Flexible Coordination of Multi-Robot Teams: Applications

Luís Paulo Reis

Flexible Coordination of Multi-Robot

Teams: Applications in Robotic Soccer

Flexible Coordination of Multi-Robot Teams: Applications in Robotic Soccer, Luis Paulo Reis, LARS/SBR 2012, Fortaleza, Brazil, 1

Luís Paulo [email protected]

http://www3.dsi.uminho.pt/lpreis

Member of the Directive Board of LIACC – Artificial Intelligence and Computer Science

Lab. Of the University of Porto, Portugal

Associate Professor at School of Engineering, University of Minho, Portugal

Presentation Outline

• Artificial Intelligence, Robotics and Simulation

• RoboCup and Our Teams– RoboCup Challenges and Leagues– Portuguese Teams: FCPortugal, 5DPO, Cambada and PT Team

• Flexible Strategy for Robotic Teams– Strategy and Formations/SBSP

AI and Robotics| RoboCup and Our Teams| Flexible Strategy for Robotic Teams| Applications and Projects| Conclusions


– Strategy and Formations/SBSP– DPRE - Dynamic Positioning and Role Exchange– SetPlays and Graphical Setplay Definition– Generic Optimization of Skills/Decisions

• Applications and Projects at Portugal– Agent Based Simulation: EcoSimNet– Educational/Assistive Robotics: Intellwheels, Robot Dancing– Strategic Reasoning: Poker Agents– Real Sports: Soccer, Indoor Sports (Handball)

• Conclusions and Future Work

Artificial Intelligence

• Intelligence

– “Capacity to solve new problems through the use of knowledge”

• Artificial Intelligence



• Artificial Intelligence

– “Science concerned with building intelligent machines, that is, machines that perform tasks that when performed by humans require intelligence”

Autonomous Agents and Multi-Agent Systems

• Agent Traditional Definition:

“Computational System, situated in a given environment, that has the ability to perceive that environment using sensors and act, in an autonomous

way, in that environment using its

?

agent

percepts

sensors

actions

effectors

environment

From Russel and Norvig, “AI: A Modern Approach”, 1995



way, in that environment using its actuators to fulfill a given function.”

• Multi-Agent System:

– Agents exhibit autonomous behavior

– Interact with other agents in the system

From Russel and Norvig, “AI: A Modern Approach”, 1995

Agents and Multi-Agent Systems• To build individual autonomous intelligent agents is important,

however:

– Agents don’t live alone… Necessary to work in group…

– Multi-Agent Applications…

Coordination : “to work in harmony in a group”– Dependencies in agent actions



– Dependencies in agent actions

– Need to respect global constraints

– No agent, individually has enough resources, information or capacity to execute the task or solve the problem

– Efficiency: Information exchange or tasks division

– Prevent anarchy and chaos: Partial vision, lack of authority, conflicts, agent’s interactions

Intelligent Robotics• Robotics

– Science and technology for projecting, building, programming and using Robots

– Study of Robotic Agents (with body)

– Increased Complexity:• Environments: Dynamic, Inaccessible, Continuous and Non



• Environments: Dynamic, Inaccessible, Continuous and Non Deterministic!

• Perception: Vision, Sensor Fusion

• Action: Robot Control (humanoids!)

• Robot Architecture (Physical / Control)

• Navigation in unknown environments

• Interaction with other robots/humans

• Multi-Robot Systems

Current State of Robotics• Used to Perform:

– Dangerous or difficult tasks to be performed directly by humans– Repetitive tasks that may be performed more efficiently (or cheap) than

when performed by humans

• Robots have moved from manufacturing, industrial applications to:– Domestic robots (Pets – AIBO, vacuum cleaners)

– Entertainment robots (social robots)



– Entertainment robots (social robots)

– Medical and personal service robots

– Military and surveillance robots

– Educational robots

– Intelligent buildings

– Intelligent vehicles (cars, submarines, airplanes)

– New industrial applications (mining, fishing, agriculture)

– Hazardous applications (space exploration, military apps, toxic cleanup, construction, underwater apps)

– Multi-Robot Applications and Human-Robot Teams!

Agent-Based Simulation• Simulation: Imitation of some real thing, state of affairs, or process, over

time, representing certain key characteristics or behaviours of the physical or abstract system

• Applications:

– Understand system functioning

– Performance optimization

– Testing and validation



– Testing and validation

– Decision making

– Training and education

• Applied to complex systems impossible to solve mathematically

• Traditional Simulation Drawbacks:

– Systems are getting more complex and difficult to model as a whole

– Higher level tools available

– Human behaviour is often neglected or over simplified

• Agent Based Modeling and Simulation:

– Entities represented by Agents with Autonomous Behaviour

Robotic Competitions• RoboCup – Robotic Soccer• Robotic Soccer FIRA • DARPA Grand-Challenge• Intelligent Ground Vehicle Competition • European Land Robot Trial • IEEE MicroMouse competition• AAAI Grand Challenges• First Competition (Lego-League)



• First Competition (Lego-League)• RoboGames (former RoboOlympics)• Manitoba Robot Games • LARC, SBR, OBR• Robotic Fight: BattleBots, RobotWars, RobotSumo• Underwater and aerial Robot Competitions• …• Some Portuguese Competitions:

– Portuguese Robotics Open (including autonomous driving)– Micro-Mouse/Ciber-Mouse– Firefighting Robots

Robotic Competitions - RoboGames

• Videos: RoboGames Videos



Robotic Competitions - RoboCup

• Videos: RoboCup Videos



Robotic Competitions - Portugal

• SPR Sociedade Portuguesa de Robótica

• Festival Nacional de Robótica (2001 – 2012)

– http://www.spr.ua.pt/fnr

– http://pt.wikipedia.org/wiki/Festival_Nacional_de_Rob%C3%B3tica

– http://robotica2011.ist.utl.pt

– http://www.robotica2012.org



• Festival Nacional de Robótica 2013 – Lisbon

– Robotic Soccer

– Autonomous Driving

– Freebots (Free Robots Competition: Scientific, Juri Demo, Public Demo)

– Robot@Factory

– RoboCup Junior

– Demonstrations

– International Conference on Autonomous Robot Systems and Competitions, April 2012, Lisbon, Portugal

Robotic Competitions• Benefits

– Research inspiration– Hard deadline for creating fully functional system– Common platform/problem for exchanging research ideas/solutions– Continually improving solutions– Excitement for students/researchers at all levels– Large number of teams/solutions created



– Large number of teams/solutions created– Encouragement for flexible software/hardware

• Dangers– Obsession with winning– Domain dependent/hacked solutions– Cost escalation– Difficulty in entering at competitive level– Restrictive rules– Invalid evaluation conclusions

based on Peter Stone, 2002

Research Question

How to Coordinate heterogeneous

Multi-Robot Teams executing flexible tasks



Multi-Robot Teams executing flexible tasks

in a dynamic, adversarial environment?

Presentation Outline• Artificial Intelligence and Robotics

• RoboCup and Our Teams

– RoboCup Challenges

– RoboCup Leagues: Simulation (2D, 3D, MR, Rescue), SSL, MSL and SPL

– Portuguese Teams: FCPortugal, 5DPO, Cambada and PT Team

• Flexible Strategy for Robotic Teams




• Application in other Projects at Portugal


RoboCup: Objectives

• Joint International Project:

– (Distributed) Artificial Intelligence

– Intelligent Robotics

• Soccer – Central Research Topic:

– Very complex collective game

– Huge amount of technologies involved:



– Huge amount of technologies involved:

• Autonomous Agents, Multi-Agent/Multi-Robot Systems, Cooperation, Communication, Strategic Reasoning, Robotics, Sensor Fusion, Real-Time Reasoning, Machine Learning, etc

Main Goal of the RoboCup Initiative:

“By 2050, develop a team of fully autonomous humanoid robots that “By 2050, develop a team of fully autonomous humanoid robots that

may win against the human world champion team in soccer!”may win against the human world champion team in soccer!”

