Research on Research on Robot Soccer Robot Soccer

and what and what PSU can doPSU can do

The perceptions The perceptions

Three perceptions: Three perceptions: seesee, , hearhear and and sense_bodysense_body..

All related to one system of All related to one system of perception.perception.

Representation of perceptions:Representation of perceptions:(see 1 (ball …) …)(see 1 (ball …) …)

Visual PerceptionVisual Perception

seesee.. List of objects recognized: List of objects recognized:

– type, type, – direction, direction, – distance, distance, – speed, speed, – number.number.

Lines, gates, boundaries, ball.Lines, gates, boundaries, ball.

sense_bodysense_body

Force detectionForce detection Energy available.Energy available.

Principal actions:Principal actions: – dashdash, , – kickkick, , – turnturn – saysay..

ActionsActions

– Role levelRole level : Determines the roles of each : Determines the roles of each robot. robot.

(defender, attacker and goal (defender, attacker and goal keeper) keeper)

– Action levelAction level : Selects actions of each robot. : Selects actions of each robot.

(shooting, blocking, dribbling, (shooting, blocking, dribbling, etc) etc)

– Behavior levelBehavior level : Move and obstacle avoidance : Move and obstacle avoidance– Execution levelExecution level : Motor control : Motor control

Role level

VarianVariants of ts of ControControl l structstructureure

Vision-based systemVision-based system– Remote brainless Remote brainless

systemsystem– Brain-on-board system Brain-on-board system

Robot-based systemRobot-based system

Selection guidelinesSelection guidelines– Developer’s interestsDeveloper’s interests– Computational capabilities of Computational capabilities of

host computer and vision host computer and vision systemsystem

– Capabilities of the Capabilities of the robotsrobots

– CostCost

The system can be classified using The system can be classified using the the location of intelligencelocation of intelligence

Classification of Robot Classification of Robot Soccer SystemsSoccer Systems

Centralized systemCentralized system Simple and inexpensive Easy to develop the robot Simple and inexpensive Easy to develop the robot No local sensors.No local sensors. Fast computing time Fast computing time

and sampling timeand sampling time Easy to debug and upgrade the programEasy to debug and upgrade the program

Remote-Brainless Remote-Brainless SystemSystem

High cost vision system and host computerHigh cost vision system and host computer

A type of vision-based systemA type of vision-based system

Intelligent part is implemented Intelligent part is implemented in the host computer. in the host computer.

Robots Robots The robots consist of The robots consist of driving mechanism,driving mechanism, communication partcommunication part, and , and computational computational

partpart for velocity and for processing the for velocity and for processing the data received from a hostdata received from a host computer computer Host computerHost computer

All the calculations for vision data processing, strategies, position control of robots All the calculations for vision data processing, strategies, position control of robots and so on, are done in the and so on, are done in the host computerhost computer which controls robots like radio - which controls robots like radio -controlled car controlled car

Remote-Remote-Brainless Brainless SystemSystem

Brain-on-board Brain-on-board system system

Intermediate levelIntermediate level between the centralized and the distributed systems / between the centralized and the distributed systems / between the remote-brainless and the robot based systems.between the remote-brainless and the robot based systems.

Robots can use Robots can use local sensorslocal sensors to move to the goal and to avoid the opponent. to move to the goal and to avoid the opponent. Can Can decompose the systemdecompose the system into high level (host computer) into high level (host computer)

and low level (robot systems).and low level (robot systems). Easy to make Easy to make the system in the system in

modular formmodular form

A type of vision-based systemA type of vision-based system

Intelligence is partially Intelligence is partially implemented in the host implemented in the host computer and robots.computer and robots.

Robots Robots The robots have functions such as velocity control, position control, obstacle The robots have functions such as velocity control, position control, obstacle

avoidance, etc.avoidance, etc. Host computerHost computer

The host The host computer processes vision datacomputer processes vision data and and calculates next behaviorscalculates next behaviors of robots of robots according to strategies and according to strategies and sends commandssends commands to the robots using RF modem. to the robots using RF modem.

Brain-Brain-on-on-

board board system system

Robot-based Robot-based systemsystem

Suitable when the Suitable when the large number of agentslarge number of agents exist exist Complex and Complex and expensiveexpensive Need Need communication among robotscommunication among robots

Distributed system Distributed system

Intelligent part is Intelligent part is implemented in the implemented in the robots.robots.

