activity
20232026
most citedFoundation Models in Robotics: Applications, Challenges, and the Future

13 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2026

, But Make It Fly: Physics-Guided Transfer of VLA Models to Aerial Manipulation

Johnathan Tucker, Denis Liu, Aiden Swann +7

Vision-Language-Action (VLA) models such as have demonstrated remarkable generalization across diverse fixed-base manipulators. However, transferring these foundation models…

cs.RO2024

E2Map: Experience-and-Emotion Map for Self-Reflective Robot Navigation with Language Models

Chan Kim, Keonwoo Kim, Mintaek Oh +10

Large language models (LLMs) have shown significant potential in guiding embodied agents to execute language instructions across a range of tasks, including robotic manipulation an…

cs.RO2024

Splat-MOVER: Multi-Stage, Open-Vocabulary Robotic Manipulation via Editable Gaussian Splatting

Ola Shorinwa, Johnathan Tucker, Aliyah Smith +5

We present Splat-MOVER, a modular robotics stack for open-vocabulary robotic manipulation, which leverages the editability of Gaussian Splatting (GSplat) scene representations to e…

cs.RO2023★ 13 cited

Foundation Models in Robotics: Applications, Challenges, and the Future

Roya Firoozi, Johnathan Tucker, Stephen Tian +12

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 li…

cs.CV2023

Aria-NeRF: Multimodal Egocentric View Synthesis

Jiankai Sun, Jianing Qiu, Chuanyang Zheng +3

We seek to accelerate research in developing rich, multimodal scene models trained from egocentric data, based on differentiable volumetric ray-tracing inspired by Neural Radiance…