RoboCup: Official Competitions

• 1997 – Nagoya (Japan)• 1998 – Paris (France)• 1999 – Stockholm (Sweden)• 2000 – Melbourne (Australia)• 2001 – Seattle (USA)• 2002 – Fukuoka (Japan)• 2003 – Padua (Italy)

• 2006 – Bremen (Germany)• 2007 – Atlanta (USA)• 2008 – Suzuhu (China)• 2009 – Graz (Austria)• 2010 – Singapore (Singapore)• 2011 – Istanbul (Turkey)• 2012 – Mexico City (Mexico)



• 2003 – Padua (Italy)• 2004 – Lisbon (Portugal)• 2005 – Osaka (Japan)

Local Championships: • German Open (European), Japanese Open, Australian Open, American Open,

Portuguese Open, Dutch Open Iranian Open, China Open, …

Participant/Awarded Countries:

• Germany, USA, Japan, Iran, China, Australia, Portugal,

Holland, Brazil, Singapore

• 2012 – Mexico City (Mexico)• 2013 – Eindhoven (Holland)• 2014 – João Pessoa (Brazil)

RoboCup: Global Perspective

• Soccer Leagues– Simulation: Sim2D, Sim3D (Humanoids), Coach, MR League

– Robots Small-Size

– Robots Middle-Size

– Standard Platform (Aibo; NAO)

– Humanoid Robots



– Humanoid Robots

• RoboCup Rescue– Simulation, Virtual, Robotic

• RoboCup Júnior

• RoboCup@Home

• RoboCup@Factory

• Virtual Robots

• 105*68m Virtual Field

• Agents controlled by different computers (or processes)

• Simulator sends perception and receives actions from agents

RoboCup Leagues: Simulation 2D



actions from agents

• Teams of 11 players plus a coach

• 2D Simulator– Client-Server System– Agents (player’s brains)

control a single player:

• UDP sockets/Linux– Server:

• Receives agent commands

• Simulates movement of objects • Sends perceptions to the agents

Server Architecture




• Sends perceptions to the agents– Two teams with 11 players + coach, try to score goals!

• Simulation Characteristics– Real-Time - Human– Distributed – 24 Processes– Inaccessible (hidden), Continuous and Dynamic World– Errors in: Perception, Movement and Action – Limited Resources and Communication – Multi-Objective, Cooperative and Adverse Environment

Server Architecture

• 1997: League Start -> Simple Play

• 1998: Simple Passing and Good Individual skills

• 2000: Formations and Soccer like Playing

Videos: Simulation 2D League




Videos: Simulation 2D League


• Third dimension adds complexity

• Complexities from real robots

• Realistic physics and Robot Model:

• Started with sphere in 2004

• Humanoids in 2007



• Humanoids in 2007

• NAO Robot Model: 2008

• Strong relation with SPL

• 6 vs 6 games -> 9 vs 9 -> 11 vs 11

• Heterogeneous Robots in 2012

• Very difficult to create competitive

skills by hand!

Humanoid Robot - Simspark

• Server (SimSpark) • Manages the simulation process

• Updates world state

• Enforces soccer rules - referee

• Forces the “laws of physics”:



• collisions, drag, gravity, ...

• Agent connections,

• Send sensor information (perceptors)

• Executes actions (effectors)

Simulation 3D – Spheres model


• 2004-2005: Very Basic playing!

• 2006: Formations/High-level playing!

Videos: Simulation 3D Spheres model


Simulation 3D – Humanoid model


• 2007-2010: Very Basic playing!

• 2011: Formations/High-level playing!

Videos Simulation3D: Humanoid Robots


Middle Size League• Robots are completely autonomous

• 5 robots per team

• Robots around 50x50cm and 80cm height

• Field 18mx12m, green with white lines

• MSL rules based on official FIFA laws



Middle Size League


• 1998-2007: Very Basic playing! Individual Dribbling!

• 2008: Formations SBSP/High-level playing/Setplays!

Videos: Middle Size League


Flexible Strategy for RoboCup

• RoboCup Leagues: Simulation 2D, Simulation 3D, Small-Size, Middle-

Size, SPL and Search and Rescue

• Applications in four distinct teams:

– FC Portugal (University of Porto/Aveiro/Minho)

• Simulation 2D, Simulation 3D, Coach, MR, Rescue, SPL

– CAMBADA (University of Aveiro) – Prof. Nuno Lau



– CAMBADA (University of Aveiro) – Prof. Nuno Lau

• Middle-Size League, RoboCup@Home

– 5DPO (University of Porto) – Prof. A.P.Moreira

• Small-Size League, Middle-Size League

– Portuguese Team (University of Porto/Aveiro/Minho)

• SPL – Standard Platform League

• More than 30 awards in International Competitions for these 4 Teams!

Our Teams: University of Porto/Aveiro

• Simulation 2D: FC Portugal– Best: Winners RoboCup 2000,

– Winners Euro 2000, Euro 2001

• Simulation 3D: FC Portugal– Best: Winner RoboCup 2006,

– Winners Euro 2006, Euro 2007

• Simulation – Coach: FC Portugal



• Simulation – Coach: FC Portugal• Best: Winner RoboCup 2002,

• 2nd RoboCup 2003, 2004

• Simulation – MR League: FC Portugal• Best: 2nd RoboCup 2007

• Rescue Simulation: FC Portugal• Best: Winner Euro 2006

• Middle-Size: CAMBADA (Univ.Aveiro)– Best: Winners RoboCup 2008

• Small-Size: 5DPO (Univ.Porto)– Best: 2nd RoboCup 2006,

– Winners Euro 2001, 2006, 2007

• Middle-Size: 5DPO (Univ.Porto)

Our Teams: University of Porto/Aveiro



• Middle-Size: 5DPO (Univ.Porto)• Best: 3rd Euro 2001

• Standard Platform (Aibo): FC Portugal/FC Portus• Best: 5th RoboCup 2003

• Standard Platform (NAO): Portuguese Team• Best: Starting in 2011


• Artificial Intelligence, Robotics and Simulation



– Strategy and Formations/SBSP



– DPRE - Dynamic Positioning and Role Exchange

– SetPlays and Graphical Setplay Definition

– Generic Optimization of Skills/Decisions

• Applications and other Projects at Portugal


• Coordinate autonomous robots decisions to carry out team tasks as efficiently as possible

• Coordination challenges

• Strategy

The Coordination Problem



• Strategy

• Role assignment

• Formation

• Plan execution

• Communication

Our Approach: “Common Framework for Cooperative Robotics”:

• Strategy - Strategical Coordination and Coaching

• SBSP – Situation Based Strategic Positioning (Formations)

• DPRE – Dynamic Position and Role Exchange

• SetPlay Framework and Graphical Definition


Flexible Strategy for Robotic Teams


• SetPlay Framework and Graphical Definition

• Generic Optimizer of Skills/Decisions

• Bridging the Gap Between Simulation and Robotics

Formalization of a Team Strategy



Coaching

• Game Statistics and Opponent Modeling Information

• Time and Result

• Individual Action: Active/Passive (with/without ball)

• Transitions (Ball losses and Ball recoveries)

• Attacks and Assistances



• Attacks and Assistances

• Ball Possession

• By:– Period

– Region (from and to)

– Team

– Player

– etc.

