Search Results for author: Eric Undersander

Found 9 papers, 4 papers with code

Habitat Synthetic Scenes Dataset (HSSD-200): An Analysis of 3D Scene Scale and Realism Tradeoffs for ObjectGoal Navigation

no code implementations CVPR 2024 Mukul Khanna, Yongsen Mao, Hanxiao Jiang, Sanjay Haresh, Brennan Shacklett, Dhruv Batra, Alexander Clegg, Eric Undersander, Angel X. Chang, Manolis Savva

Surprisingly, we observe that agents trained on just 122 scenes from our dataset outperform agents trained on 10, 000 scenes from the ProcTHOR-10K dataset in terms of zero-shot generalization in real-world scanned environments.

Navigate ObjectGoal Navigation +1

Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement at 100k Steps-Per-Second

1 code implementation CVPR 2023 Vincent-Pierre Berges, Andrew Szot, Devendra Singh Chaplot, Aaron Gokaslan, Roozbeh Mottaghi, Dhruv Batra, Eric Undersander

Specifically, a Fetch robot (equipped with a mobile base, 7DoF arm, RGBD camera, egomotion, and onboard sensing) is spawned in a home environment and asked to rearrange objects - by navigating to an object, picking it up, navigating to a target location, and then placing the object at the target location.

Reinforcement Learning (RL)

Transformers are Adaptable Task Planners

no code implementations6 Jul 2022 Vidhi Jain, Yixin Lin, Eric Undersander, Yonatan Bisk, Akshara Rai

Every home is different, and every person likes things done in their particular way.

Attribute

Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale

no code implementations CVPR 2022 Ram Ramrakhya, Eric Undersander, Dhruv Batra, Abhishek Das

We present a large-scale study of imitating human demonstrations on tasks that require a virtual robot to search for objects in new environments -- (1) ObjectGoal Navigation (e. g. 'find & go to a chair') and (2) Pick&Place (e. g. 'find mug, pick mug, find counter, place mug on counter').

Imitation Learning ObjectGoal Navigation +1

Efficient and Interpretable Robot Manipulation with Graph Neural Networks

no code implementations25 Feb 2021 Yixin Lin, Austin S. Wang, Eric Undersander, Akshara Rai

Manipulation tasks, like loading a dishwasher, can be seen as a sequence of spatial constraints and relationships between different objects.

Graph Neural Network Imitation Learning +1

Block-Sparse Recurrent Neural Networks

no code implementations ICLR 2018 Sharan Narang, Eric Undersander, Gregory Diamos

Even though sparse operations need less compute and memory relative to their dense counterparts, the speed-up observed by using sparse operations is less than expected on different hardware platforms.

Language Modelling Machine Translation +3

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