A distilled student policy using monocular depth estimation from cameras outperforms a 2D LiDAR teacher policy in navigating complex 3D obstacles while running fully onboard a Jetson Orin.
Available: https://www.science.org/doi/abs/10.1126/ scirobotics.abk2822
2 Pith papers cite this work. Polarity classification is still indexing.
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A single goal-conditioned RL policy trained on contact plans performs multiple gaits and bimanual manipulation tasks on quadruped and humanoid robots.
citing papers explorer
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Learning Vision-Based Omnidirectional Navigation: A Teacher-Student Approach Using Monocular Depth Estimation
A distilled student policy using monocular depth estimation from cameras outperforms a 2D LiDAR teacher policy in navigating complex 3D obstacles while running fully onboard a Jetson Orin.
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Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning
A single goal-conditioned RL policy trained on contact plans performs multiple gaits and bimanual manipulation tasks on quadruped and humanoid robots.