Coach

Assistant Coach

Players

Gam

e S

tatis

tics

Definitions

Opp

onen

t Mod

elin

g

Field Information Field

Act

ions

Instructions

Principal Coach

Coach Unilang

• Base Concepts: – Time Periods, Regions, Tactics, Formations, Situations, Player Types

• Language Defined in BNF

• Examples:<MESSAGE> ::= (<TIME> <ID> <MESSAGE PART> {<MESSAGE PART>})

<MESSAGE PART> ::= <DEFINITION_MESS> |<STATISTICS_MESS> | <OPP_MOD_MESS> |



<MESSAGE PART> ::= <DEFINITION_MESS> |<STATISTICS_MESS> | <OPP_MOD_MESS> |

<INSTRUCTION_MESS>

TACTIC_DEFINITION> ::= <TEAM_MENTALITY> <GAME_PACE> <TEAM_PRESSURE> <FIELD_USE>

<PLAYING_STYLE> <RISK_TAKEN> <OFFSIDE_TACTIC> <POSITIONING_EXCHANGE_USE>

<FORMATIONS_USED>

<FORMATION> ::= <PREDEFINDED_FORMATION> <FORMATION_NAME> | <FORMATION_DEFINITION>

<PREDEFINED_FORMATION> ::= 433 | 433att | 442 | 343 | 4123 | 352 …

<FORMATION_DEFINITION>::= {(<PLAYER> <POS_NUMBER> <PLAYER_POSITIONING> <PLAYER_TYPE>)}

<PLAYER_POSITIONING> ::= <VERTICAL_POSITIONING> <HORIZONTAL_POSITIONING>

Formations in Robotic Soccer

• Formations are an essential concept in multi-robot teams:

• Provide a coordination framework: tasks/role assignment

• Real impact on team performance

• Can/should be adapted to team and opponent



• Can/should be adapted to team and opponentcapabilities

• Common concept with military units coordinatedmovements or real soccer formations

• Role based models

• Ex: Striker, Supporter, Defender, Goalie

• SPAR – Strategic Positioning with Attraction and Repulsion

• Locker-Room agreement

• SBSP – Situation Based Strategic Positioning

Formation Models



• SBSP – Situation Based Strategic Positioning

• Distinction between active and passive situations

• Distinct team movements for different situations

• Strategic position based on global information (such as currentball position) keeps the team in the selected formation

• SBSP/DT – Situation Based SP with Delaunay Triangulation

• Added flexibility in the definition of positionings

SBSP - Situation Based Strategic Positioning

• Strategic Situation: SBSP – Strategic Positioning

• Active Situation (with/without Ball): Active Behavior

• Definition based on: Situation and Shared info (Ball Position)



SBSP vs SPAR



SBSP with Delaunay Triangulation



Based on Akiyama, 2007

SBSP with Delaunay Triangulation



Formations in the MSL


Videos: Formations in the MSL


SBSP with Flux



SBSP with Flux


• Calculates Flux, Safety and Easiness of all possible points considering the tactic in use!


DPRE - Dynamic Positioning and Role Exchange

• Dynamic Exchange of Positionings and Behaviors based on utility:

– Distances from players positions to their strategic positions

– Positioning importance and adequacy of agents



– Positioning importance and adequacy of agents

• DPRE improves the robotic team collective performance

• Important against opponents with similar collective capabilities

ALGORITHM DynamicPositioningExchange(WorldState, Situation, Positionings)RETURNS Positionings(TeamSize)PARAMETERS WorldState, Positionings[TeamSize], Situation{FOR PL1 = 2 TO TeamSize-1 DO

FOR PL2 = PL1+1 TO TeamSize DO IF PositionValid(PL1) AND PositionValid(PL2) THEN {Dist11 = Distance(Position(Pl1),SBSPPosition(Pl1))

DPRE - Dynamic Positioning and Role Exchange



Dist11 = Distance(Position(Pl1),SBSPPosition(Pl1))Dist22 = Distance(Position(Pl2),SBSPPosition(Pl2))Dist12 = Distance(Position(Pl1),SBSPPosition(Pl2))Dist21 = Distance(Position(Pl2),SBSPPosition(Pl1))Adeq11 = PosAdequacy(Pl1, Positioning[Pl1])Adeq22 = PosAdequacy(Pl2, Positioning[Pl2]) Adeq12 = PosAdequacy(Pl1, Positioning[Pl2]) Adeq21 = PosAdequacy(Pl2, Positioning[Pl1]) Util = ExchangePositions(DPREMode, Situation, Dist11, Dist22, Dist12, Dist21,

Adeq11, Adeq22, Adeq12, Adeq21, PosImp(Positioning[Pl1]), PosImp(Positioning([Pl2])IF Util > ThresUtil(Situation) THEN exchange(Positionings[Pl1], Positionings[Pl2]) }RETURN Positionings

}

ADVCOM –Intelligent Communication

• Challenges: What and When to communicate?

• What to Communicate?

– Individual World State – to improve world state accuracy

– Useful Events – for coordination

• When to Communicate?



• When to Communicate?

– Communication utility is very high or is greater then communication utility (modeled) of teammates!

– Creation of a Communicated World State!

MM - Mutual Modeling

• Motivation and principle:

– Use Teammate and Opponent Models!

– Estimate their positions and actions!

– Fuse this information with visual, sensorial, aural information



information

– Enables more accurate world states

– Very useful when vision and sensors are not of good quality

Setplays: Concept and Definition

Simple, pre-defined but flexible plans, which describe

cooperation and coordination between agents/robots

• Defined before the game by a domain expert

• Easy to define and change

• Human readable language (high abstraction level)

• Selected, Instantiated and executed at run-time (text file)



• Selected, Instantiated and executed at run-time (text file)

Setplay Definition

(setplay :name simpleCorner:players (list (playerRole :roleName CornerP) (playerRole :roleName receiver) (playerRole :roleName shooter))

:steps (seq (step :id 0 :waitTime 15 :abortTime 70:participants

(list (at CornerP (pt :x 52 :y 34)) (at receiver (pt :x 40 :y 25)) (at shooter (pt :x 36 :y 2)))



(at receiver (pt :x 40 :y 25)) (at shooter (pt :x 36 :y 2))) :condition (playm fk_our) :leadPlayer CornerP:transitions (list

(nextStep :id 1:condition (canPassPl :from CornerP :to receiver) :directives (list

(do :players CornerP :actions (bto :players receiver)) (do :players receiver :actions (receivePass))))))

Setplay Definition

(step :id 1 :waitTime 5 :abortTime 70:participants (list (at CornerP (pt :x 52 :y 34)) (at receiver (pt :x 40 :y 25))

(at shooter (pt :x 36 :y 2)) ) :condition (and (bowner :players receiver) (playm play_on)) :leadPlayer receiver:transitions (list

(nextStep :id 2:condition (canPassPl :from receiver :to shooter)



:directives (list(do :players receiver :actions (bto :players shooter)) (do :players shooter :actions (receivePass))))))

(step :id 2 :abortTime 70:participants (list (at CornerP (pt :x 52 :y 34)) (at receiver (pt :x 40 :y 25)) (at shooter (pt :x 36 :y 2)) ) :condition (and (bowner :players shooter) (playm play_on) ) :leadPlayer shooter :transitions (list

(nextStep :id 3 :condition (canShoot :players shooter) :directives (list(do :players shooter :actions (shoot))))))

Setplays - Structure



Setplays – Actions and Conditions



Usage/Interest of Setplay Library

• Setplay Definition/Graphical application

• Implement Conditions and Actions

• Deal with low level Communication

• Decide Setplay start, eventually CBR/ML

• Great flexibility: Application to all RoboCup leagues:



• Great flexibility: Application to all RoboCup leagues: – Simulation 2D, Simulation 3D, Middle Size, MR League, SPL)

Setplays: Graphical Definition


SPlanner

Formal Definition (Setplayframework)

Import

Export


FCPortugal Debug LogPlayer

RCSSMonitor14.0.1

RCSSLogPlayerincluded on

SPlanner

SetPlays in the Simulation 2D League


Videos: Setplay Graphical Definition

Videos: Setplays in the Simulation 2D League

Flexible Coordination of Multi-Robot Teams: Applications in Robotic Soccer, Luis Paulo Reis, LARS/SBR 2012, Fortaleza, Brazil, 5757/23

SetPlays in the MSL

RolePasser RoleReceiver

PassFlag ← TRYING_TO_PASS

Align to receiver Align to Passer

PassFlag ← READY

Kick the ball

PassFlag ← BALL_PASSED

Move to next position Catch ball

Passes

• Essential for teamplay

• 3 phases – Preparation/Alignment

– Pass



Move to next position Catch ball

– Catch ball

• Used by CAMBADA in – Playoff

– Free Challenge 2008

– Also on Playon!

