Active simultaneous localization and map** (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …

Scene graph is a structured representation of a scene that can clearly express the objects,
attributes, and relationships between objects in the scene. As computer vision technology …

For robots to perform a wide variety of tasks, they require a 3D representation of the world
that is semantically rich, yet compact and efficient for task-driven perception and planning …

Large language models (LLMs) have unlocked new capabilities of task planning from
human instructions. However, prior attempts to apply LLMs to real-world robotic tasks are …

Computer vision now relies on data, but we know surprisingly little about what factors in the
data affect performance. We argue that this stems from the way data is collected. Designing …

We present a scalable approach for learning open-world object-goal navigation (ObjectNav)–
the task of asking a virtual robot (agent) to find any instance of an object in an unexplored …

3D scene graphs have recently emerged as a powerful high-level representation of 3D
environments. A 3D scene graph describes the environment as a layered graph where …

This work studies the problem of object goal navigation which involves navigating to an
instance of the given object category in unseen environments. End-to-end learning-based …

How does language inform our downstream thinking? In particular, how do humans make
meaning from language--and how can we leverage a theory of linguistic meaning to build …