Media Summary: K. Zhang, F. Niroui, M. Ficocelli and G. Nejat, “Robot We propose a model-based reinforcement learning approach for robust and adaptive long-horizon Walking safely in complex and possibly dangerous
Rough Terrain Navigation Using Divergence - Detailed Analysis & Overview
K. Zhang, F. Niroui, M. Ficocelli and G. Nejat, “Robot We propose a model-based reinforcement learning approach for robust and adaptive long-horizon Walking safely in complex and possibly dangerous We present a novel method for reliable robot A Sim-to-Real Pipeline for Deep Reinforcement Learning for Autonomous Robot Learning-based Uncertainty-aware Navigation in 3D Off-road Terrains
L. Nardi and C. Stachniss, “Actively Improving Robot
![Rough Terrain Navigation Using Divergence Constrained Model-Based Reinforcement Learning [CoRL 2021]](https://i.ytimg.com/vi/Zthy1dZGLHk/mqdefault.jpg)