SetPlays in the MSL


Videos: Setplays in the MSL



Simple Example(from FCPortugal 3D):

void FCPAgentH::FillInWSforStrategy() {WorldState& world = SWorldState::getInstance();strategy->WS_GameTime = world.gTime;strategy->WS_Result = world.game->ourGoals- world.game->opponentGoals;strategy->WS_BallPos = world.ball->position.to2d(); /

Flexible Strategy for Robotic Teams

STWorldState <- FillInWSforStrategy();

Actions <- CallStrategy(STWorldState);

ExecuteActions(Actions);


strategy->WS_BallPos = world.ball->position.to2d(); /strategy->WS_BallOwner = world.->ball_owner;strategy->WS_BallIntPos = world.ball->finalPos.to2d();strategy->WS_MyNumber = world.me->unum;strategy->WS_MyDir = world.me->orientation;for (int t = 1; t <= strategy->ST_NUM_PLAYERS; t++) {

strategy->WS_TeamPos[t]= world.getFCPortugalPlayer(t)->position.to2d();strategy->WS_OppPos[t] = world.getOpponentPlayer(t)->position.to2d();strategy->WS_TeamConf[t] = world.getFCPortugalPlayer(t)->conf;strategy->WS_OppConf[t] = world.getOpponentPlayer(t)->conf;

}strategy->WS_PlayMode = world.game->playmode;

}

Generic Optimization of Skills/Decisions


A skill consists in a purposeful, repeatable action taken by the executing agent, such as:

• - Walk (forward/backward/side)

• - Turn around

• - Rotate around a point


• - Rotate around a point

• - Kick the ball

• - Catch the ball (fall down)

• - Get up (front/back)

• ...

These can be specified once and executed as many times as necessary

Humanoid Robot

Parameters

Specification

XML File



Specification Model

Joint Values

Agent Code

Angle Valuessent to the server

at each cycle

Humanoid Robot SkillsFCP Types of Skills

• Slot Behaviors

• CPG Behaviors

• TFS Walk

Skills definition:

• XML File



• XML File

• Flexible

Generic Optimization• Find the best configuration of a set of

parameters to achieve a goal

• The goal is to minimize or maximize a quantity - the value of the objective

function

• The independent variables that can

kick the ball

maximize distance

travelled by the ball

Joint angles at certain

time intervals, ... -



• The independent variables that can change while trying to achieve the goal are known as decision variables

• Decision variables can only take certain values - variable domains

• Decision variables can be subject to further constraints

time intervals, ... -

specification model

parameters

knee joints cannot

bend forward

left & right arm joints

must have the same

values

Generic Optimization



Get Up Front Skill• Get the robot up after it fell down on the ground to its front

• Skill Specification Model: Slot Behavior, Sine interpolation

• Select metaheuristic: Hill climbing, simulated annealing, tabu search, PSO, ACO, genetic algorithms

• 39 decision variables

– after enforcing left & right side equality

• Objectives:



• Objectives:

– Speed

– Stability

– Effectiveness

Get Up Front Skill

Videos: Skill’s Optimization Process



Results: Fast Stable Skills

Videos: Getup, kick and walk skills



Results – 20 m Kick!!!

• Optimization increased Kick length from 9m to aprox 20m!

• More than the double of the best Simulation3D teams



PT Teams: Portuguese Team


• Videos: Portuguese Team and Application to Real Humanoid Robots


Selected Results: FC PortugalCompetition Results: FCPortugal

2000 1st place in the 2D Simulation League, European 20001st place in the 2D Simulation League, RoboCup 2000

2001 3rd place in the 2D Simulation League, RoboCup 20011st place in the 2D Simulation League, European (GO) 2001

2002 1st place in the Coach Competition, RoboCup 2002

2003 2nd place in the Coach Competition, RoboCup 20032004 2nd place in the Coach Competition, RoboCup 20042006 1st place in the 3D Simulation League, RoboCup 2006



2006 1st place in the 3D Simulation League, RoboCup 2006

2nd place in the Small-Size League, RoboCup 20061st place in the 3D Simulation League, European 20061st place in the Rescue Sim League, European 2006

2nd place in the 2D Simulation League, European 20062007 1st place in the 3D Simulation League, European 2007

2nd place in the 2D Simulation League, European 20072nd place in the Physical Visual. League, RoboCup 2007

2009 3rd place in the 3D Simulation League, European 20093rd place in the 2D Simulation League, European 2009

2010 3rd place in the 3D Simulation League, European 20103rd place in the 2D Simulation League, European 2010

Selected Results: CAMBADA, 5DPOCompetition Results: FC Portugal

2011 2nd place in the 3D Simulation League, European 2011 (GO)2nd place in the 2D Simulation League, European 2011 (GO)

2012 1st place in the 3D Simulation League, European 2012 (DO)

3rd place in the 2D Simulation League, European 2012 (DO)2nd place in the Rescue Simulation League, European 2012 (DO)

Competition Results: CAMBADA and 5DPO

1998 5DPO: 3rd place in the SSL League, RoboCup 2000

2001 5DPO: 1st place in the SSL League League, European (GO) 2001



2001 5DPO: 1st place in the SSL League League, European (GO) 2001

5DPO: 3rd place in the MSL League League, European (GO) 20012002 5DPO: 2nd place in the SSL League, European (GO) 20022003 5DPO: 2nd place in the SSL League, European (GO) 20032004 5DPO: 1st place in the SSL League, European (GO) 2004

2006 5DPO: 1st place in the SSL League, European 2006

5DPO: 2nd place in the SSL League, RoboCup 2006

2008 CAMBADA: 1st place in the MSL League, RoboCup 2008

2009 CAMBADA: 3rd place in the MSL League, RoboCup 2009

2010 CAMBADA: 2nd place in the MSL League, European 2010CAMBADA: 3rd place in the MSL League, RoboCup 2010

2011 CAMBADA: 3rd place in the MSL League, RoboCup 2011


• Artificial Intelligence and Robotics



• Applications and other Projects at Univ. of Porto and Minho



• Applications and other Projects at Univ. of Porto and Minho

– Agent Based Simulation: EcoSimNet, FlightSimNet

– Educational/Assistive Robotics: Intellwheels, Robot Dancing

– Strategic Reasoning: Poker Agents

– Real Sports: Soccer, Indoor Sports (Handball)


• Realistic simulation of ecological models

– Difficult task

– Mixing complex biological, chemical and physical processes

– Slowness associated to each simulation

• Integrate human factor/decisions in the simulation

EcoSimNet: Agent-Based Ecologic Simulation



simulation

• Provide flexible services to help sustainable management of aquatic ecosystems

– Custom solutions to “any” aquatic ecosystem

– Environmental impact studies/water framework directive

– Aquaculture optimization/Carrying capacity

• EcoDynamo

– Simulator for aquatic ecosystems

• Intelligent Agents

– Include the human rationality in the scenarios generation and decisions

• ECOLANG

EcoSimNet: Agent-Based Ecologic Simulation



• ECOLANG

– Communication language for simulations of complex ecological systems

• EcoSimNet

– Platform that integrates all the previous

– Enables parallel simulations -clusters

• Limited mobility:

– Increment of the elderly population

– Physical disabilities: Cerebral Palsy, Tetraplegia

– Inability to control electric wheelchairs

• Intelligent Wheelchair: Robotic device provided with

sensorial and actuation systems and processing capabilities:

0.00

2.00

4.00

6.00

8.00

1960 1980 2000 2020Year

World elderly pop.

