Recent efforts have augmented large language models (LLMs) with external resources (eg,
the Internet) or internal control flows (eg, prompt chaining) for tasks requiring grounding or …

Large language models (LLMs) exhibit a wide range of promising capabilities--from step-by-
step planning to commonsense reasoning--that may provide utility for robots, but remain …

In this work, we address challenging multi-agent cooperation problems with decentralized
control, raw sensory observations, costly communication, and multi-objective tasks …

Abstract 3D vision-language grounding (3D-VL) is an emerging field that aims to connect the
3D physical world with natural language, which is crucial for achieving embodied …

The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …

Embodied AI aims to create agents that complete complex tasks by interacting with the
environment. A key problem in this field is embodied navigation which understands multi …

Recent research in language-guided visual navigation has demonstrated a significant
demand for the diversity of traversable environments and the quantity of supervision for …

We present Habitat 3.0: a simulation platform for studying collaborative human-robot tasks in
home environments. Habitat 3.0 offers contributions across three dimensions:(1) Accurate …

Large Language Models (LLMs) have the capacity of performing complex scheduling in a
multi-agent system and can coordinate these agents into completing sophisticated tasks that …

HomeRobot (noun): An affordable compliant robot that navigates homes and manipulates a
wide range of objects in order to complete everyday tasks. Open-Vocabulary Mobile …