Quadruped Robots that Play Soccer

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Quadruped Robots that Play Soccer

• Claude Sammut
• School of Computer Science and Engineering
• The University of New South Wales

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Darren Ibbotson
Son Bao Pham
Bernhard Hengst
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What is RoboCup?
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Four Leagues
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Why make robots play soccer?

• Robots must perceive environment
• Recognise objects
• Form a representation of the world
• Plan and execute actions
• Cooperate with team mates
• Operate in a hostile environment

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The SONY Robots
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Robot Programming
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The Game
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The Teams

• Carnegie-Mellon (USA)
• Essex (UK)
• Humboldt (Germany)
• La Sapienza, Rome (Italy)
• Laboratoire de Robotique de Paris (France)
• Melbourne/RMIT (Australia)
• McGill (Canada)
• Osaka (Japan)
• Pennsylvania (USA)
• Team Sweden (Sweden)
• Tokyo (Japan)
• UNSW (Australia)

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The Scores

• Pool 14 - 0 McGill (Canada)
• QF 11 - 0 Humboldt (Germany)
• SF 12 - 1 CMU (USA)
• F 10 - 0 LRP (France)

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Architecture
Behaviours
Visual objects
Role
Motor positions
Skill
Skill
Skill
Skill
Skill
Skill
Skill
Action Parameters
Robot x,y,q ball x,y
Vision, Object Recognition
Action Head Legs
Localisation
Move x,y,q
Visual Object dist, head
Camera
Motors
Robots, Ball and Soccer Field Environment
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Robot Vision
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Training robots to see colours
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3D YUV Colour Classes
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Colour Calibration
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Object Recognition
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Doggie Cam
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What the robot sees
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World Model
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Localisation
(x, y)
d
New position after taking into account distance
to landmark
h
Current robot position according to world model
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Localisation
(x, y)
d
New position after taking into account distance
to landmark
h
Updated position
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Locomotion
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Turning
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Sideways Walk
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Circling Behaviour
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Conan Strategy
Goalie
Ball Lost
Find Ball
Low CF
Yes
Localise
Yes
No
Low CF
Localise
Forward
Yes
Yes
Find Ball Pos 100,5
Ball Lost
No
No
Ball close
No
Yes
No
follow at 50cm rad from (100,0)
Ball close
Upfield
Ball robot
Downfield
No
Yes
Aligned(R)
Yes
Rob too far
Back-Up
Go Side
Go Behind
Yes
No
Align
Dribble
Butt(R)
Dribble
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Field Regions
6
3
5
4
1
2
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The Arena
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UNSW vs LRP
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(No Transcript)
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2001 a new robot
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Whats next?

• Radio Ethernet Team cooperation
• Learning new behaviours
• Improved colour calibration
• Better robot recognition
• Better dribbling, kicking, walking
• Improve localisation
• Anticipating ball trajectory
• Switching camera resolution
• Force feedback