In this article we propose a dynamic role exchange algorithm
for mobile robots. The heuristics used to alternate among the diﬀerent
roles is based on utility functions. We have utilize the Sony Aibo ERS-7
for testing our design and implementation. The RoboCup 4-legged competition environment has been chosen for proving our wor

Agüero, Carlos

Cañas, José María

Gómez Gómez, Víctor Manuel

Matellán Olivera, Vicente

English

Leon University (Spain)

SWITCH! Dynamic roles exchange amongcooperative robots ?Carlos E. Agüero, Vicente Matellán, José M. Can̂as, and Vı́ctor M. GómezUniversidad Rey Juan CarlosTulipán s/n, 28933, Móstoles (Madrid) - Spain{caguero,vmo,jmplaza,vmanuel}@gsyc.escet.urjc.es ,WWW home page: http://www.robotica-urjc.esAbstract. In this article we propose a dynamic role exchange algorithmfor mobile robots. The heuristics used to alternate among the differentroles is based on utility functions. We have utilize the Sony Aibo ERS-7for testing our design and implementation. The RoboCup 4-legged com-petition environment has been chosen for proving our work.1 INTRODUCTIONRoboCup is a very challenging and motivating robotic competition where undera simple soccer match, are hidden lots of research in several areas.In this paper we will focus on the 4-legged league [1]. Teams in this league aremade by four Aibo robots [2]. In this competition, communication among robotsis allowed (since 2002 edition held in Fukuoka, Japan). Cooperative behaviorscan benefit from communications in many ways: Improving accuracy to locateobjects by adding a global shared model [3], to allocate dynamically player roles[4].Dynamic multi-robot coordination had already been explored by other teams.Early work on cooperation and coordinated positioning in RoboCup was pro-posed in [5]. Cooperation among heterogeneous robots has been explored in [6].In [7] the ball position is determined by a probabilistic integration of all ballperceptions coming from the players. [8] suggested a potential field approachfor managing robots constructed with shared information. Newcastle universityteam [9], finalist in Osaka 2005, shares ball location helping robots to find theball quickly.In this paper we present our work in this area focusing on task allocation.Dynamic task allocation allows a team to divide its main objective in a couple ofsub-objectives more specialized and adapted to the location of each of the team-mates and the strategy of the team. Section 2, 3 and 4 details our contributionto role allocation problem and strategy decisions for roles in RoboCup. Section5 analyzes experiments and results we have got. Finally, section 6 summarizesour conclusions using coordination in robot teams and using our algorithms.? This research has been partially sponsored by grants DPI2004-07993-C03-01,DPI2004-07993-C03-02 and S-0505/DPI/0176 corresponding to Ditpa and Robocity2030 projects respectively2 ROLES SPECIFICATIONSeveral teams [10], [9] attending RoboCup events in the last years have used aset of roles assigned to each robot instead of using a single role for all players ofthe team. The use of a collection of roles allows a team to organize more easilyall responsibilities involved in the task to resolve.The roles can be assigned to each robot in an statical or in a dynamical way.Dynamic role allocation benefits, from example, from opportunistic situationslike fast ball changes along the field, penalized players1, or failures in some robot.We have considered four main roles in the RoboCup domain: Goal-keeper,Striker, Defender, and Supporter. Goal-keeper is the only role assigned statically.The main reason to have a single player to the Goal-keeper role is that the rulesdo not allow that players enter in its own goal area (like in the hand ball). Therest of roles can be exchanged among robots according to game conditions.Next, we are going to describe the objectives of each role and the advantageswe have obtained using dynamic role allocation:– Goal-keeper: Its goal is to protect its own goal from shots by the otherteam players. Also, it should rest in its own area.– Striker: It tries to get the ball and to carry it, or to kick it, towards thenet. When the other team have got the ball, it tries to recover it actively(going after the ball).None of the other roles are devoted to get the ball. This approach has oneimplicit advantage: It avoids pushing among players of our team, that isexplicitly penalized in the rules. If a team does not have a ball bookingmechanism [11] or similar, all robots will finish bumping into each other,and its players will be penalized.– Defender: Its goal is to intercept the ball if an opponent kicks it to its net.Furthermore, it should stand in the way of the opponent and should try tohide the net preventing the opponent to kick the ball.Another implicit consequence of the Defender role is that one robot of theteam always remains in a position near its own net. This fact is very usefultaking into account that the ball quickly moves from side to side. We havealways one robot covering its defending half of the field.