Building a Robot Soccer Team David Cohen and Paul Vernaza University of Pennsylvania.
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Transcript of Building a Robot Soccer Team David Cohen and Paul Vernaza University of Pennsylvania.
![Page 1: Building a Robot Soccer Team David Cohen and Paul Vernaza University of Pennsylvania.](https://reader036.fdocuments.in/reader036/viewer/2022062407/56649dff5503460f94ae6e98/html5/thumbnails/1.jpg)
Building a Robot Soccer Team
David Cohen and Paul Vernaza
University of Pennsylvania
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What is Robocup? International robotics competition
and symposium Goal: By the year 2050,
to develop a team of fully autonomous humanoid robots that can win against the human world soccer champion team.
Many different leagues in competition
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The Four-Legged League Team composition Rules Field Uniforms Ball Halves Challenges Robots used…
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The Sony AIBO
“Robotic Pet”/research platform Construction (deconstruction) Battery, memory stick, wireless
card Sensors, effectors What kinds of sensors and
effectors are present on the AIBO?
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Major Challenges
Can you guess what the major challenges are?
We will talk about four of them…
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Major Challenges
Vision: making sense of the camera image
Localization: finding out where the dogs are located on the field
Locomotion: teaching a dog to walk Behavior: decision-making and
cooperation
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Vision
1. Build a color table2. Convert image pixels to distinct
colors3. Connect the dots to make blobs
Images courtesy of CMU
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Localization
What does it give us? Why localization? Humans don’t
have it Beacon-based localization Line-based localization
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Locomotion A good walk is omnidirectional,
fast, and stable Teams differ greatly in locomotive
ability Being able to walk fast gives a
team a great advantage Walk is generated using inverse
kinematics
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Behavior Consists basically of
telling the dog what to do in different circumstances
Fully autonomous Modeled with a state
machine Important issues include
collaboration, obeying rules, robustness
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Robocup 2003 Penn finished 2nd out
of 24 teams Teams from around
the world participated Each team had its
own characteristic strengths and weaknesses (UNSW, Germany, U. of Washington, etc.)
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Plans for the Future New robots: ERS-7 Improving walk speed Improving localization
with more natural visual cues
Using AI techniques for behavior
Passing