we designed a simulation envi-
ronment inspired in the RoboCup Junior Rescue competition (Fig. 4). In this
world, the robot must be programmed first to follow a line with obstacles and
intersections, then to find and pick some balls scattered around the room, and
carry them to a destination area.
The simulation platform was used in combination with a Learning Manage-
ment System based on Moodle [5]. The students worked on the lessons and
examples, developed the exercises on the simulators, and submitted their code
through Moodle workshops, with peer assessment activity, where students sub-
mit their own work and then receive a number of submissions from other students
which they must assess according to the teacher’s specifications [6].
Cloud Simulations for RoboCup 5
Fig. 3. Sumo challenge: the robots are programmed to fight each other according to
the rules, with an automatic referee for scoring the matches.
Fig. 4. MOOC simulation world inspired in the RoboCup Junior Rescue competition.
6 Enric Cervera, Gustavo Casa˜n, and Ricardo Tellez
3 A Proposal for RoboCup
From its initial challenge in soccer, RoboCup has expanded into a wide range
of domains. Though initially focused on the development of real robots, the
advantages of simulators for fast prototyping and cost reduction has led to many
of the leagues having either physical or simulated robots sub-leagues.
Each league has developed its own simulation software: while adapting to a
particular domain may be an advantage, an undesirable consequence is the need
of more resources for the development of software that could share a common
We advocate for the convergence of all the RoboCup simulators in a common
open-source cloud platform. The advantages would be the optimization of the
development resources and the availability of a cross-platform, powerful simula-
tion engine, which can be run efficiently, no matter what operating system or
hardware is used. The only requirements are a WebGL-enabled browser and an
Internet connection. The participants would also have an easier time taking part
in different competitions.
Based on the recent history of the RoboCup simulation competitions, we
believe that the community is moving towards such a common, open-source
platform. An example of this is the evolution of the RoboCup Rescue Simulation
Platform: its was based initially on the Unreal Engine, but recently was moved
to the Gazebo platform, benefitting from the progress made by the Open Source
Robotics Foundation [15]. The maintenance of the simulation environment is now
in hands of the open source community, since the simulator is no longer actively
supported by the National Institute of Standards and Technology (NIST).
Moving this league to the cloud platform would be straightforward, since the
tools (Gazebo and ROS) are already supported.
Two other different simulators are being used in RoboCup leagues: SimSpark
for RoboCup Soccer Simulation [17], and Microsoft Robotics Developer Studio
(MRDS) for RoboCup Junior CoSpace [7].
In this case, there are two ways for implementing the leagues in the cloud:
one possibility is importing the world simulation files into Webots or Gazebo,
the cloud supported simulators; the other alternative is to develop the WebGL
and ROS interfaces for those simulators, which should be feasible for SimSpark
since it already works in Linux, but quite problematic for MRDS, which only
works in Windows.
It should be noted that supporting a specific simulator is a heavy task; in fact,
MRDS has not been updated or patched since version 4.0, which was released in
early 2012. Moreover, the Robotics Division of Microsoft Research was suspended
in September 2014.
Other leagues that only used hardware platforms could be candidates to
activate their simulated counterpart: in RoboCup@Work, the KUKA youBot
platform is one candidate system for use, and this platform is readily available
in the Webots and Gazebo simulators (Fig. 5). Participants who can’t afford
such a costly physical robot would definitely benefit from the availability of a
simulated environment.
Cloud Simulations for RoboCup 7
Fig. 5. Simulated environment of a KUKA youBot platform, a candidate system for
the RoboCup@Work competition.
Competition based on low-cost platforms, like RoboCup Junior, can also
benefit from the access to a simulation platform. It would allow the users to
test their algorithms on standard platforms, or even simulate their own specific
hardware design. We have already implemented the environment of the line sub-
league of RoboCup Junior rescue (Fig. 6).
Fig. 6. Simulated environment for the RoboCup Junior Rescue competition.
3.1 Advantages of cloud simulators
These are the main advantages of using a web based simulator:
1. They do not need installation nor maintenance. Such operations are per-
formed by the web portal that provides the simulator. Hence, neither the
school nor the students have to deal with this unrelated task.
8 Enric Cervera, Gustavo Casa˜n, and Ricardo Tellez
2. Students cannot break the simulation program by making errors or miss
use of the simulation. If students make mistakes and something goes wrong
crashing the simulation, they just can relaunch the web simulation again and
start again from the initial conditions.
3. Different simulators available which allows entrance at different level of com-
plexity. A web simulation system can provide different simulators at the same
portal, each one with a different level of abstraction (for high school students,
for university students, etc).
4. Students can use any type of computer. Only a WebGL-enabled browser is
5. Students and teachers can work from anywhere. Since the only requirement
is to have access to internet, teachers and students can actually be anywhere
while doing their simulations.
6. Students can cooperate with their mates while working on the simulation.
Web simulation is by nature a collaborative thing, at the contrary of desktop
simulations. Hence, differently from desktop simulators, web simulators allow
the work of different people at the same time on the same simulation.
3.2 Drawbacks
As any system, web simulations have also drawbacks:
1. Users need a fast enough internet connection. Web simulations are run
through an internet connection, and since the simulations tend to be com-
plex, it is required to have an internet connection with fast speed.
2. By being on the cloud, web simulation inherits all the security problems that
any cloud system has. It is very difficult to ensure that the data stored in
the cloud will not be accessed by unauthorized people.
4 Conclusion and Future Work
We have presented a cloud simulation platform suitable for RoboCup Virtual
Competitions. An open-source, common simulation platform has an important
advantage over the current scattered development of specific simulators for each
RoboCup league: programming and maintaining a simulator application is hard
and time consuming. In addition, the cloud platform allows any user, anywhere,
to run a simulation with any device equipped with a WebGL-enabled browser,
be it a laptop, desktop, tablet, or even a smartphone.
Obviously, an Internet connection is needed, and the cost of the cloud in-
frastructure needs to be taken into account. We have presented a platform built
on top of AWS, which can be used initially for free. More powerful computing
configurations with an increasing number of CPUs and GPUs are available at
an additional cost.
We expect that the RoboCup community opens a debate about the adoption
of this or a similar platform for future editions of the virtual leagues. In the
Cloud Simulations for RoboCup 9
near future, we plan to offer cloud versions for all the leagues that currently
use simulators, and develop simulation versions of some other leagues that use
physical robots. The cloud allows to share simulations and code, enabling the
development of a lively community of RoboCup users, which would become a
complement and reinforcing tool for the successful RoboCup events throughout
the world.
Support of IEEE RAS through the CEMRA program (Creation of Educational
Material for Robotics and Automation) is gratefully acknowledged. This paper
describes research done at the Robotic Intelligence Laboratory. Support for this
laboratory is provided in part by Ministerio de Economia y Competitividad
(DPI2015-69041-R), by Generalitat Valenciana (PROMETEOII/2014/028) and
by Universitat Jaume I (P1-1B2014-52).
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