26 citations · 30 across the 10 of their papers we have counts for
6 papers · 1 filter
ReLIC: A Recipe for 64k Steps of In-Context Reinforcement Learning for Embodied AI
Ahmad Elawady, Gunjan Chhablani, Ram Ramrakhya +4
Intelligent embodied agents need to quickly adapt to new scenarios by integrating long histories of experience into decision-making. For instance, a robot in an unfamiliar house in…
HM3D-OVON: A Dataset and Benchmark for Open-Vocabulary Object Goal Navigation
Naoki Yokoyama, Ram Ramrakhya, Abhishek Das +2
We present the Habitat-Matterport 3D Open Vocabulary Object Goal Navigation dataset (HM3D-OVON), a large-scale benchmark that broadens the scope and semantic range of prior Object…
Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge
Sriram Yenamandra, Arun Ramachandran, Mukul Khanna +42
In order to develop robots that can effectively serve as versatile and capable home assistants, it is crucial for them to reliably perceive and interact with a wide variety of obje…
Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control
Gunshi Gupta, Karmesh Yadav, Yarin Gal +4
Embodied AI agents require a fine-grained understanding of the physical world mediated through visual and language inputs. Such capabilities are difficult to learn solely from task…
GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
Mukul Khanna, Ram Ramrakhya, Gunjan Chhablani +7
The Embodied AI community has made significant strides in visual navigation tasks, exploring targets from 3D coordinates, objects, language descriptions, and images. However, these…
Seeing the Unseen: Visual Common Sense for Semantic Placement
Ram Ramrakhya, Aniruddha Kembhavi, Dhruv Batra +3
Computer vision tasks typically involve describing what is present in an image (e.g. classification, detection, segmentation, and captioning). We study a visual common sense task t…