Foundation models in robotics: Applications, challenges, and the future

R Firoozi, J Tucker, S Tian… - … Journal of Robotics …, 2023 - journals.sagepub.com
We survey applications of pretrained foundation models in robotics. Traditional deep
learning models in robotics are trained on small datasets tailored for specific tasks, which …

Conceptgraphs: Open-vocabulary 3d scene graphs for perception and planning

Q Gu, A Kuwajerwala, S Morin… - … on Robotics and …, 2024 - ieeexplore.ieee.org
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 …

Benchmarking neural radiance fields for autonomous robots: An overview

Y Ming, X Yang, W Wang, Z Chen, J Feng… - … Applications of Artificial …, 2025 - Elsevier
Abstract Neural Radiance Field (NeRF) has emerged as a powerful paradigm for scene
representation, offering high-fidelity renderings and reconstructions from a set of sparse and …

On bringing robots home

NMM Shafiullah, A Rai, H Etukuru, Y Liu, I Misra… - ar**
Y Zheng, X Chen, Y Zheng, S Gu… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Constructing a 3D scene capable of accommodating open-ended language queries, is a
pivotal pursuit in the domain of robotics, which facilitates robots in executing object …

Physical property understanding from language-embedded feature fields

AJ Zhai, Y Shen, EY Chen, GX Wang… - Proceedings of the …, 2024 - openaccess.thecvf.com
Can computers perceive the physical properties of objects solely through vision? Research
in cognitive science and vision science has shown that humans excel at identifying materials …

One-shot open affordance learning with foundation models

G Li, D Sun, L Sevilla-Lara… - Proceedings of the IEEE …, 2024 - openaccess.thecvf.com
Abstract We introduce One-shot Open Affordance Learning (OOAL) where a model is trained
with just one example per base object category but is expected to identify novel objects and …