online control of simulated humanoids using particle belief propagation
TRANSCRIPT
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Online Control of Simulated Hu-manoids Using Particle Belief Propaga-
tion
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Motivation
• Control simulated humanoid• Various movements, environment• Without any pre-computation, motion capture data• At real time
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Simulation Model
: State ( pose and velocity )
: Control. ( Desire joint angle )
Character model ( 15 bones, 30 DOF )
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Objective
( for balancing )
vel : speed of COMcom : horizontal distance of COM from the feety : y position of COM relative to feetfeet : distance between each footw : angular speed of the pelvisup : difference between the pelvis up vector and global up vectorfwd : head facing directiondamage : 10000 if the character’s head touches the environment
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Previous work
Reference Motion
Simula-tion
Fall down
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Previous work
Reference Motion
Change reference motion
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Previous work
Reference Motion
Simula-tion
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Result Control
Simula-tion
Initial Pose
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Result Control
Simula-tion
Initial Pose
Pick best sam-ple
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Result Control
Simula-tion
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Result Control
Simula-tion
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Result Control
Simula-tion
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Result Control
Simula-tion
N : # of samples ( = 32 )
K : Planning horizon ( = 1.2s, 36 time step )
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Simulation Model
: State ( pose and velocity )
: Control. ( Desire joint angle )
Character model ( 15 bones, 30 DOF )
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Sampling
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Resampling
Backwards local refine-ment
Using previous trajectories as a prior
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Probability Model
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Probability Model
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Probability Model
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Control as Markov Random Field
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Belief Propagation
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Particle Belief Propagation
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Particle Belief Propagation
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Particle Belief Propagation
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Result Control
Simula-tion
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Resampling
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Local Refinement
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Operation Over Multiple Frames
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Current Step
Previous Step
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Sampling
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Operation Over Multiple Frames
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Current Step
Previous Step
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Total Algorithm
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