A decomposed adversarial imitation learning framework with a unified digital human prototype transfers human loco-manipulation skills across five simulated humanoid robots, reducing per-robot training time.
Real-world humanoid locomotion with reinforcement learning,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.RO 1years
2024 1verdicts
CONDITIONAL 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
Human-Humanoid Robots Cross-Embodiment Behavior-Skill Transfer Using Decomposed Adversarial Learning from Demonstration
A decomposed adversarial imitation learning framework with a unified digital human prototype transfers human loco-manipulation skills across five simulated humanoid robots, reducing per-robot training time.