Sports, Simulation, AI and VRMonte Carlo Methods in Computer Simulations

of Complex Systems

NUSTEP Collaboration

FEFU, Vladivostok, Nov.11, 2016How to get Olympic Medals !

But neither Salmon Fishing nor Acorn Collecting Game

in Olympic . . .

National Geographics 2010© Itsu Horiguchi

Otomo Yasuo `Kuma-kun no

Aki’ Fukuin-Kan

2005

NUSTEP Collaboration

T.Asai, T.Hatsuda, R.Himeno, Y.Kawahara, S.Koike, H. Miyachi,

T.Miyosi, A.Molochkov, A.Nakamura, T.Ogi, T.Sakajo, T.Sumiya,

H.Takagi, M.Taki, N.Yamanaka

SportsSimulation Artificial Intelligence

Assimilation Virtual Reality

NUSTEP: Nextgeneration Unified Sport TEchnology Platform

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Leader

Plan of the Talk1. Blind Men touched Part of an Elephant

Sport Measurement Simulation with Assimilation AI (Artificial Intelligence) VR(Virtual Reality)

2. Target Sports Soccer Swimming Judo

3. International ? 4. Discussions

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1.1 Sports Measurement

Motion Capture

Wind TunnelAcceleration Meter

4

Water Tunnel

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1.2 Simulations

Men’sJumper� Women’sJumper�

Crosssec0on�Velocity,Surface:Pressure�

Latesepara0on

Earlysepara0on

FTFCE

FPE

(tendon)

(PE)

q

(CE)

αlT lMTC

lCE

FTFCE

FPE

(tendon)

(PE)

q

(CE)

αlT lMTC

lCE

Computational Fluid Dynamics

Modeling of Tendon-Frame5 /19

1.2 (Continue) Simulations+Assimilation

Assimilation? Cultural Assimilation?

All animals should eat Salmon !

Weather Forecast Mountain Fire

Rouchoux et al., 2014

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Data AssimilationSimulation + Real Measurement Data

Objective 1

Improvement of Simulation with the help of Real data.

Objective2

Compliment un-observed parts of data by physical

Simulation

Most Probable

Observed data

Different Initial/Boundary Conditions

K.Hosokawa, MTI-Handbook 7 /19

Tools for Data Assimilation

1. (Physical) Simulation Model

2. Measurement data

3. Statistical Science

4. High-performance Computers

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1.3 AI (Artificial Intelligence)

AI coach ?

What does a good coach do ?To know the difference between good and bad performance. (sometimes unconsciously)

Left, Right, Left,,,, Mmm.. Very Bad.

Great Progress mainly due to the Deep Learning.

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Let us find essential differences

between good and bad athletes

CC: j0sh (www.pixael.com)

CC: Agência Brasil

CC: R.H.Sumon

Input many sport measurement data (and data

assimilated simulations)

into AI. Tell me ‘good’ or ‘bad’ for each data.

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https://youtu.be/QZO9juIxptoAut.12, 2016

MIZUNO Corporation+Kawahara+Yamawaki

Expert Standard

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1.4 VR (Virtual Reality) for Educating PlayersMost Important, but most non-trivial parts.

We need more ideas.

We plan to compose a camera-image and VR.

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Play Oppositions in VR.

See one’s real movement and an ideal movement suggested by AI.

See an ideal movement from all direction views using a dataassimilated simulation.

or ..

How to use VR ?

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2.1 Soccer

Many studies in Tsukuba Univ. It includes

a Single Kick, CFD(Computational Fluid Dynamics)

Team Play.

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2.2 Swimming

Movement in the Water introduces new Research Points.

Many Studies in Tsukuba Univ.

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2.3 Judo

Depending Skill of Opponent. Good skill for one Opponent can

be Bad Skill for another.

In case of Soccer and Swimming, Skill is ‘closed’,

but for Judo it is ‘open’.

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3. International Collaboration

It is only for Japanese.

No, No. It is universal !

We want to collaborate with a university/institute out of Japan, to show NUSTEP is universal.

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Best partner ?There are Schools of ‘’Bio-Medicine’’, and “Arts, Culture and Sports’’ at FEFU. A member of NUSTEP, Dr. Yamanaka, is a Post-Doc at FEFU, who is an Asia Champion of Brazilian Jujutsu. with rank of Judo, 2-dan.

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4. Discussions

Now, this is only a Plan or our Dream. But all members believe this is worthwhile to pursue and this opens a new Research field. We appreciate any idea or proposal.

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