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as a test bed for Measuring 

Performance

Minoru Asada

Adaptive Machine Systems

Osaka University, JAPAN

August 13th, 2002

PerMIS-02@NIST

nations around world, and about 1000 

media people.

 About 120,000 visitors during one press d

and four open public days

 The first humanoid robot league

 13 teams from 6 nations

 ROBOTREX (Robot Trade & 

Exhibitions)

 50 companies, universities, and institutes

Outline of my talk

 RoboCup

 Purpose, Current State, and Issues.

 Technological issues towards 

finial goal: Humanoid league

 Levels of autonomy

 One leg standing, walk, PK, 

and free style

 Future issues

What’s RoboCup?

An attempt to foster intelligent robotics 

research by providing a standard problem

Video Clips What’s RoboCup?
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0

20

40

60

80

100

120

140

1997 1998 1999 2000-

Euro

2000-Mel 2001-

Seattle

2002-

Fukuoka

Humanoid

4-legged

Sim

F2000

F180

Why RoboCup? (I) Why RoboCup? (I)

 Landmark Project:

 to set a goal high enough so that a series of 

technical breakthroughs is necessary to 

accomplish the task

 this set of technologies should form the 

foundation of a next generation of industries

 widely appealing and exciting

Ultimate Goal Æ

To beat the human world cup champion 

team by a team of 11 humanoids

Why RoboCup? (II) Why RoboCup? (II)

 Standard Problem:

 a systematic approach to promote research 

using common domain, soccer!

 Comparison with “Chess Problem”

Chess RoboCup

Environment Static Dynamic

State Change Turn taking Real time

Info. accessibility Complete Incomplete

Sensor Readings Symbolic Non-symbolic

Control Central Distributed 

Research Issues in RoboCup (I) Research Issues in RoboCup (I)

 Mechanical design for individual 

robots

 Robust Sensing, especially, vision 

(object discrimination and tracking)

 Self-localization and map building

 Control Architecture

 Communication

Research Issues in RoboCup (II) Research Issues in RoboCup (II)

 Multi-agent systems in general

 Behavior learning for complex tasks

 Combining reactive and modeling 

approaches

 Real-time recognition, reasoning, plann

and action execution in a dynamic 

environment

 Cross modal association (Sensor fusion) 

 Strategy acquisition

 Cognitive modeling in general
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 Simulation: Coach, Visualization

 Real robot: Small, Middle, Legged, 

and Humanoid

 RoboCupRescue

 Simulation and real robot

 RoboCupJunior

 Soccer, Dance, and Rescue

ow cos, Saa ode, v.s. , 

perception, broadcasting

 Secondary Domain ÆRoboCup-Res

Soccer 

Simulation 

League

 Teamwork

 On-line learning

 Coach 

competition

 Visualization

Real Robot Leagues

 Small Size league: A table tennis table, an 

orange golf ball, and global vision..

 Middle Size league: 3X3 table tennis tables

official soccer ball, and local vision..

Real Robot Leagues (cntd.)

 Legged league: Sony AIBO Type robots, 4 on 4.

 Humanoid league: Four classed according to 

the size. One leg standing, walk, PK, and free 

style

Small-size league

 1997~ Global vision:

 Perception: Sharing 

global information Æ

reliable and real-time 

detection of multi 

mobile robots and ball.
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g

the filed to encourage 

the team plays.

 Evolution from 

individual behavior to 

team plays.

Middle-size league (cntd.)

 Global reconstruction by LRFs (C. S. Freiburg, 

Germany)  1997~ 5 on 5 Footsul-4 ball

 2000~ 4 on 4 Footsul-5 (official ball)

 Omni-directional vision, Reactive behavior, 

and social ones.

Middle-size league (cntd.)

Middle-size league (cntd.)

 Holonomic Vehicles: 

Omni-directional 

movement

Middle-size league (cntd.)

 2002~ No walls

 Quick motions

 Team plays
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 1998:exhibition (Osaka U.,CMU,ParisVI )

 1999~:Official league (2m×3m,3 on 3)

 computer

 actuator

 mechanism

Legged league (cntd.)

 Various kinds of behaviors: Ball handling

 Teamwork: social behavior based on 

vocal communication

Legged league (cntd.)

 2001~: New platform

 2002~:3m×4m,4 on 4,wireless 

communication

Humanoid league

 2002: the first humanoid robot soccer.

 4 kinds of size:40cm,80cm,120cm,180cm

 Perfomance factor towards fully autonomous 

humanoid robot: Platform, power supply from 

outside, remote brain, human control

 Japan (5), Sweden (3), Singapore (2), New 

Zealand, Australia, Denmark

Why humanoid robot?

 One extreme application: test-bed 

for brain science.

 Current application: 

entertainment, pet robots.

 Another extreme application: 

practical use in our daily life??? Æ

HRP by Japanese government.
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running, turning, jumping,.....

