Integrating Omnidirectional Perception and Drivein the Body of a Soccer Robot

Enrico Pagello*† Emanuele Menegatti* Tommaso Guseo Francesco FavaroEnrico Ros

Intelligent Autonomous Systems LaboratoryDepartment of Information Engineering

The University of Padua, Italy†also withInstitute of Biomedical Engineering

of the National Research Council (ISIB-CNR) Padua , ItalyE-mail:*{epv,emg}@dei.unipd.it

ABSTRACT

The aim of this paper is to provide an overview of the robotsdesigned at the University of Padua. Most of the robot weredesigned to work in the Middle-Size League of the RoboCupCompetitions. In this paper we detail the insights we haddesigning so many robots and the new way of looking at om-nidirectional vision we developed. Omnidirectional vision isnot only a powerful sensor, but linked to a careful body de-sign and an omnidirectional drive can realise a much morereactive machine, able to sense and act in real time, with-out any time delay due to limits of the sensory horizon or toconstraints of the motion drive.

1 Introduction

Robotics researchers believe that Embodiment and Situated-ness are two basic issues for any intelligent autonomous sys-tem. Often, papers from Artificial Intelligence communityconcentrate on the design of the reasoning level. They as-sume that someone has built a physical body for their agent,that they make able to localise itself and to act autonomouslyin its environment through sophisticated AI instruments. Wealso have mostly concentrated our attention on the prob-lem of balancing reactivity and deliberation in multi-robotsystems[2] and on designing an architecture for emergentbehaviours[13].But, we believe that shaping robots is an important scientificactivity, especially when the design of bodies, and a correctdisplacement of sensors, are a key for the success of its intel-ligent components. Without experimenting the real problemsgiven by a locomotion system, it is difficult to design the soft-ware that realises both the basic and the complex behaviourfor a team of cooperating robots. Thus, in this paper, we wantto tell the ”problems behind”. We illustrate in particular thesynergy between an omnidirectional locomotion and an om-nidirectional sensor that we introduced in our team of robotsfor RoboCup, as a key step for allowing them to cooperateintelligently[8].We dedicate this gallery of robots to our great mentor andfriend, Marco Somalvico, who always recommended us to

develop an experimental environment for our research activ-ities. The Middle-Size League among the different RoboCupleagues is the one that knows the biggest turn over of tech-nologies. The constraint that the robots must carry all sen-sors on board and the increasing speed of the games pose achallenge to the researchers in a careful design of the robot.The perceptual systems, the actuators, the computational re-sources, the power supplies, the internal weights of the robotshould be carefully considered and integrated to obtain awinning design. The seek for better performances is whatpush researchers to improve their robots and sometimes tocompletely change their bodies, their sensors and their actu-ators.The University of Padua started to compete in RoboCup ’98with slightly modified Pioneer1 platforms fitted with stan-dard perspective cameras. When in the following years westarted to design our own sensors (especially omnidirectionalvision systems with a custom profile [7][9]), we realised thenew possibilities offered by a custom design of the robot’sbody, shaped on the sensors it will carry and on the rolethe robot will assume. The design of omnidirectional vi-sion systems gave us a deep understanding of the links andthe connections between the design of a sensory system andthe design of the appropriate body and the appropriate drivefor the robot. Since the beginning of the RoboCup compe-titions, several researcher caught the insight that omnidirec-tional sensing and omnidirectional drive are two technolo-gies that offer several advantages in the RoboCup domain,but few of them tried to fuse the two technologies in a singleplatform. We think that using vision sensors with a narrowfield of view can be appropriate for a non-holonomic vehi-cle which has the limit of a minimum radius of curvature. Infact, the obstacle becomes dangerous after they entered thefield of view (at least static obstacles). If one want to usean omnidirectional vision sensor in a non-holonomic vehi-cle, the potentials of the sensor are limited to spot objects allaround the robot. The capacity of locate obstacles all aroundthe robot is mandatory for a holonomic vehicle; as a matter offact an omnidirectional sensor is required for an holonomic,so it can spot obstacles in every directions it chooses to move,even backward. The synergy of the omnidirectional sensing

and the omnidirectional moving extends beyond the detec-tion of obstacles or meaningful events, it can be exploited tocreate a more reactive system where the response to a mo-tor command is not governed by complex motion laws, butsimple compositions of rotations and translations, that can beobtained as simple sums of vectors.

