EFGCL adds external assistive forces during RL training to let legged robots physically experience successful dynamic motions early, accelerating learning of jumps and flips by about 2x and enabling behaviors conventional methods cannot acquire.
Learning agile and dynamic motor skills for legged robots
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
GeAN learns actuator dynamics from position trajectories to enable successful sim-to-real transfer of goal-reaching and ball-in-a-cup policies on a 4-DoF pneumatic muscle-actuated robot, reported as the first such transfer for this system type.
citing papers explorer
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EFGCL: Learning Dynamic Motion through Spotting-Inspired External Force Guided Curriculum Learning
EFGCL adds external assistive forces during RL training to let legged robots physically experience successful dynamic motions early, accelerating learning of jumps and flips by about 2x and enabling behaviors conventional methods cannot acquire.
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Sim-to-Real Transfer for Muscle-Actuated Robots via Generalized Actuator Networks
GeAN learns actuator dynamics from position trajectories to enable successful sim-to-real transfer of goal-reaching and ball-in-a-cup policies on a 4-DoF pneumatic muscle-actuated robot, reported as the first such transfer for this system type.