 Cognitive performance: object 

recognition/tracking

 Combined behaviors: object following, 

object avoidance, kicking a 

stationary/moving ball,...

 Auditory system, planning Æ Future

Benchmark for the humanoid league 

[Kitano & Asada 98] Standard Components 

and Software Resources

 OpenR: Open Architecture 

for High DOFs and Sensors.

OpenR SDK (June, 2002)

 Humanoid Robot Project 

supported by Japanese 

government

HRP robot (Honda P3-base)

HRP 2 robot (original) Æ

Perfomance Factor

 We would like to trigger developments towards fully 

autonomous self-build humanoid robots.

 Therefore, we took so-called performance factors for 

the different dimensions with regard to autonomy.

1. external power cord

2. computer outside robot

3. remote control

4. Platform

 1.2 is assigned for each item and if more then one is 

applicable then they are multiplied (1.2, 1.44, 1.728, 

2.0736). 

Perfomance Factor (cntd.)

 These factors were either used

1. as penalty factor in the walking the time t

was multiplied by them or 

2. as handicap (in penalty kiccking the score 

divided by them). 

 They are working quite well (with regard 

the above stated intention) and will certai

prefer the more autonomous robots but w

also allow for semi-autonomous ones if th

performance is much better then that of t

autonomous ones. No changes needed.
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ts. t was doe uuoa by asg eveybody 

the audience to perform this challenge together with 

the robots.

penalty which is linearly increasing: 20 sec/1st 

touch, 40 sec/2nd touch, 60 sec/3rd touch etc. 

 Champion:

 Nagara (Japan) 

 81,64, and 61 seconds 

 3.29 (p/f: 1.0)

 Second:

 Robo-Erectus (SG)

 209, 109, and 183 secs.

 4.932 (p/f: 1.2)

Challenges: Penalty kick  Total behavior coordination with walking, one leg 

standing, kicking, and balancing.

 The physical height of the striking robot was used to 

determine the distance between ball and striker 

while the measurements of the goals were only 

available for the two categories (40 cm and 80 cm 

height). 

Challenges: Penalty kick (cnt

 First, to give the striker a realistic chance we 

introduced a 5 sec latency after the starting whist

before the goalie may start to walk towards the ba

reduce the angle which could be used to score a go

 Second, the line of the goal area was used a strict 

demarcation line to avoid the collision. 

 The was so light that it often went astray due to sm

uneven parts in the field.

Challenges: Penalty kick (cntd.)  First, to give the striker a realistic chance we 

introduced a 5 sec latency after the starting whistle 

before the goalie may start to walk towards the ball to 

reduce the angle which could be used to score a goal. 

 Second, the line of the goal area was used a strict 

demarcation line to avoid the collision. 

 The was so light that it often went astray due to small 

uneven parts in the field.

Challenge: free style

 Honda Asimo’s example performan

and digest from humanoid league.
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Sad ooe eg: dcuo decde ea

sensor feedback or open loop. Introduction 

disturbance to check it.

 PK: from PK to 2 on 2!

 Free style: A test bed for humanoid researc

general

Materials and Basic 

Components

 Surface Materials

Soft, Embedded-sensory systems

 Frame Materials

Light Weight

 Power Supply

45 min x 2 + PK, etc.

Weights and Safety

 Energy Saving Architecture

Materials and Basic 

Components

 Actuation Systems

Current Motor-Gear system is too 

fragile

Robust Parallel System is necessary

Artificial Muscle

 Mechanical Design

Joint systems, etc.

Totally new design?

Basic Control Issues

 High Performance Mobility

Basic Walking is accomplished

Run and Jump

 Behavioral Robustness

Can it safely fell down and stand 

up again?

 Behavioral Complexity

Sensory Systems

 Vision and Touch

 Auditory System

 Other Sensing Systems

 Sensor-Fusion

 Sensory-Motor Integration
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 Strategy Planner

 Learning

 Brain and Cognitive Science

got wins from human teams since 19

 Small size league: Human won until 

1998, but no more since 1999. 

 Sony AIBO league: robot team won!

 But, human teams have not got used 

operate robots. What happened if th

learned more?

RoboCupRescue Simulation

500 x 500 m region in 

Nagata Ward, Kobe City 

Multi-layered human interface

with information filtering

RoboCupRescue Simulation (cntd

RoboCupRescue Real robot

 Evaluation of 

cooperation 

deployed in three 

stage rescue 

situations by NIST

RoboCupJunior
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 Humanoid league: regulations

Padua, Italy

 July, 2004: The eighth RoboCup at 

Lisbon, Portugal 

Acknowledgement

 RoboCup Federation,

 NPO RoboCup Japanese Committee

 Humanoid Chair: Prof. Dr. Thomas Christaller

http://www.robocup.org/