Robots Robots The robots decide their own behavior autonomously using the received The robots decide their own behavior autonomously using the received

vision data, own sensor data and strategies. vision data, own sensor data and strategies. Host computerHost computer

The The host computer processes only vision datahost computer processes only vision data

can be considered as a can be considered as a kind of sensor.kind of sensor.

Robot-Robot-based based systemsystem

Main PCMain PC Serial PortSerial Port

– Select the serial communication portSelect the serial communication port Home GoalHome Goal

– Select the home side on the screenSelect the home side on the screen Find ObjectsFind Objects

– Check the box of which you like to find on the fieldCheck the box of which you like to find on the field Initial Position:Initial Position: tell the vision system the initial tell the vision system the initial

position position

of each objectof each object– E.g.) for the ballE.g.) for the ball

i) turn on the radio button of ‘Ball’i) turn on the radio button of ‘Ball’

ii) place the mouse on the ball and press the left buttonii) place the mouse on the ball and press the left button– Repeat above procedure for another objectRepeat above procedure for another object

EXAMPLEEXAMPLE

Main PCMain PC

Select SituationSelect Situation– The situation in which the game is about to startThe situation in which the game is about to start

Command Command – Click ‘Ready’: the vision system starts finding the Click ‘Ready’: the vision system starts finding the

objects objects

on the fieldon the field– Click ‘Start’ : the vision system starts sending Click ‘Start’ : the vision system starts sending

commandscommands

to the robotsto the robots– Click ‘Stop’ : the vision system stops finding objectsClick ‘Stop’ : the vision system stops finding objects

and sending commandsand sending commands

EXAMPLEEXAMPLE

Communication (Infra-Communication (Infra-red)red)

Infra-red CommunicationInfra-red Communication

– Four transmitters are used to cover the whole Four transmitters are used to cover the whole fieldfield

t

Transmitter

Receiver

t

r, : View angle

r

130cm0,0cm

35cm,35cm

15

0cm

X

Y

35cm,95cm

115cm,35cm 115cm,95cm

EXAMPLEEXAMPLE

CommunicationCommunication Both teams share the same transmitter via a Both teams share the same transmitter via a

mediatormediator

Communication PacketCommunication Packet

– Three 0xFFs: the start of a packetThree 0xFFs: the start of a packet– 0x0F (0xF0): Team A (Team B)0x0F (0xF0): Team A (Team B)

– VVLi Li ,, VVRiRi: left and right wheel velocity of robot i: left and right wheel velocity of robot i

– 0xAA: end of velocity data of each robot0xAA: end of velocity data of each robot

0xFF 0xFF 0xFF 0x0F 0xAA 0xAA 0xAA1LV 1RV 2LV 3LV2RV 3RV

TransmitterPC 1 (Team A) PC 2 (Team B)

Infra-redmodule

EXAMPLEEXAMPLE

Tough, practical problems Tough, practical problems to be solvedto be solved

Real-TimeReal-Time image processing image processing Sensor fusionSensor fusion (sonar, touch, vision, (sonar, touch, vision,

light, other). light, other). Motors, batteries. Motors, batteries. Sophisticated Sophisticated control strategiescontrol strategies RadioRadio communication communication AgentAgent communication communication

Problems Problems

Players do not know Players do not know absolute absolute locationslocations. .

Points of referencePoints of reference are: are: boundaries, lines and gates.boundaries, lines and gates.

Conflicts Conflicts of playersof players Limited Limited visibilityvisibility Limited Limited communicationcommunication

SoftwareSoftware Real-TimeReal-Time Problem, Problem, rule-basedrule-based, ,

agent agent behavior.behavior. DynamicDynamic planning and executionplanning and execution of of

plans in real-time.plans in real-time. Cooperation and competition.Cooperation and competition. No precise informationNo precise information Non-deterministicNon-deterministic behavior: behavior:

– results of actions are uncertain.results of actions are uncertain.

Software potentials Software potentials (cont.)(cont.)

Voice Voice comunication of playerscomunication of players Various players have different rules Various players have different rules

and behaviors, different strategies and and behaviors, different strategies and implementations - implementations - rule-based, neural rule-based, neural nets, fuzzy logic, etc.nets, fuzzy logic, etc.

multi-agents:multi-agents: competition versus competition versus collaboration. collaboration.

on-lineon-line versus versus off-lineoff-line, , individualindividual versus versus group behaviors.group behaviors.

