A last-mile navigation module that connects to prior policies, leading to improved image-goal navigation results in simulation and real-robot experiments.
In this work we develop a gradient-based meta-learning algorithm for efficient, online continual learning, that is robust and scalable to real-world visual benchmarks.
In this work, we develop a novel formulation based on Reinforcement Learning that generates fail safe trajectories while using Monocular SLAM for localization.