Guided RL using Bezier curves and UARM model enables efficient, explainable omnidirectional jumping in quadruped robots.
Tamols: Terrain-aware motion optimization for legged systems
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Integrating foot position maps into heightmaps and adding a locomotion-stability reward in an attention-based RL framework improves quadrupedal success rates on both trained and out-of-domain complex terrains.
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Guided Reinforcement Learning for Omnidirectional 3D Jumping in Quadruped Robots
Guided RL using Bezier curves and UARM model enables efficient, explainable omnidirectional jumping in quadruped robots.
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Learning Locomotion on Complex Terrain for Quadrupedal Robots with Foot Position Maps and Stability Rewards
Integrating foot position maps into heightmaps and adding a locomotion-stability reward in an attention-based RL framework improves quadrupedal success rates on both trained and out-of-domain complex terrains.