2 Robot Body Design

In this Section we will describe the evolution of the platformsused for robots fitted with omnidirectional vision developedat the University of Padua. We will show that omnidirec-tional vision sensors enforced a reshape of the robot’s bodyand a rethinking of the classical car-like robot’s motion. Wewill describe all the robots fitted with omnidirectional visionwe designed: from our very first robot Lisa, where the chas-sis was not optimised for the omnidirectional vision sensor,to our last robot Nelson that was designed thinking of mount-ing two vision systems (a perspective and an omnidirectionalvision system) and making it suitable for outdoor applica-tions.

2.1 Lisa

The goalkeeper, called Lisa, was the first robot of our teamwhere we mounted an omnidirectional vision sensor. Itsbody is a box of37cm × 27cm × 33cm. The weights in-side the chassis of the robot are disposed in order to have thecentre of gravity (COG) of the body on the crossing of thebox diagonals. The two driving wheels are positioned trans-versely to the body, to allow lateral motion that is suitablefor a goalkeeper. The axis of the wheels passes through theCOG (centre of gravity) of the robot’s body, Fig. 1 (Bot-tom View). This permits to the robot to turn exactly on thespot and then to have a a quasi-holonomic move. In fact, therobot can move in any direction after a suitable turn on thespot. The body was designed before the decision of mount-ing an omnidirectional vision sensor, so it suffers of somelimitations, but the position of the wheels gave us the first in-sight that an holonomic move was necessary when using anomnidirectional sensor.The limitations dues to the box-like body are mainly aboutocclusions in the acquired images. In fact, the upper sideof the box occludes an area around the robot. This problemcan be partially overcome by a smart design of the profileof the mirror, as we detailed in [7]. In this paper, we gavedetails on the design of a multi-part mirror with a customprofile. These limitations corroborated the insight that a re-shape of the robot was needed when using omnidirectionalvision sensors.

2.2 Argo

Argo is the new goalkeeper robot of the Artisti VenetiRoboCup Team. Argo is an evolution of the old goalkeeperLisa. The starting point in the design of Argo was to preserveand enhance the characteristics that proved to be the point ofstrength of Lisa and to overcome its limitations. As we said

Figure 1: (Top) Side View of our robot Lisa. (Bottom) Bot-tom view of Lisa.

Figure 2: (Top) Side View of our robot Argo. (Bottom) Bot-tom view of Argo.

in Section 2.1, the main advantage of Lisa with respect toother goalkeeper robots was its quasi-holonomic driving sys-tem. This resulted in the possibility to move on a semi-circlefor a better shielding of the goal mouth [7]. This idea, thatproved to be effective on the field of play, was further in-vestigated and we discovered that instead of a semicircle theline to obtain the best shielding is an arc of circumference.The position of the motors of Argo was decided in order toobtain a preferential motion on this arc while enhancing theholonomic motion of the robot, see Fig. 2. The main disad-vantage of Lisa was its chassis. As we said the Lisa’s chassiswas not optimised for omnidirectional vision, generating un-necessary occlusions. Moreover, the chassis was too heavyfor the reactivity required to a goalkeeper. The chassis ofArgo was designed to work with an omnidirectional visionsystem. The shape of the chassis presents an approximativecircular symmetry to avoid occlusions and a frontal concav-ity to better retain the ball when contrasting an opponent,see Fig. 2. Inspired by Ducati motorbikes, Argo’s designersrealised a completely tubular frame. At the time of writingArgo is under construction and it will play its first match atthe RoboCup2003 in Padua.