Intellwheels: Intelligent Wheelchair



sensorial and actuation systems and processing capabilities:

– (Semi)Autonomous behavior

– Obstacle avoidance, navigation and planning

– Flexible Human-Machine interaction

– Cooperation with other IW/devices

• IW useful in practice:

– Very low cost and ergonomic impact

– Simulation/mixed reality

– Flexible multi-modal interface

– IW development platform




Facial Expressions Voice Commands Head GesturesJoystick / Buttons

...



Facial Expressions Voice Commands Head GesturesJoystick / Buttons

...


Motivation:

• Improve human-robot social interaction: – by means of bodily communication

• Improve robotic expressiveness:

– By imitation of human motion

• Dance as a rich case study

Robot Dancing based on RTBT



• Dance as a rich case study

Goals:

• Map human movement periodic patterns onto humanoid robots

• Model and generate humanoid dance– Samba dance style as first case study

Dance Motion Analysis Dance Motion Generation







Sports Analysis: Handball and Soccer

• Artificial Intelligence x Computer Vision x Intelligent Simulation

• Detection and Tracking of Ball and Players

• Intelligent Game Analysis: Coach Reports (Data Mining)

• Creation of Players and Team Models (High-level models



• Creation of Players and Team Models (High-level models + Data mining)

• Realistic Simulation of Soccer/Handball Games

Colour

Calib.

Back/Forg

Detect

Forg

Categ.

Colour

Update

Pixel

Aggr.

Indoor Sports Analysis: Handball



Poker Strategy with Online Opp. Modeling

• Poker is a game humans find fascinating

• Huge and growing market:

• Casinos, tournaments, online, television

• Challenge of Poker for DAI: Many new and interesting

problems not faced in Chess, Go, or Backgammon:



problems not faced in Chess, Go, or Backgammon:

• Random, hidden information, bluffing and trapping, need for opponent modeling

• Poker is a simple game that demands for complex strategies

• Project General Objective:

– Develop an agent capable of beating the best human players in “No Limit, Multi-Player, Texas Hold’em, Poker”

Poker Strategy with Online Opp. Modeling

Agent 1

Agent 2

Agent n

LIACC Poker

SimulatorAgent 3

AAAI Poker

Competition

Server

St OM

POKERLANG

<STRATEGY>::= {<ACTIVATION_CONDITION> <TACTIC>}

<ACTIVATION_CONDITION>::= {<EVALUATOR>}

<TACTIC>::= <PREDEFINED_TACTIC> | <TACTIC_NAME><TACTIC_DEFINITION>

<PREDEFINED_TACTIC>::= loose_agressive | loose_passive | tight_agressive |

tight_passive

<TACTIC_NAME>::= [string]

<TACTIC_DEFINITION>::={<BEHAVIOUR> <VALUE>}

<BEHAVIOUR>::= {<RULE>}

<RULE>::= {<EVALUATOR> | <PREDICTOR>} <ACTION>

<EVALUATOR>::= <NUMBER_OF_PLAYERS> | <STACK> | <POT_ODDS> |



Human Interface

HumanPlayer

Poker BuilderOnline Poker

Server 1

Online Poker

Server n

StrategyOpp.Modelling

AgentOpp.

Model

St OM<EVALUATOR>::= <NUMBER_OF_PLAYERS> | <STACK> | <POT_ODDS> |

<HAND_REGION> | <POSITION_AT_TABLE>

<PREDICTOR>::= <IMPLIED_ODDS> | <OPPONENT_HAND> | <OPPONENT_IN_GAME> |

<STEAL_BET> | <IMAGE_AT_TABLE>

<ACTION>::= {<PREDEFINED_ACTION><PERC> | <DEFINED_ACTION><PERC>}

<PREDEFINED_ACTION>::= <STEAL_THE_POT> | <SEMI_BLUFF> |

<CHECK_RAISE_BLUFF> | <SQUEEZE_PLAY> | <CHECK_CALL_TRAP> |

<CHECK_RAISE_TRAP> | <POST_OAK_BLUFF>

Research Team – Finished StudentsFormer Phd Students (finish date)

1. Pedro M. V. Moreira (PRODEP/IPVC, Mar2009)

2. Vasco H. Vinhas G. Moreira (FCT, Oct2010)

3. Francisco A. F. Reinaldo (FCT/Brasil, Nov2010)

4. Rodrigo A. M. Braga (Capes/Brasil , Nov2010)

5. António M. C. Pereira (FCT/FEUP, Dec2010)

6. Pedro M. H. C. Abreu (FCT, Mar2011)

7. Daniel C. Silva (FCT, Nov2011)

9. Jorge Filipe de Ribeiro Teixeira, Mar2008

10. João Pedro Bugalho Certo, Mar2008

11. João Manuel Marques de Oliveira, Mar2008

12. Dinis Alexandre Marialva Felix, Mar2008

13. Péricles Filomeno Monteiro Pinto, May2008

14. António Pedro da Silva Mota, May2008

15. João Carlos Leite Ferreira, Jun2008

16. João Manuel Lobato Oliveira, Jul2008

17. Pedro Miguel de Castro Malheiro, Jul2008

18. Márcio Miguel Couto de Sousa, Jul2008



7. Daniel C. Silva (FCT, Nov2011)

8. António Pedro Costa (FCT/U.Aveiro, Mar2012)

9. Luís H. R. Mota (FCT/ISCTE, Apr2012)

10. Pedro Valente (Univ. South. Denmark, Aug2012)

Former MSc Students (finish date)

1. Pedro Miguel Teixeira Faria, Nov2000

2. Pedro Nuno Macedo Leite da Silva, Dec2000

3. Sérgio Fernando Grilate Louro, Sep2004

4. Paulo César Basto Cardoso, July2006

5. André Monteiro Oliveira Restivo, Oct2006

6. Darya Alexandrovna Barteneva, Apr2007

7. Marcelo Roberto Petry, Feb2008

18. Márcio Miguel Couto de Sousa, Jul2008

19. Marco Filipe Chaves Pinto da Silva, Jul2008

20. José Miguel Neves Leão de Campos, Jul2008

21. Ricardo Nuno Nóbrega Silva, Jul2008

22. Daniel Tiago de Jesus Coutinho, Jul2008

23. André Miguel de Oliveira Rodrigues, Jul2008

24. Pedro Melo Campos, Jul2008

25. Rui André Teixeira de Sousa Sêca, Jul2008

26. Pedro Daniel da Cunha Mendes, Jul2008

27. Duarte Miguel Faria Ferreira Cabral, Jul2008

28. João Nuno Boavista Taborda, Jul2008

29. Luís Ângelo de Sá Barbosa, Jul2008

30. Filipe Manuel Miranda da Cruz, Nov2008

Research Team – Finished StudentsFormer MSc Students (finish date)