FIRA and the FIRA and the ECE 478/ECE 479 class at ECE 478/ECE 479 class at

PSUPSU

Class project and in future Capstone Class project and in future Capstone Project (if a company will sponsor)Project (if a company will sponsor)

High-School projectHigh-School project Portland Cyber TheatrePortland Cyber Theatre Experience in Visual C++, Basic, Lisp Experience in Visual C++, Basic, Lisp

and Prolog programming.and Prolog programming. A lot of fun.A lot of fun. Travel to Japan or Korea?Travel to Japan or Korea?

Does PSU team has a Does PSU team has a chance?chance?

1. Professor Kim from KAIST in Korea 1. Professor Kim from KAIST in Korea invited us to create a new league of invited us to create a new league of walking robotswalking robots

2. 2. We have experience with walking We have experience with walking robotsrobots

3. We will try to propose new 3. We will try to propose new competition ideas and have a leverage competition ideas and have a leverage of knowing them earlier.of knowing them earlier.– Besides, our students are smart…..?Besides, our students are smart…..?

Let us look to our robots…...

What we What we proposepropose

Robot soccer systemRobot soccer system– Intelligent control Intelligent control

systemsystem– Multi-agent systemMulti-agent system

Composition of robot soccer Composition of robot soccer systemsystem– Mobile robotsMobile robots– Host computerHost computer– Vision systemVision system– Communication moduleCommunication module

Sports commentator

Walking robots

Team OneTeam One

Complex robotsComplex robots 8 to 12 servos8 to 12 servos

Our walking quadrupeds and Our walking quadrupeds and hexapodshexapods

Collaborations:

ATR, Japan

Technical University of Warsaw, Poland

Technical University of Gliwice, Poland

KAIST, Korea

Multi-national team

QuadrupeQuadruped d

Basic Radio-Controlled Basic Radio-Controlled Spider HexapodSpider Hexapod with Gripper with Gripper

Spider with a cameraSpider with a camera

New soccer-specialized New soccer-specialized hexapodhexapod

Hexapod’s Soccer Hexapod’s Soccer KickerKicker

Team TwoTeam Two

Simple robots - hexapodsSimple robots - hexapods 2 servos2 servos

SoccerBotSoccerBot

Final design of a quadruped Final design of a quadruped walkerwalker

Block Diagram of the Block Diagram of the Simple Robot SystemSimple Robot System

Logic Power

PWM RightPWM Left

MotorDriver

MotorDriver

Motor Motor

VoltageRegulator

MotorPower

Micro-Controller

Battery

Communication Signal

CommunicationModule

Motor Part

Sport Sport CommentatorsCommentators

Bug

Virginia WoolfVirginia Woolf

JonasJonas

Marvin the Crazy Marvin the Crazy RobotRobot

Class Projects - Class Projects - Winter/Spring 2002Winter/Spring 2002

1. 1. Robot Robot position, orientation and conflict position, orientation and conflict detection using top-mounted cameradetection using top-mounted camera

2. 2. Ball recognitionBall recognition and vision interface to and vision interface to the serverthe server

3. Server and user interface3. Server and user interface 4. Egoistic soccer-playing strategy4. Egoistic soccer-playing strategy 5. 5. CollaborativeCollaborative soccer-playing strategy soccer-playing strategy 6. Recovery from body conflicts such as 6. Recovery from body conflicts such as

leg entanglementsleg entanglements of robots of robots

Class Projects - Class Projects - Winter/Spring 2002Winter/Spring 2002

7. Design of robo-head sport 7. Design of robo-head sport commentator: speech and natural commentator: speech and natural language generation.language generation.

8. Mechanical improvements to 8. Mechanical improvements to robotsrobots

9. Design of a special soccer player 9. Design of a special soccer player hexapod.hexapod.

Image Processing: find position, orientation and conflicts of a walker

Filtering, histogramming, Hough transform, equations

Localization, orientation, conflicts (leg entanglements)

Robo Soccer - Why is it Robo Soccer - Why is it so cool? so cool?

Is Robot Soccer useful?Is Robot Soccer useful? Is the result of Robot Soccer useful?Is the result of Robot Soccer useful? Is Robot Soccer the worlds largest Is Robot Soccer the worlds largest

playground?playground? Is there money to be made with Is there money to be made with

robots to play sports? robots to play sports?

Why are Robot Sports so Why are Robot Sports so cool? cool?

