Second, the latent space is modeled with a Mixture of Gaussians conditioned on the current observation and next best action.
Underwater robot interventions require a high level of safety and reliability.
Many robotic applications require the agent to perform long-horizon tasks in partially observable environments.
In this paper we study the problem of learning to learn at both training and test time in the context of visual navigation.
We demonstrate the surprising strength of unimodal baselines in multimodal domains, and make concrete recommendations for best practices in future research.
his paper presents a simple approach for drone navigation to follow a predetermined path using visual input only without reliance on a Global Positioning System (GPS).
Recent efforts on training visual navigation agents conditioned on language using deep reinforcement learning have been successful in learning policies for two different tasks: learning to follow navigational instructions and embodied question answering.