1 citations · 2 across the 5 of their papers we have counts for
10 papers
DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos
Shenyuan Gao, William Liang, Kaiyuan Zheng +27
Being able to simulate the outcomes of actions in varied environments will revolutionize the development of generalist agents at scale. However, modeling these world dynamics, espe…
End-to-end RL Improves Dexterous Grasping Policies
Ritvik Singh, Karl Van Wyk, Pieter Abbeel +3
This work explores techniques to scale up image-based end-to-end learning for dexterous grasping with an arm + hand system. Unlike state-based RL, vision-based RL is much more memo…
Deep Sensorimotor Control by Imitating Predictive Models of Human Motion
Himanshu Gaurav Singh, Pieter Abbeel, Jitendra Malik +1
As the embodiment gap between a robot and a human narrows, new opportunities arise to leverage datasets of humans interacting with their surroundings for robot learning. We propose…
Agentic Web: Weaving the Next Web with AI Agents
Yingxuan Yang, Mulei Ma, Yuxuan Huang +15
The emergence of AI agents powered by large language models (LLMs) marks a pivotal shift toward the Agentic Web, a new phase of the internet defined by autonomous, goal-driven inte…
The Sound of Simulation: Learning Multimodal Sim-to-Real Robot Policies with Generative Audio
Renhao Wang, Haoran Geng, Tingle Li +7
Robots must integrate multiple sensory modalities to act effectively in the real world. Yet, learning such multimodal policies at scale remains challenging. Simulation offers a via…
SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending
Yuxuan Kuang, Haoran Geng, Amine Elhafsi +5
Humanoid robots hold significant potential in accomplishing daily tasks across diverse environments thanks to their flexibility and human-like morphology. Recent works have made si…