– Supporter: The function of this role is to assist the striker in its path, andto cover the maximum amount of field in case the ball will be kicked in thewrong way.The main contributions of this role are to recover the ball if the kicks madeby the striker do not go in the good direction, and also to maintain a goodposition for future passing kicks.3 UTILITY AND HEURISTIC FUNCTIONSIn this section we are going to introduce some concepts needed to explain howthe roles are dynamically assigned. Our role allocation algorithm will be based1 Penalized players are removed from the field for 30”in heuristic functions. Those functions evaluates some parameters like the balldistance, localization, etc. and obtains a value for each role. We will call thisvalue utility. Utilities will be calculated periodically and roles will be assignedto robots in a priorized way according to the values obtained.A general definition for utility is “value to estimate the cost of executing anaction”. In our approach, utility is employed to evaluate the degree of adaptationof one role to one robot in a particular game conditions.In our proposal utilities will be individually computed by each robot as theweighted sum of several factors: Distances to ball, nets, etc. In order to describethose factors, we will use the formalism described in [4]:– Let I1, ..., In be the set of n robots.– Let J1, ..., Jn be the set of n priorized roles and w1, ..., wn their relativeweights.– Let Uij the nonnegative utility of robot Ii for role Jj , 1 ≤ i, j ≤ n.1. Update Utilities2. Look for robot with larger utility for Striker role3. Look for robot with larger utility for Defender role4. Look for robot with larger utility for Supporter roleUpdate Utilities step computes a matrix with all combinations among robotsand roles according to the heuristic described below. The next steps selects themore suitable robot for the Striker, Defender and Supporter roles in this order.The heuristic functions used to allocate the roles developed are the following:– Ui,Striker = DIi,Ball + (θIi−Net − θBall−Net) + REC– Ui,Defender = DIi,Own net + REC– Ui,Supporter = DIi,Opp net + RECDIi,Ball, DIi,Own net and DIi,Opp net are the distances to the ball, own net,and opponent net. θIi−Net is the difference in orientation between the localorientation of the robot and the orientation needed for focusing the net. θBall−Netis the angle between the ball and the opponent net. REC (Role Exchange Cost)is also added to prevent excessive roles exchanges if only small changes havehappened in the environment. This factor provides some kind of hysteresis tothe system.Next are the equations to select the appropriate robot for each role. In thispaper we suppose that the order in roles assignment is Striker,Defender andSupporter.1. Utilitystriker = min(Ui,striker) , ∀i ∈ (1..n)2. Utilitydefender = min(Ui,defender) , ∀i ∈ (1..n) ∧ i 6= Robotstriker3. Utilitysupporter = min(Ui,supporter) , ∀i ∈ (1..n) ∧ i 6= Robotstriker, RobotdefenderEvery robot updates its utilities periodically, and broadcasts this informationto its teammates. We will refer to this information as coordination information.The information sent is its own location, and an estimation of its distance to theball. Coordination information is sent at 5Hz.When one robot receives coordination information it updates data associatedto the corresponding robot in its global model. This global model stores positionof the teammates and, combined with the position of the ball is used to calculateutilities functions.4 ROBOT POSITIONINGIn the previous section we have explained our mechanism for selecting rolesaccording to the game situations. Other interesting issue is what should a robotdo if it is running Defender or Supporter Role (Striker always goes for the ball).In our proposal, Defender and Supporter go to a specific position. In this sectionwe describe how the players calculate their “ideal position” according to the rolesthey have been assigned.Fig. 1. Detailed points of interest calculating ideal posititions for roles4.1 Defender positioningDefender should stay in a position near its own net in order to defend its goal.We have developed an approach that places Defender between the ball and themiddle of its own net. If an opponent hits the ball and the ball travels in the netdirection, the defender must be in its trajectory.angle = arctan(ownNety − bally, ownNetx − ballx)Ax = −cos(angle) ∗ areaCornerAy =FieldLength2− sin(angle) ∗ areaCornerball2aproxArea = distance(A, Ball)Illegal defense must be taken into account when the team is defending. Thispenalty is applied when a defending robot goes into its own area. In order toprevent our Defender from entering in its own area, we have approximated thearea penalty to a semi-circumference.The Defender ideal position will be the center of the segment delimited bythe ball and point A (see figure 1 left). This position (DEFx,DEFy) is calculatedusing the next equations:DEFx = −cos(ang) ∗ (areaCorn +ball2Area2)DEFy =FldLgth2− sin(ang) ∗ (areaCorn + ball2Area2)4.2 Supporter positioningIdeal position is the middle point of the quadrant delimited by the ball and thefairest corner of the opponent side (as shown in figure 1 right) where we can seethis quadrant). This can be calculated as:Dlateral = Max(dist(ballx, latleft), dist(ballx, latright))DgoalLine =FieldLength2+ ballySUPPORTx = ballx ±Dlateral2SUPPORTy = bally −DgoalLine2This position guarantees that Supporter will never stand in the way of strikerand the opponent net. Its goal is to support the striker and, in case a kick doesnot go in the right direction, to reduce the time to go for the ball.5 EXPERIMENTSTeamChaos [12] code is composed by the source code of the program that runsinto the robots and a suite of tools. One of this tools is the team simulator. Wehave tested what are the differences if our team uses Switch coordination or not.5.1 Playing with Switch coordination in simulatorUsing dynamic role allocation, experiments show that the game is more dynamic.The main reason is that we give the biggest