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The RobotCub Project:Research on the iCub Platform

Klaus Raizer, PhD student, Unicamp

Abstract—This text is an introduction to the humanoid robotic platform iCub and the RobotCub project. The importanceof an embodied humanoid robot for the study of human-like cognition is briefly explained and the idea of a completelyopen-source platform is introduced. The RobotCub is a project financed by the European union commission, withthe objective of advancing the current understanding of cognitive systems. The platform is essentially composed ofa physical humanoid robot named iCub and a physically realistic simulator. Some comments on the works from theliterature, related to the project, are made and future work is proposed.

Index Terms—Embodiment, humanoid robotics, simulated robotics, cognition, artificial intelligence, iCub, RobotCub.

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1 INTRODUCTION

ONE of the turning points in the history ofartificial intelligence was the publication

of two papers by Robert Brooks named Intelli-gence without reason [1] and Intelligence withoutrepresentation [2].

Until then it was believed that any systemexhibiting a certain degree of perceived intel-ligence must operate by manipulation of sym-bols [3], as stated by Newell and Simon [4]: ”aphysical symbol system has the necessary andsufficient means for general intelligent action”.

Brooks argued however that to build an in-telligent system one could not rely on sym-bolic representations, but have its representa-tions grounded in the physical world, since theworld is the best model of itself there couldpossibly exist [5]. In order for this to hold true,the system or robotic agent must have a body,and this body must be situated, or embed-ded, into an environment. This intelligent agentmust be embodied.

Embodiment can be understood as an agentpossessing a physically-active body capable ofmoving in space, manipulating its environ-

• K. Raizer is with the School of Electrical and Computer Engineer-ing at the Department of Computer Engineering and IndustrialAutomation , State University of Campinas, Campinas, SP, Brazil.E-mail: klaus@dca.fee.unicamp.br

Manuscript received June 30, 2010

ment, altering its state and experiencing thephysical forces implied inherent to this inter-action [6]. Ziemke however characterized fivedifferent types of embodiment [7]:

1) Structural coupling between agent andenvironment: meaning the system can bedisturbed by the environment and theenvironment can be disturbed and influ-enced by the system as well.

2) Historical embodiment: which is formedby the resultant history of the previouslymentioned structural coupling

3) Physical embodiment: the agent is capa-ble of acting on the environment by theexertion of forces

4) Organismoid embodiment: In the sense ofa morphological or functional similaritybetween the robotic agent and other or-ganisms, such as humanoid robots, insect-like robots and so on and so forth.

5) Organismic embodiment of autopoietic,living systems: case when the artificialagent is closer to a biological one.

The first type of embodiment is more generalthan the following ones and Ziemke suggeststhat humanoid embodiment could be consid-ered a special case of organismoid embodiment[7]. He then stresses the potential interest ofthis sort of system for cognitive science.

The fundamental idea is that the morphology

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of the robot is a crucial part of its cognitive sys-tem. Based on this argument many humanoidrobotic platforms have been developed andused for research in various fields such aspsychology, computer vision, control and socialinteraction.

This paper reports about the iCub humanoidrobotic platform, produced by the RobotCubresearch initiative which aims at broadeningour knowledge on cognitive systems such asthese.

krJune 30, 2010

2 THE ROBOTCUB PROJECT

ROBOTCUB is the name of an Europeanresearch initiative with the objective of

studying embodied cognition. Its goal is thento create a humanoid robotic platform, callediCub, in order to advance the current under-standing of cognitive systems.

Since it is assumed that manipulation playsa vital role on the development of cognitivecapability, special attention was given to thedevelopment of iCub’s upper part, includingarms, torso, head and hands [8], giving it amaximum number of degrees of freedom.

The robot was build to have the overalldimensions of a 3.5 years old child. It has atotal of 53 actuated degrees of freedom being41 for the upper body and 12 for the lowerbody.

Fig. 1. iCub CAD drawings: front and side views

Special attention was given to the construc-tion of iCub’s hand, which can be seen inFigure 2. The flexing of the fingers is controlledby those tendons while their extension is dic-tated by spring system. The thumb, index andmiddle finger have independent actuator whilethe last two fingers are actuated together by thesame motor.

