A Few Shot Adaptation of Visual Navigation Skills to New Observations using Meta-Learning

Qian Luo, Maks Sorokin, Sehoon Ha

The IEEE International Conference on Robotics and Automation (ICRA) 2021

Abstract

We show how vision-based navigation agents can be trained to adapt to new sensor configurations with only three shots of experience. Rapid adaptation is achieved by introducing a bottleneck between perception and control networks, and through the perception component's meta-adaptation.