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.
Two-stage reinforcement learning for planetary rover navigation: Reducing the reality gap with offline noisy data,
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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.