Fig. 2. iCub hand: 9 degrees of freedom, actu-ated by tendons moved by motors located in theforearms [9]

The robot’s lower body is able to supportcrawling, as can be seen on Figure 3, givingiCub the ability to explore the surroundingenvironment and revert to a sitting position soit can manipulate objects on the floor.

The constraints in size, available technologyand the experience of the consortium were thedeciding factors while making design choices.The robot includes electric motors do controlits joints, cameras, microphones, gyroscopes,linear accelerometers, encoders, temperatureand current consumption sensors, force/torquesensors and also tactile sensors [8].

The software controlling iCub is potentiallyparallel and distributed, being based on a mid-dleware called YARP.

2.1 YARP

YARP stands for ”Yet Another Robot Plat-form”, and is an open-source platform for

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Fig. 3. iCub robot crawling on the floor

long-term software development for applica-tions that are computation-intensive and de-pend on constantly changing hardware.

One of the major problems concerning hu-manoid robotic platforms until now has beenthe fact that most of the technology developedfor a certain robot couldn’t be properly reusedin another project. All controlling software andbehaviour modules developed end up beingdiscarded once the project reaches its finalstage.

YARP was developed to remedy this ongo-ing situation in humanoid robotic research, itsmain objective being to allow collaboration be-tween working groups. It is essentially modu-lar, which facilitates adapting to ever changinghardware, and SO independent [10]. Most of itsprograming is done in C and C++, but there arebindings for Java, Matlab, C#, Python and Perlas well.

2.2 The iCub Simulator

A S previously explained, an iCub roboticunit, even being open-source in nature,

is not easy to construct and not cheap to ac-quire. Being an expensive tool of research, itis only natural trying to find alternative waysto perform some of the tasks meant to be runon iCub. Simulating the robot with realisticphysical interactions bring about a number ofadvantages to the researcher [11]:

1) Allows studying the embodied agent

without the need to building it in ad-vance.

2) The simulator can be used as a platformto quickly test new algorithms and checkfor major problems in its implementation.

3) Getting familiar with the platform andwith how to perform experiments latterto be tested on the physical platform.

The iCub simulation can be see in Figure 4,where the robot is seen behind a table with afew objects on it [11].

Fig. 4. iCub simulation with surrounding objects

The simulated robot was built trying toachieve an exact replication of the physicalrobot, and the environment has its parameters,such as gravity and friction, similar to realenvironment conditions.

Special care was given to the process ofchoosing the software tool to compose the finalsimulator. Since one of the main objectives wasto keep it open-source and easily available toany researcher looking forward to perform ex-periments on it, the simulation was composedby the following free platforms:

1) ODE Physics Engine2) OpenGL Rendering Engine3) YARP protocolODE stands for ”Open Dynamics Engine”

[12] and it is used for simulating the rigidbodies forming the robot and for the collisiondetection algorithms as well. Since the process-ing power required to perform the full simula-tion is quite big, the rendering of the whole

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scenes was performed in OpenGL, producinga smoother simulation. And at last, YARP, thesame protocol used on the physical robot, waschosen as an interface software between iCub’shardware parts. Commands are sent to therobot as YARP instructions and feedback fromiCub simulation’s sensors are acquired from themodel the same way [11].

3 WORKING WITH ICUB

THE RobotCub, being a recent project as itis, already has a number of articles related

to it in one way or another. Basically, thereare three types of works that can be found inthe literature at the moment: work related toRobotCub project, work on the developmentof iCub and its simulator and work using thedeveloped platform.

In the following sections, the nature of theseprojects will be briefly commented and someexamples of each will be given.

3.1 Works related to the RobotCub projectThese are the works that have a direct or indi-rect relation to the RobotCub project. The 6thframework (FP6) of the European Commissionsupported a number of works on the topic ofCognitive Systems in a broad way.

An example of such a work is a Survey ofArtificial Cognitive Systems, as can be seen in[13]. In this survey an overview of cognitivearchitectures and development of mental capa-bilities in computational agents is presented.

It compares the cognitive and the emergentparadigms of cognition. For a cognitive system,cognition is representational, based on the ma-nipulation of symbolic representations of thestate and behaviour of the external world. Forthe emergent approach on the other hand, cog-nition is mainly a self-organization processeswhich enables the system to become viable andeffective in its environment.

