312 citations · 411 across the 10 of their papers we have counts for
12 papers
MolmoSpaces: A Large-Scale Open Ecosystem for Robot Navigation and Manipulation
Yejin Kim, Wilbert Pumacay, Omar Rayyan +23
Deploying robots at scale demands robustness to the long tail of everyday situations. The countless variations in scene layout, object geometry, and task specifications that charac…
The One RING: a Robotic Indoor Navigation Generalist
Ainaz Eftekhar, Rose Hendrix, Luca Weihs +11
Modern robots vary significantly in shape, size, and sensor configurations used to perceive and interact with their environments. However, most navigation policies are embodiment-s…
PoliFormer: Scaling On-Policy RL with Transformers Results in Masterful Navigators
Kuo-Hao Zeng, Zichen Zhang, Kiana Ehsani +6
We present PoliFormer (Policy Transformer), an RGB-only indoor navigation agent trained end-to-end with reinforcement learning at scale that generalizes to the real-world without a…
Holodeck: Language Guided Generation of 3D Embodied AI Environments
Yue Yang, Fan-Yun Sun, Luca Weihs +11
3D simulated environments play a critical role in Embodied AI, but their creation requires expertise and extensive manual effort, restricting their diversity and scope. To mitigate…
SPOC: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World
Kiana Ehsani, Tanmay Gupta, Rose Hendrix +11
Reinforcement learning (RL) with dense rewards and imitation learning (IL) with human-generated trajectories are the most widely used approaches for training modern embodied agents…
Ask4Help: Learning to Leverage an Expert for Embodied Tasks
Kunal Pratap Singh, Luca Weihs, Alvaro Herrasti +3
Embodied AI agents continue to become more capable every year with the advent of new models, environments, and benchmarks, but are still far away from being performant and reliable…
ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Matt Deitke, Eli VanderBilt, Alvaro Herrasti +8
Massive datasets and high-capacity models have driven many recent advancements in computer vision and natural language understanding. This work presents a platform to enable simila…
Asymptotic behavior of the free interface for entire vector minimizers in phase transitions
Nicholas D. Alikakos, Zhiyuan Geng, Arghir Zarnescu
We study globally bounded entire minimizers of Allen-Cahn systems for potentials with and $W(u)\sim |u-a…
ManipulaTHOR: A Framework for Visual Object Manipulation
Kiana Ehsani, Winson Han, Alvaro Herrasti +5
The domain of Embodied AI has recently witnessed substantial progress, particularly in navigating agents within their environments. These early successes have laid the building blo…
RoboTHOR: An Open Simulation-to-Real Embodied AI Platform
Matt Deitke, Winson Han, Alvaro Herrasti +10
Visual recognition ecosystems (e.g. ImageNet, Pascal, COCO) have undeniably played a prevailing role in the evolution of modern computer vision. We argue that interactive and embod…
Learning Generalizable Visual Representations via Interactive Gameplay
Luca Weihs, Aniruddha Kembhavi, Kiana Ehsani +7
A growing body of research suggests that embodied gameplay, prevalent not just in human cultures but across a variety of animal species including turtles and ravens, is critical in…
AI2-THOR: An Interactive 3D Environment for Visual AI
Eric Kolve, Roozbeh Mottaghi, Winson Han +10
We introduce The House Of inteRactions (THOR), a framework for visual AI research, available at http://ai2thor.allenai.org. AI2-THOR consists of near photo-realistic 3D indoor scen…