Hierarchical Representations and Explicit Memory: Learning Effective Navigation Policies on 3D Scene Graphs using Graph Neural Networks
Zachary Ravichandran,Lisa Peng,Nathan Hughes,J. Daniel Griffith,Luca Carlone,Zachary Ravichandran,Lisa Peng,Nathan Hughes,J. Daniel Griffith,Luca Carlone
Representations are crucial for a robot to learn effective navigation policies. Recent work has shown that mid-level perceptual abstractions, such as depth estimates or 2D semantic segmentation, lead to more effective policies when provided as observations in place of raw sensor data (e.g., RGB images). However, such policies must still learn latent three-dimensional scene properties from mid-leve...