2.3 Leonardo

The project of the platform called Leonardo started at the endof 2002 and it was intended to improve the omnidirectionalplatform Golem built by the Golem Team [4]. We carefullystudied the Golem platform that is disposable in two exem-plar at our laboratory. We discovered that the motion of thisplatform with three driving wheels is no completely holo-nomic. In fact, the low limit of the maximum translationalspeed of the Golem platform makes impossible to achieve acomplete holonomic motion. The Golem platform is holo-nomic only in a limited range of speeds of the three motors.The platform Leonardo was studied to have a nearly symmet-ric shape and a fully holonomic motion, and to integrate thestructure with an omnidirectional vision system. The plat-form has four omni-wheels placed in a cross-like positions.Its body was made out of a square with a 48 cm side, whosecorner were rounded for better escaping from cluttered situa-tions. The concavity in the chassis is designed to better con-trol the ball. One of the problems of the Golem platform wasthat having the wheels external to the robot frame, they getstuck when manoeuvring in clattered areas with other robots.To avoid these situations, the Leonardo’s chassis is designedto contain the four wheels. Another difference of Leonardowith respect to its ancestor, i.e. the Golem platform, is itsheight. Leonardo height is of 70 cm with respect to the 55cm of the Golem. This choice is motivated by the increaseddimensions of the field of play in the Middle-Size RoboCupcompetitions, that in RoboCup2003 will be of10 × 7m. Inorder to conveniently image such a large field the omnidirec-tional sensor should be placed well above the ground.To avoid vibrations to the structure supporting the vision sys-tem, the upper structure was isolated from the vibrations gen-erated by the motors with two order of shock absorber.

Figure 3: (Top) Side View of our robot Leonardo. (Bottom)Bottom view of Leonardo.

2.4 Nelson

The starting point in the design of Nelson was the consid-eration that even a fully holonomic platform, like Leonardo,in practise has a preferential direction, so why not to exploitthis preferential direction to build a quasi-holonomic robotfitted with omnidirectional vision able to move also on slickor rough terrains? So we renounced to the fully holonomicdesign of Leonardo to overcome its limitations, recoveringthe drive design of Lisa: two driving wheels mounted on thesides of the chassis with their axes passing through the COG(centre of gravity) of the chassis, Fig. 4 (Bottom View).This permits to the robot to turn exactly on the spot with anull minimal radius of curvature and then to have a a quasi-holonomic move, because the robot can move in any direc-tion after a suitable turn on the spot or combining rotationand translation. This design gives a great agility and speed inapproaching the ball and to escape from cluttered situationwithout any complex manoeuvre. Again, we renounced tothe fully holonomic motion permitted by the omni-wheels, tomount rubber wheels with a high friction coefficient suitablefor moving on every surface from slick to rough or non com-pletely planar. This would be useful for outdoor application,like a futureoutdoor soccer league. The two side wheels per-mits to have more power in the preferred direction, the frontdirection, to accelerate and to resist in the contrasts with theopponents.The chassis of Nelson is the result of a careful design of thebody in order to avoid that parts of the body could occlude

Figure 4: (Top) Side View of our robot Nelson. (Bottom)Bottom view of Nelson.

areas the ground around the robot and to maintain a heightstructural strength. As you can see from Fig. 4 (Top View),the chassis does not present a circular symmetry, but it avoidsunnecessary parts that would have generate occlusions, likethe corners of the box that composes the chassis. The supportfor the catadioptric vision system presents a pyramidal shape,again to avoid occlusions, Fig. 4 (Side View).

3 Considerations on a careful body design

In the experience we made with car-like vehicles, with quasi-holonomic vehicles, and with holonomic vehicles we can ex-tract the following considerations on the “pros and cons” ofomnidirectional drive systems:The advantages of holonomic:

• the robot can move directly to the target;• simultaneous rotations and translations of the vehicle

are possible;• the stability of the platform is assured by the fact that

the robots has three points of contact with the floor;• the robot can escape from cluttered environment with-

out complex manoeuvres;

The disadvantages of holonomic:

• the drive system requires a careful and skillful mechan-ical design;

• an additional motor is required with respect to the twodriving wheels vehicles;

• existing holonomic systems are not suitable for outdoorapplications;

• the off-of-the-shelves omni-wheels do not presentenough friction and so the platform is often slipping;

• the information from the encoder is not reliable for anabsolute localisation (not only because the wheels slipbut also because the wheel revolution is not in the direc-tion of the actual robot’s motion);

• if the wheels slip, for the robot it is difficult to realise itis stuck somewhere;

From the experience we made designing omnidirectionalvision system, we extracted the following guide lines thatshould be followed to design a chassis appropriate for an om-nidirectional vision system:

• the robot’s body should have a pyramidal profile;• the robot’s base should have circular symmetry;• the catadioptric system should be placed at the geomet-

rical centre of the robot’s body;• the height of the support of the catadioptric sensor

should be carefully considered;