31. Hugo Rafael de Brito Picado, Dec2008

32. Nuno Filipe dos Reis Almeida, Dec2008

33. Pedro César Fonseca Gonçalves Alves, Jan2009

34. Rui Manuel Figueiredo de Almeida, Mar2009

35. Pedro Ricardo da Nova Valente, Mar2009

36. Luís Pedro Brandão Martinho, Mar2009

37. Rui Filipe Lourenço Guedes, May2009

38. Luís Filipe Gonçalves Lemos, May2009

50. Abel Fernando Neto M. Santos, Jul2010

51. Pedro Daniel Pereira Alves de Sousa, Jul2010

52. João Paulo Santos Portela, Jul2010

53. Luis Filipe GuimarãesTeófilo, Jul2010

54. Hugo Miguel Pereira Peixoto, Jul2010

55. Pedro Miguel Amorim Gomes, Jul2010

56. Hugo Filipe P. A. S. Mendes, Jul2010

57. Miguel Augusto Pereira de Oliveira, Dec2010

58. José Luís Machado Rei, Feb2011

59. Ivo Miguel da Paz dos Reis Gomes, Feb2011



38. Luís Filipe Gonçalves Lemos, May2009

39. José Maria Mendonça e Moura, Jul2009

40. Mário Joaquim Firmino Leite Faria, Jul2009

41. Antero Guimarães Pacheco da Silva, Jul2009

42. Rui Manuel Fernando Lopes, Jul2009

43. Catarina M. B. N. Santiago, Jul2009

44. Nuno Pedro Silva da Cruz, Jul200

45. Ricardo João Teixeira Santos Mestre, Jul2009

46. José Carlos Pinto Miranda, Dec2009

46. Frederico Manuel S. C. B. Cunha, Mar2010

47. Vitor Hugo da Silva Pereira, Mar2010

48. Carlos Jorge Lemos Nunes, Mar2010

49. Filipe Teixeira Marques, Jul2010

59. Ivo Miguel da Paz dos Reis Gomes, Feb2011

60. Sérgio Miguel Fontes de Vasconcelos, Feb2011

61. André Almeida Vidal, Feb2011

62. Paulo Sérgio Ribeiro Martins , Feb 2011

63. Maria João Tavares Barbosa Jul2011

64. André Susano Pinto Jul2011

65. António Jorge Alpedrinha Ramos, Jul2011

66. João Guilherme Cravo, Jul2011

67. Luís Miranda Cruz, Jul2011

68. Nuno Miguel da Silva Passos, Jul2011

69. Paulo Alexandre Alves de Sousa, Jul2011

70. José Eduardo Castro Xavier, Jul2011

71. Marco André Silva, Jul2011

Current Research TeamCurrent PhD Students (pred finish dates)

1. Roberto Rodrigues (FEUP/PRODEI, E.S.F.V., Dec2012)

2. João Lobato Oliveira (FEUP/PRODEI, FCT, Dec2012)

3. Dulce Mota (FEUP/PRODEI, ISEP/PROTEC, Dec2012)

4. Marcelo Petry (FEUP/PRODEI, FCT/Brasil, 2013)

5. Catarina Santiago (FEUP/PRODEI, F.Gulbenkian, 2013)

6. Nima Shafii (FEUP/PRODEI, FCT/Iran, 2013)

7. Paula Rego (FEUP/PRODEI, IPVC/PROTEC, 2013)

8. Fernando Almeida (MAPI, FCT/IPV, 2013)

PhD Researchers1. Pedro M. V. Moreira (IPVC)

2. Rodrigo A. M. Braga (Univ. Fed. Sta Catarina)

3. António M. C. Pereira (FEUP)

4. Pedro M. H. C. Abreu (DEI/UC)

5. Daniel C. Silva (DEI/UC)

6. Luís H. R. Mota (ISCTE)

7. António Pedro Costa (Loudomedia)

Current MSc Students



8. Fernando Almeida (MAPI, FCT/IPV, 2013)

9. Marco Guimarães (FADEUP, Sports, 2013)

10. Liliana Mendes (FPCUP, Psychology, 2014)

11. Luis Teófilo (FEUP/PRODEI, FCT, 2014)

12. Rui Chirlo (FEUP/PRODEI, FCNAUP, 2014)

13. Daniel Constantino (FEUP/PRODEI, ESVC, 2014)

14. Paulo Trigueiros (UMinho/DEI, 2014)

15. Abbas Abdlomeki (MAPI, FCT/Iran, 2015)

Current PostDoc Students1. Bruno Pimentel (FCT/ PhD UA, 2010-2012)

Current MSc Students (pred finish dates)

1. Bruno Vaz Queiroga Alves, 13 Feb2012

2. Seraphin Miranda, 13 Feb2012

3. João Couto Soares, 13 Feb2012

4. Romina Neves, 13 Feb2012

5. Rui Pedro Gomes Ferreira, 20 Feb2012

6. Nuno Resende, Jul2012

7. Cesar, Brandão, Jul2012

8. Rui Monteiro, Jul2012

9. Gil J. Silva, Jul 2012

10. Carlos Eduardo Ermida Santos, Jul2012

Collaborations - Conferences

• 16th EPIA 2013 (Portuguese Conf. on Artificial Intelligence), Azores, Portugal , September 2013 - http://www.epia2013.uac.pt/

• Propose a Thematic Track (Deadline December 2012)

• Submit Papers to EPIA – Portuguese Conference on Artificial Intelligence (Deadline March 2013)

• 13th Portuguese Robotics Open 2013 (Festival Nacional de Robótica), Lisbon, April 2013 - www.robotica2012.org/ (webpage 2013 not yet available)

• Participate in the Competitions (Deadline March 2013)

• Submit Papers to the International Conference on Autonomous Robot Systems and Competitions (Deadline January 2013)



(Deadline January 2013)

• 8th CISTI 2013 (Iberian Conf. on Inf Systems na Technologies), Lisbon, June 2013 - http://www.aisti.eu/cisti2013/

• Propose a Workshop (Deadline November 2012)

• Submit Papers to WISA@CISTI – Workshop on Intelligent Systems and Applications (Deadline March 2013)

• PhD in Portugal (or Sandwich Portugal/Brasil)

• Joint Participation in RoboCup

• SPR – Portuguese Robotics Society

• Joint Research Projects

• LIACC, Porto

• University of Minho , University of Porto, University of Aveiro

• INESC Brasil

• Coordination of Teams in Adversarial Environments: Strategy, Formations (SBSP/DT), DPRE, Setplays

• Complete Tactical/Formation Framework including graphical interface

• Complete Setplay Framework including graphical interface

• Generic Coordination Framework/Library:

• May be used for coordinating any team:

– World State -> High-Level Decision!

Conclusions



– World State -> High-Level Decision!

• Useful for researching on low-level Robotics!

• Several MAS/MRT coordination methodologies developed with competition success

• Applications to different robots for distinct cooperative robotic tasks and also to other domains: Rescue, surveillance, military apps

Future Work• Strategy based on Tactics, Formations, Flux and Setplays:

– Formations: flexible use of global vs local info

– Apply and test in other leagues

– Test Strategy definition by domain experts (using graphical application)

– Heterogeneous Robot Teams and Human-Robot Teams

• Setplays Framework

– Learning/optimizing setplays using ML





– Test Setplay definition by domain experts (using graphical application)

– Heterogeneous Robot Teams and Human-Robot Teams

• Release Strategy and Setplay Frameworks for the community

• Other Current Work: – Bridging the Gap between Simulation and Real Robotics: MSL Simulation, SPL League

(3D Sim), Real Sports

– Apply Strategy to other domains: Computer Poker– Real Soccer/Sports Research: Individual/team decision, game analysis, and realistic

players/game simulation

Related Publications (1)• Luis Mota, Luís Paulo Reis and Nuno Lau, Multi-Robot Coordination using Setplays in the Middle-size and

