PAPL uses phase-conditioned FiLM layers in RL networks to create a unified policy for quadruped robots to ride skateboards by capturing phase-dependent behaviors while sharing knowledge across phases.
Learning belief representations for imitation learning in pomdps
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Phase-Aware Policy Learning for Skateboard Riding of Quadruped Robots via Feature-wise Linear Modulation
PAPL uses phase-conditioned FiLM layers in RL networks to create a unified policy for quadruped robots to ride skateboards by capturing phase-dependent behaviors while sharing knowledge across phases.