The paper then describes some cognitive ar-chitectures that work with both concepts. Likethe cognitive architecture SOAR, that works ina cognitive way, the Global Workspace concept,that is emergent in nature, and Cerebus, anexample of a hybrid architecture.

After describing and comparing these anda number of other architectures, the authorsconclude the paper pointing some of the mostimportant factors in the development of cogni-tive systems, such as the importance of embod-iment and a history of interactions [13]. Muchlike the Physical and Historical embodimentpreviously stated by Ziemke in [7] respectively.

3.2 Works on the development of the iCubplatformPerhaps the best article to learn more aboutthe iCub platform is the official paper [9]. Thisarticle has been rewritten and updated as theproject developed, and reports the RobotCubproject and development of the iCub humanoidrobot. Most of its content has already beendescribed in Section 2.

Another example of work on the develop-ment of the iCub can be seen in [14]. Thepaper describes the development of an anthro-pomorphic hand for the iCub. As previouslyexplained, manipulation plays an importantrole in the development of a cognitive system.And that is the reason why so many degreesof freedom were dedicated to the upper part ofthe robot and, in particular, to its hands. Thepaper describes how the selection of the de-grees of freedom was done so optimal graspingand manipulation could be performed. It is an”ongoing work” report, much like many of thearticles on the development of the iCub robotprior to 2007.

3.3 Works using the iCub platformThe most recent works related to the RobotCubproject are those using the iCub as a platformfor testing and evaluating new algorithms androbotic interactions.

These works are the most interesting ones tothose who would like to investigate embodiedcognition and all its related subjects such ascognitive architectures, behaviour and actionselection, humanoid control systems, embed-ded computational vision and so on and soforth.

An example of a highly important behavioura humanoid robot must be capable of per-forming is the grasping behaviour. In [15] for

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instance, the authors describe a technique forpreparing the robot to perform a grasping be-haviour. The objective is to estimate the 3Dposition of both the object to be held and therobot’s hand in space.

The processes consists of two phases:1) Positioning the hand near the object in a

proper configuration2) Applying a precise hand-to-target posi-

tioning of the handBoth the hand and the object are approxi-

mated as ellipsoids and the idea is that moreprecise movements are learned by experience.

The first phase comprises of wide move-ments based on the knowledge of wherethe object is and of the robot’s arm dynam-ics/kinematics. As soon as the hand gets nearthe object to be held, and both are in thevisual field of the stereo cameras, the secondphase starts. The second phase makes use ofthe CAMSHIFT 1 algorithm, a method basedon colour histograms. Due to the method’sdependence on colour, it is assumed that theobjects have sufficiently distinct colours for thealgorithm to work.

The results show that the method was ableto identify the two objects in question, handand object to be grasped, as correctly orientedellipsoids. Further work was proposed on im-proving pose estimation and implementing itin actual servoing and grasping experiments.

4 CONCLUSION AND FUTURE WORK

MOST of the work destined to be im-plemented in the physical iCub can be

initially developed on its simulated version.Being a physically realistic simulation of thereal robot and its surrounding environment, itcan be used to implement vision algorithms,such as the example given in Section 3.3, loco-motion control as in [16] or [17] and many otherbehaviours related to humanoid robotics.

Being a completely open-source platform,both hardware and software alike, the iCubpresents itself as a unique opportunity to fur-ther our knowledge on humanoid robotics and

1. please check reference [15] for further information on howthey have applied it

on human level cognition in a broader sense.With a growing community of researchers, andthanks to its modular architecture, it will be-come easier to develop on the platform andalso to cooperate with other researches andlaboratories.

Future work should encompass the conti-nuity of reviewing recent works on the plat-form, learn more about its structure and im-plement some fundamental behaviours, such asgrasping or following objects. In a followingmoment, a general control system for thosebehaviours shall be implemented, such as be-haviour networks or cognitive architectures.The intention would be not only to controlthe robot in a more holistic manner, but alsoto investigate some particular characteristics ofthe chosen control system and its implications.

ACKNOWLEDGMENTS

I would like to thank Dr. Professor RicardoGudwin and Andre L. O. Paraense for all thehelp regarding this project. I would also like tothank the Department of Computer Engineer-ing and Industrial Automation for the oppor-tunity to develop this work and CAPES for thefinancial support.

REFERENCES

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