Domain Randomization The Reality Gap Visual Narrative

Summary

Learn how to build policies that generalize across physical variations without ever touching a real robot during training. We dive ... To help make deep learning more accessible, researchers from NVIDIA have introduced a structured Course Instructor: Pieter Abbeel Guest Lecturer: Josh Tobin Course Website: ... Master Domain Randomization (DR) to make your reinforcement learning and imitation policies robust against real-world chaos ... On our approach to randomizing objects, texture and other scene components within the realistic values. In this series, we explore using reinforcement learning algorithms (RL) to have a robot learn to balance on its own. We will deploy ... Authors: Raghad Alghonaim and Edward Johns Institution: The Robot Learning Lab at Imperial College London Website: ... Talk at Deep Learning for Action and Interaction, NIPS 2016, explaining method and results of "CAD2RL: Real Single-Image ... Discover why reinforcement learning policies trained in simulation often fail miserably when tested on physical hardware.