Simulation Leagues, Mechatronics, Elsevier, Vol. 21, Issue 2, pp. 434-444, March 2011, ISSN: 0957-4158, DOI: 10.1016/j.mechatronics.2010.05.005) (IF: 0.94; SCImago Q2)

• Rodrigo A.M. Braga, Marcelo Petry, Luís Paulo Reis, A. Paulo .Moreira, IntellWheels: A Modular Development

Platform for Intelligent Wheelchairs. JRRD - Journal of Rehabilitation Research and Development, Dep. of Veterans Affairs, USA, Vol. 48, Issue 9, pp. 1061-1076, Dec2011, ISSN: 0748-7711, (IF: 1.71; SCImago Q1)

• Pedro H. Abreu, J.Moura, Daniel C. Silva, Luís Paulo Reis, Júlio Garganta, Performance Analysis in Soccer: a

Cartesian Coordinates based Approach using RoboCup Data, Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Verlag, Germany, Vol. 16, pp. 47–61, ISSN: 1432-7643, January 2012 (IF: 1.51; SCImago Q2)



(IF: 1.51; SCImago Q2)

• Pedro Abreu, João Moreira, Israel Costa, Daniel Castelão, João Moreira, Luís Paulo Reis, Júlio Garganta, Human

vs. Virtual Robotic Soccer: A Technical Analysis about Two Realities, European Journal of Sport Science, Taylor & Francis, Vol. 12, Issue 1, pp.26-35, January 2012, ISSN: 1746-1391 (IF: 0.89; SCImago Q2).

• Daniel Silva, Rodrigo A.M. Braga, Luís Paulo Reis, Eugénio Oliveira. Designing a Meta-Model for a Generic

Robotic Agent System using GAIA Methodology. Information Sciences, Volume 195, pp. 190-210, July 2012, Elsevier, ISSN: 0020-0255, (IF:2.84; SCImago Q1) (online first, to appear)

• João Lobato Oliveira, Luiz Naveda, Fabien Gouyon, Luís Paulo Reis, Paulo Sousa, Marc Leman. A

Parameterizable Spatiotemporal Representation of Popular Dance Styles for Humanoid Dancing Characters.

EURASIP Journal on Audio, Speech, and Music Processing, Hindawi Publishing Corporation, USA, ISSN: 1687-4714, 1687-4722 (IF: 0.34; SCImago Q3) (to appear)

• B.M.Faria, G.Castillo, N.Lau, L.P.Reis, “Classification of FC Portugal Robotic Soccer Formations: A Comparative Study of Machine Learning Algorithms”, Robotica Journal, n. 82, 1st Trim., pp. 4-9, 2011, ISSN: 0874-9019

Related Publications (2)

• C.B.Santiago, A.Sousa, L.P.Reis, M.L.Estriga, "Real Time Colour Based Player Tracking in Indoor Sports", Computational Vision and Medical Image Processing, Computational Methods in Applied Sciences, 2011, Volume 19, 17-35, (Springer)

• P.Martins, L.P.Reis, L.Teófilo, "Poker vision: Playing cards and chips identification based on image processing", (2011) Lecture Notes in Computer Science, 6669 LNCS, pp. 436-443. (Springer)

• P.Abreu, I.Costa, D.Castelão, L.P.Reis, J.Garganta, "Human vs. robotic soccer: How far are they? A statistical comparison", (2011) Lecture Notes in Computer Science, 6556 LNAI, pp. 242-253. (Springer)

• N.Shafii, L.P.Reis, N.Lau, "Biped walking using coronal and sagittal movements based on truncated Fourier series", (2011) Lecture Notes in Computer Science, 6556 LNAI, pp. 324-335. (Springer)

• E.Domingues, N.Lau, B.Pimentel, N.Shafii, L.P.Reis, A.J.R.Neves, "Humanoid behaviors: From



• E.Domingues, N.Lau, B.Pimentel, N.Shafii, L.P.Reis, A.J.R.Neves, "Humanoid behaviors: From simulation to a real robot" (2011) Springer LNCS , 7026 LNAI, pp. 352-364. (Springer)

• A.S.Pinto, A.Pronobis, L.P. Reis, "Novelty detection using graphical models for semantic room classification", (2011) Lecture Notes in Computer Science, 7026 LNAI, pp. 326-339. (Springer)

• Abdolmaleki, M.Movahedi, S.Salehi, N.Lau, L.P.Reis, "A reinforcement learning based method for optimizing the process of decision making in fire brigade agents", (2011) Lecture Notes in Computer Science, 7026 LNAI, pp. 340-351. (Springer)

• P.A.Rego, P.M.Moreira, L.P.Reis, "Natural user interfaces in serious games for rehabilitation", (2011) Proceedings of the 6th Iberian Conference on Information, Systems and Technologies, CISTI 2011, art. no. 5974331. (IEEE)

• N.Shafii, L.P.Reis, R.J.F.Rossetti,"Two humanoid simulators: Comparison and synthesis", (2011) Proceedings of the 6th Iberian Conference on Information Systems and Technologies, CISTI 2011, art. no. 5974352. (IEEE)

Related Publications (3)

• P.Sousa, J.L. Oliveira, L.P.Reis, F.Gouyon, "Humanized robot dancing: Humanoid motion retargeting

based in a metrical representation of human dance styles", (2011) Springer, 7026 LNAI, pp. 392-406. (Springer)

• C.B.Santiago, J.L.Oliveira, L.P.Reis, A.Sousa, "Autonomous robot dancing synchronized to musical

rhythmic stimuli", (2011) Proc. of the 6th Iberian Conf. on Info. Syst. Technologies, CISTI 2011, (IEEE)

• C.B. Santiago, L.P.Reis, R.Rossetti, A.Sousa, "Foundations for creating a handball sport simulator", (2011) Proceedings of the 6th Iberian Conf. on Information Systems and Technologies, CISTI 2011, (IEEE)

• Luís Mota, Luís Paulo Reis, Nuno Lau, Multi-Robot Coordination using Setplays in the Simulation

League, Proc. 10th Conf. on Mobile Robots and Competitions, ROBÓTICA'2010, March, Leiria, 2010.



League, Proc. 10th Conf. on Mobile Robots and Competitions, ROBÓTICA'2010, March, Leiria, 2010.

• Brígida Mónica Faria, Gladys Castillo, Nuno Lau, Luis Paulo Reis, Classification of FC Portugal Robotic

Soccer Formations: A Comparative Study of Machine Learning Algorithms, Proc. of the 10th Conference on Mobile Robots and Competitions, - ROBÓTICA'2010, March, Leiria, 2010.

• Luís Paulo Reis, Rui Lopes, Luís Mota, Nuno Lau, Playmaker: graphical definition of formations and

setplays, Second Workshop on Intelligent Systems and Applications (WISA), CISTI 2010 - 5ª ConferênciaIbérica de Sistemas e Tecnologias de Informação, Santiago de Compostela, 16-19 Junho, 2010.

• Brigida Monica Faria, Luis Paulo Reis, Nuno Lau, Gladys Castillo, Machine Learning Algorithms applied

to the Classification of Robotic Soccer Formations and Opponent Teams, IEEE International Conference on Cybernetics and Intelligent Systems and IEEE International Conference on Robotics, Automation and Mechatronics (IEEE CIS & RAM 2010), Singapura, 2010.

Related Publications (4)• Nuno Lau, Luis Seabra Lopes, Gustavo Corrente, Nelson Filipe, Ricardo Sequeira, Robot team

coordination using dynamic role and positioning assignment and role based setplays, Mechatronics, Elsevier, ISSN 0957-4158, 2010 (In Press).

