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

13 citations · 14 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.RO2026

DreamControl-v2: Simpler and Scalable Autonomous Humanoid Skills via Trainable Guided Diffusion Priors

Sudarshan Harithas, Sangkyung Kwak, Pushkal Katara +6

Developing robust autonomous loco-manipulation skills for humanoids remains an open problem in robotics. While RL has been applied successfully to legged locomotion, applying it to…

cs.RO2025

DreamControl: Human-Inspired Whole-Body Humanoid Control for Scene Interaction via Guided Diffusion

Dvij Kalaria, Sudarshan S Harithas, Pushkal Katara +7

We introduce DreamControl, a novel methodology for learning autonomous whole-body humanoid skills. DreamControl leverages the strengths of diffusion models and Reinforcement Learni…

cs.RO2024

Logically Constrained Robotics Transformers for Enhanced Perception-Action Planning

Parv Kapoor, Sai Vemprala, Ashish Kapoor

With the advent of large foundation model based planning, there is a dire need to ensure their output aligns with the stakeholder's intent. When these models are deployed in the re…

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.RO2023★ 1 cited

GRID: A Platform for General Robot Intelligence Development

Sai Vemprala, Shuhang Chen, Abhinav Shukla +2

Developing machine intelligence abilities in robots and autonomous systems is an expensive and time consuming process. Existing solutions are tailored to specific applications and…