priority to take the ball. In simulatorwe have seen that always the better placed robot wants to go for the ball. If wedrag the ball to different positions on the field, role reallocation acts quickly androbots change their positions. In consequence, the ball is take it more quicklythan experiments without Switch coordination.In order to test the real advantages of the dynamic role allocation, we havemade six matches in our simulator, three of them with coordination and theothers without switch. During the simulation there are not any opponents andeach match has 10 minutes. Every time a player scores, the ball is taken to themiddle of the field. In table 1 we can see the results of the simulations.Match # Goles with Switch Goles w/out Switch1st 3 22nd 4 33th 4 3Table 1. Results of matches without opponentsNon cooperative team has a clear problem: All players go to the ball. Thereare not any advantage playing with one player or playing with three players. Inthis case, more players involve more obstructs between them.Coordinated team offers a very more ordered play with the three attackerplayers spreaded on the field. With less robots standing in the way of others,there are more time to carry the ball inside the net and if the pushing rule wouldbe applied they would have been removed from the field.Although there is not a very large improvement in goals, the overall behaviorof the team is much more organized. When the code of our Striker will be moretuned, we hope the results with and without coordination will drastically emerge.5.2 Playing with Switch coordination with real robotsWe have also tested Switch coordination in real robots. We have used a team ofthree Sony AIBO ERS-7 using the framework of the TeamChaos RoboCup team[12]. First, we have tested the operation of the assigning protocol for the strikerrole.We have hold down the three robots in boxes. We want to show that only therobot with best utility and only one goes for the ball. If we put the ball in frontof one of the robots, only the closest robot goes for it. If we move the ball andput it close to another player, this one takes the role of striker and it moves itslegs for catching the ball. Note that for this experiment, defender and supporterroles are running a still behavior. You can see a movie for this experiment inhttp://gsyc.es/c̃aguero/Switch-Pre.avi.6 CONCLUSIONSWe have developed a basic coordination mechanism among members of a multi-robot team. Localization and local ball estimation are the elements shared. Com-bining periodically the information received with local information, each robotupdates a global model of the environment. Using coordination we have alsogot a very good way to identify the rest of the team members. We can not dopreviously because all teammates look alike.Using the global map, an strategy layer uses the shared information to allo-cate roles. We have used a simulator to choose several heuristic functions andfactors. We have observed the behavior in opportunistic situations dragging theball and releasing it in other point. Robots quickly exchanges their roles accord-ing to the new scenario. However, when doing little changes in the environment,robots are able to cushion them maintaining their roles and improving the dy-namism of the system.Finally, ideal positions for each role are one option chosen by our team thathas worked very well in our tests. Movement of the Defender robot is very smoothwithout big jumps between positions, preventing this critical player from movingconstantly.Supporter robot is less critical so it moves more than Defender coveringthe attacking field. Tests have shown that if a kick fails, Supporter goes forthe ball quicker than previously implementations without coordination. Beforeusing cooperation, the three players were closer all together and now they areexpanded in a more intelligent way around the field.References1. Legged Robocup Federation: Robocup Four-Legged League.http://www.tzi.de/4legged/bin/view/Website/WebHome (2006)2. Sony: Sony Global - AIBO Global Link. http://www.sony.net/Products/aibo/(2006)3. Roth, M., Vail, D., Veloso, M.: A world model for multi-robot teams with commu-nication. In: IROS-2003. (2003)4. Gerkey, B., Mataric, M.: On role allocation in robocup. In: RoboCup 2003: RobotSoccer World Cup VII, 2004, Springer-Verlag (2004) 43–535. Stone, P., Veloso, M., Riley, P.: The CMUnited-98 champion simulator team.Lecture Notes in Computer Science 1604 (1999) 61–756. Castelpietra, C., Iocchi, L., Nardi, D., Piaggio, M., Scalzo, A., Sgorbissa, A.: Com-munication and coordination among heterogeneous mid-size players: ART99. Lec-ture Notes in Computer Science 2019 (2001) 86–957. Weigel, T., Gutmann, J.S., Dietl, M., Kleiner, A., Nebel, B.: CS Freiburg: Coordi-nating Robots for Successful Soccer Playing. IEEE Transactions on Robotics andAutomation 18(5) (2002) 685–6998. Vail, D., Veloso, M.: Dynamic multi-robot coordination. In: Multi-Robot Systems.Kluwer (2003)9. Laboratory, N.R.: The NUbot 2005 Team Report.www.robots.newcastle.edu.au (2005)10. GermanTeam: http://www.germanteam.org/ (Team report, 2005)11. Agüero, C.E., Mart́ın, F., Mart́ınez, H., Matellán, V.: Communications and basiccoordination of robots in teamchaos. In: Actas VII Workshop de Agentes F́ısicos.(2006) 3–912. TeamChaos: Team Chaos roboCup Team. http://www.teamchaos.es (2006)

SWITCH! Dynamic roles exchange among cooperative robots

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SWITCH! Dynamic roles exchange among cooperative robots

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