• João Silva, Nuno Lau, Antonio J. R. Neves, João Rodrigues, José Luis Azevedo, World modeling on an MSL robotic soccer team, Mechatronics, Elsevier, ISSN 0957-4158, 2010 (In Press)

• Nima Shafii, Omid Mohamad Nezami, Siavash Aslani and Saeed Shiry Ghidary. Evolution of Biped Walking Using Truncated Fourier Series and Particle Swarm Optimization, RoboCup Symposium 2009, J.Baltes et al. editors, Springer, LNAI, Graz, Austria, 2009.

• Frederico Santos, Luis Almeida, Luis Seabra Lopes, José Luís Azevedo , Manuel Bernardo Cunha, Communicating among Robots in the RoboCup Middle-Size League, RoboCup Symposium, J.Baltes et al. es, Springer, LNAI, Graz, Austria, 2009.



al. es, Springer, LNAI, Graz, Austria, 2009.• Márcio Sousa, Rodrigo Braga and Luis Paulo Reis. Intellwheels MMI: A Flexible Interface for an Intelligent

Wheelchair, RoboCup Symposium 2009, J.Baltes et al., editors, Springer, LNAI, Graz, Austria, 2009.• Pedro Malheiro, Rodrigo Braga,Luis Paulo Reis, Development of a Realistic Simulator for Robotic

Intelligent Wheelchairs in a Hospital Environment, RoboCup Symposium 2009, J.Baltes et al. edsSpringer, LNAI, Graz, Austria, 2009.

• Hugo Picado, Marcos Gestal, Nuno Lau, Luís Paulo Reis, Ana Maria Tomé, Automatic Generation ofBiped Walk Behavior Using Genetic Algorithms. In J.Cabestany et al. (Eds.), 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Springer, LNCS Vol. 5517, pp. 805-812, Salamanca, Spain, June 10-12, 2009.

• André Conceição, A. Paulo Moreira, Paulo Costa, A Practical approach of Modeling and Parameters Estimation for OmniDirectional Mobile Robots, IEEE/ASME Transactions on Mechatronics, Vol. 14, Nº 3, pp. 377-381, June 2009.

Related Publications (5)• Luís Mota, Nuno Lau, Luis Paulo Reis, Coordination in RoboCup’s 2D Simulation League: Setplays as

flexible, Multi-Robot plans, IEEE International Conference on Cybernetics and Intelligent Systems and IEEE Int. Conf. on Robotics, Automation and Mechatronics (IEEE CIS & RAM 2010), Singapura, 2010

• André Conceição, A. Paulo Moreira, Paulo Costa, A Practical approach of Modeling and Parameters Estimation for OmniDirectional Mobile Robots, IEEE/ASME Transactions on Mechatronics, Vol. 14, Nº 3, pp. 377-381, June 2009.

• Nuno Lau, Luís Seabra Lopes, G. Corrente and Nelson Filipe, Multi-Robot Team Coordination Through Roles, Positioning and Coordinated Procedures, Proc.IEEE/RSJ Int. Conf. on Intelligent Robots and Systems – IROS 2009, St. Louis, USA, Oct. 2009.

• Rui Almeida, Luís Paulo Reis, Alípio Mário Jorge: Analysis and Forecast of Team Formation in the Simulated Robotic Soccer Domain, 14th Port. Conf. on Artificial Intelligence, EPIA'2009, Aveiro, LNAI



Simulated Robotic Soccer Domain, 14th Port. Conf. on Artificial Intelligence, EPIA'2009, Aveiro, LNAI 5816, Springer, pp 239-250, October 12-15, 2009.

• Nuno Lau, Luis Seabra Lopes, Gustavo Corrente and Nelson Filipe, Roles, Positionings and Set Plays to Coordinate a MSL Robot Team, 14th Port. Conf. on Artificial Intelligence, EPIA'2009, Aveiro, LNAI 5816, Springer, pp 323-337, October 12-15, 2009.

• Luis Mota, Luís Paulo Reis, A Common Framework for Cooperative Robotics: an Open, Fault Tolerant Architecture for Multi-league RoboCup Teams, International Conference on Simulation Modeling and Programming for Autonomous Robots (SIMPAR 2008), Springer-Verlag, LNCS/LNAI series, pp. 171-182, Venice, Italy, November, 3-7, 2008.

• Nuno Lau, Luís Paulo Reis and João Certo, Multi-Level, Functional, Spatial and Temporal Agent’s Reasoning Debugging, Proc. 13th Port.Conf. on AI, EPIA 2007, New Trends in Artificial Intelligence, pp. 716-726, Guimarães, Portugal, December 3-6, 2007.

• Nuno Lau and Luis Paulo Reis, FC Portugal - High-level Coordination Methodologies in Soccer Robotics, Robotic Soccer, Book edited by Pedro Lima, Itech Education and Publishing, Vienna, Austria, pp. 167-192, December 2007, ISBN 978-3-902613-21-9.

Related Publications (6)• Luis Mota, Luís Paulo Reis, An Elementary Communication Framework for Open Co-operative RoboCup Soccer

Teams, in Sapaty P; Filipe J (Eds.) 4th International Conference on Informatics in Control, Automation and Robotics - ICINCO 2007 – 3rd International Workshop on Multi-Agent Robotic Systems (MARS 2007), pp. 97-101, Angers, France, May 9-12, 2007.

• João Certo, Nuno Lau e Luís Paulo Reis, A Generic Multi-Robot Coordination Strategic Layer, RoboComm 2007 - First International Conf. on Robot Communication and Coordination, Athens, Greece, October 15-17, 2007.

• Luís Mota e Luís Paulo Reis, Setplays: Achieving Coordination by the appropriate Use of arbitrary Pre-defined

Flexible Plans and inter-robot Communication, RoboComm 2007 - 1st Int. Conf. on Robot Communication and Coordination, Athens, Greece, October 15-17, 2007.

• Nuno Lau, Luís Paulo Reis e João Certo, Understanding Dynamic Agent’s Reasoning, In Progress in Artificial Intelligence, 13th Port. Conf. on AI, EPIA 2007, Guimarães, Portugal, December 3-6, 2007, Springer LCNS, Vol.



Intelligence, 13th Port. Conf. on AI, EPIA 2007, Guimarães, Portugal, December 3-6, 2007, Springer LCNS, Vol. 4874, pp. 542-551, 2007.

• André Scolari Conceição, A. Paulo Moreira, Luís Paulo Reis and Paulo J. Costa. Architecture of Cooperation for

Multi-Robot Systems, 1st IFAC Workshop on Multivehicle Systems (MVS'06), Bahia Conv. Center, Salvador, Brazil, October 2 – 3, 2006.

• Luís Paulo Reis and Nuno Lau, COACH UNILANG – A Standard Language for Coaching a (Robo) Soccer Team,

in Andreas Birk, Silvia Coradeschi and Satoshi Tadokoro, editors, RoboCup2001 Symposium: Robot Soccer World Cup V, Springer Verlag LNAI, Vol. 2377, pp. 183-192, Berlin, 2002, ISBN 3-540-43912-9.

• Luis Paulo Reis, Nuno Lau and Eugénio C. Oliveira, Situation Based Strategic Positioning for Coordinating a

Team of Homogeneous Agents in M.Hannebauer, J.Wendler and E.Pagello Editors, Balancing Reactivity and Social Deliberation in Multi-Agent System – From RoboCup to Real-World Applications, Springer LNAI, Vol. 2103, pp. 175-197, 2001

Luís Paulo Reis

Questions?Flexible Coordination of Multi-Robot

Teams: Applications in Robotic Soccer


Luís Paulo [email protected]

http://www3.dsi.uminho.pt/lpreis

Member of the Directive Board of LIACC – Artificial Intelligence and Computer Science

Lab. Of the University of Porto, Portugal

Associate Professor at School of Engineering, University of Minho, Portugal

Documents

Flexible Coordination of Multi-Robot Teams: Applications