Getting robots to navigate to multiple objects autonomously is essential yet difficult in robot
applications. One of the key challenges is how to explore environments efficiently with …

This paper presents a novel approach for the Vision-and-Language Navigation (VLN) task in
continuous 3D environments, which requires an autonomous agent to follow natural …

Embodied AI agents in large scenes often need to navigate to find objects. In this work, we
study a naturally emerging variant of the object navigation task, hierarchical relational object …

Existing deep reinforcement learning-based mobile robot navigation relies largely on single-
modal visual perception to perform local-scale navigation. However, multimodal visual …

Multisource fusion localization is a mainstream scheme for acquiring accurate locations in
complex indoor scenes. To overcome the interference of indoor structures on radio and …

Understanding the geometric relationships between objects in a scene is a core capability in
enabling both humans and autonomous agents to navigate in new environments. A sparse …

The Embodied AI is the current frontier direction in the field of AI and is regarded as a
research leading to general artificial intelligence. Embodied AI refers to the study and …

Future Moon bases will likely be constructed using resources mined from the surface of the
Moon. The difficulty of maintaining a human workforce on the Moon and communications lag …

In this paper, we introduce the map-language navigation task where an agent executes
natural language instructions and moves to the target position based only on a given 3D …

Recent advances in deep learning have led to a data-centric intelligence ie artificially
intelligent models unlocking the potential to ingest a large amount of data and be really …