Terrain-Adaptive Fall Recovery for Wheeled-Quadruped Robots: A Teacher-Guided Learning Framework

Boyuan Deng*, Nikolaos Tsagarakis
Istituto Italiano di Tecnologia

Abstract

We present an optimal posture formulation for robotic recovery on uneven terrain and a novel teacher-student reinforcement learning framework that enables a student policy to infer external terrain conditions using only proprioceptive sensing.

Framework and Fall Simulation


Diverse Terrains Depolyment

We show that our policy performs on the non-flat environments.

Box Grid
Pyramid Slope
Random Rough
Pyramid Stairs
Inverted Pyramid Stairs
Inverted Pyramid Stairs

Bibtex




  

Acknowledgements:

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