The last advice stands especially for mirror with custom pro-file, where the height of the catadioptric system is one of thevariables of the mirror’s design, so once it has been fixed atthe design stage, it cannot be changed later. Omnidirectionalmirrors with an isometric design, like the ones presented in[6] or [5] are really sensible to this problems with the resultthat the image reflected is no longer isometric, while multi-part mirrors like the ones we designed in [10] can tolerate abigger amount of displacement from the position fixed at thedesign stage and they need just a re-calibration for the exactcalculation of the distances.As we said, the best would be to design the robot’s chas-sis together with the omnidirectional vision sensor, adaptingthe body shape to the catadioptric sensor’s needs (and vice-versa), like we did for Nelson, but several times we have tomount an omnidirectional vision system on an existing chas-sis. This was the case for our robots Lisa and, lately, for arobot of the GMD team. In fact, the German GMD Teamcommissioned from us an omnidirectional vision system fortheir new goalkeeper. In this case, the biggest problem is theocclusions’ problem: parts of the body occlude the view ofinteresting areas of the field of play.

4 Adding Intelligence to the Bodies

Having the possibility to experiment with the real robotswe described, we were able to implement innovative soft-ware systems. We have developed anenhanced reactivityapproachtrying to combine the reactive approach and thedeliberative approach[13]. At the reactive level, our robotsare programmed using a behaviour-based approach. Threedifferent robot roles [12] has been introduced by specifyinga set of behaviours [3]. The three roles are:attacker, mid-fielder anddefender.A measure of quality Q, able to triggers the proper role, wasintroduced time ago, at IAS Lab. of Padua Univ., for evalu-ating how much work must be done by a robot to get the ball

in the best position to score [3]. A generalisation of the func-tion Q has been introduced in [1] as a set of utility functionsable to give through an explicit communication some utilityvalues that indicate the usefulness of each role. Our robotsare able to show a cooperative action, like aball exchange,by coordinating their basic behaviours through the dynamicassignment of the above three roles realised by a set of be-haviours that exploit some smart collision-free motion strate-gies, based on the computation of a vector field [13]. Robotsswap frequently their roles, and they succeed toexchange theball, as an emergent behaviour during past games.Each basic behaviour is realised as a thread in ADE (ArtistiVeneti’s Development Environment), a multi-thread dis-tributed real-time Environment working under Linux OS.ADE has been inspired by the coordination environment usedby ART [12].ADE allows to create a set of processes structured as threads.Each thread can communicate, through message passing,with other threads of the same process and also with otherprocesses running on other processors. Each thread can al-low or deny itself to other threads of lower priority.At the moment, we are working on realising a DistributedVision System (DVS) able to fuse the information gatheredby the single agents. The DVS we develop can take as inputany measurement described as a Gaussian probability distri-bution. So far, it takes as inputs only measurements madewith the omnidirectional vision systems of the robots, but weare working on integrating data coming from arrays of mi-crophone sensors [11].

5 Conclusions and Acknowledgements

In this paper, we reported the experience we matured in thedesign of different kinds of quasi-holonomic and holonomicplatforms for robots fitted with omnidirectional vision. Wereported the evolution of the robot’s platforms used at the In-telligent Autonomous System Laboratory for the RoboCupcompetition, analysing the advantages and disadvantages ofquasi-holonomic and holonomic drive systems. In addition,we gave some practical hints on the design of a robot’s plat-form for a robot fitted with omnidirectional vision and howomnidirectional vision can be fully utilised, exploiting it be-yond the mere observation of the surroundings of the robot.Most of these ideas came out during the design we did ofa multi-part mirror for the German RoboCup Team, calledGMD. In the last section we shed some light on the softwaresystems developed thanks to the practical experimentationswith the robot presented in this paper.Artisti Venetihas been supported by a Special Research Project on”Cooperative Multi-robot Systems” granted by The University ofPadua. Additional founding were given by MURST, by the InstituteISIB of CNR, by ENEA (Parallel Computing Project). We acknowl-edge all the students of the Artisti Veneti Team. We acknowledgefor their cooperation the members of the Golem Team that designedand built the Golem platform. We thank Elpro Innotek that lentus one of our two Golem platforms. We thank Tecnogamma s.p.a,Padova Ricerche s.p.a., Garbuio s.p.a., and PadovaFiere s.p.a fortheir support.

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