Home /Research /AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos
OTHER

AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos

Laura Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine

Year
2020
Citations
31
Access
Open access

Abstract

Fig. 1: Left: Human instructions for each stage (top) are translated at the pixel level into robot instructions (bottom) via CycleGAN. Right: The robot attempts the task stage-wise, automatically resetting and retrying until the instruction classifier signals success, prompting the human to confirm via key press. Algorithmic details are provided in Algorithm 1.

Keywords

Computer scienceRobotArtificial intelligenceTask (project management)Process (computing)Reinforcement learningComputer visionHuman–robot interactionConstruct (python library)Robot learning

Related papers

Browse all OTHER papers