Captures the Captures the essence of socceressence of soccer. (That’s . (That’s why there can be a lot of people cheering why there can be a lot of people cheering on the teams)on the teams)

””Hacker-party”Hacker-party” more than a dull more than a dull academic conference….that is, it is a lot of academic conference….that is, it is a lot of activity.activity.

Interesting problem in Interesting problem in co-ordinatingco-ordinating 11 11 processes to achieve a common goal.processes to achieve a common goal.

The The width of the fieldwidth of the field, from Robotic-, from Robotic-nerds to Sociologists.nerds to Sociologists.

In the simulator league, you are In the simulator league, you are forced to forced to learnlearn many concepts: many concepts:– for example for example network communication, multi-network communication, multi-

threadingthreading, agents, hardware, etc., agents, hardware, etc.

TestbedTestbed for AI-algorithms, sociological for AI-algorithms, sociological theories. theories.

Fairly Fairly simplesimple environment. environment. A limited set of rules (also predefined), A limited set of rules (also predefined),

but always but always closeclose to real world to real world problems.problems.

Why are Robot Sports so Why are Robot Sports so cool? cool?

What are the problems with What are the problems with Robot Competitions ? Robot Competitions ?

Too much work Too much work before reachingbefore reaching an an interesting research levelinteresting research level

Too much focus on Too much focus on low levellow level implementation (still)implementation (still)

Still Still focus on competingfocus on competing instead of instead of comparing of strategies.comparing of strategies.

ResearchResearch

We do research in several areas:We do research in several areas:– Machine learning (constructive induction)Machine learning (constructive induction)– Decision theory Decision theory – Social agents Social agents – walker’s gaits evolutionwalker’s gaits evolution– +more+more

In all of the above we plan to use robot In all of the above we plan to use robot sports as a testbed, or applied area.sports as a testbed, or applied area.

ConclusionConclusion

Robot sports areTHE Robot sports areTHE new standardnew standard problem within AI.problem within AI.

1500 researchers1500 researchers world-wide. world-wide. Focuses on interdisciplinary co-Focuses on interdisciplinary co-

operative work between the operative work between the researchers as well as co-operation researchers as well as co-operation between the agents.between the agents.

NewNew experience experience for for PSUPSU

Current classCurrent class 4 ME students4 ME students 3 CS students3 CS students 3 EE students3 EE students

Using existing robots CS and EE students develop software

ME students develop 2 new robot prototypes and kits with good documentation

CS and EE students build new robots from kits ME students adopt software to

new robots and learn programming

6 robots of two types build and tested in July

Current classCurrent class 4 ME students4 ME students 3 CS students3 CS students 3 EE students3 EE students

Using existing robots CS and EE students develop software

ME students develop 2 new robot prototypes and kits with good documentation

CS and EE students build new robots from kits ME students adopt software to

new robots and learn programming

6 robots of two types build and tested in July

Technical Publications Technical Publications Hiroaki Kitano, Masahiro Fujita, Stephane Zrehen , and Koji Hiroaki Kitano, Masahiro Fujita, Stephane Zrehen , and Koji

Kageyama, "Sony Legged Robot for RoboCup Challenge", Kageyama, "Sony Legged Robot for RoboCup Challenge", – In Proceedings of the IEEE INTERNATIONAL CONFERENCE ON In Proceedings of the IEEE INTERNATIONAL CONFERENCE ON

ROBOTICS AND AUTOMATION, IEEE, 1998, pp.2605-2612 ROBOTICS AND AUTOMATION, IEEE, 1998, pp.2605-2612 Manuela Veloso, William Uther, Masahiro Fujita, Minoru Manuela Veloso, William Uther, Masahiro Fujita, Minoru

Asada, and Hiroaki Kitano, "Playing Soccer with Legged Asada, and Hiroaki Kitano, "Playing Soccer with Legged Robot", Robot", – In Proceedings of the INTERNATIONAL CONFERENCE ON In Proceedings of the INTERNATIONAL CONFERENCE ON

INTELLIGENT ROBOTS AND SYSTEMS, 1998, pp.437-442 INTELLIGENT ROBOTS AND SYSTEMS, 1998, pp.437-442

Let us go deeperLet us go deeper

How to find more How to find more about RoboCup?about RoboCup?

Web Pages:Web Pages:

http://medialab.di.unipi.it/Project/http://medialab.di.unipi.it/Project/RobocupRobocup

http://www.robocup.orghttp://www.robocup.org http://www.dsv.su.se/~robocuphttp://www.dsv.su.se/~robocup