no code implementations • 26 Oct 2023 • Andrew Szot, Max Schwarzer, Harsh Agrawal, Bogdan Mazoure, Walter Talbott, Katherine Metcalf, Natalie Mackraz, Devon Hjelm, Alexander Toshev
We show that large language models (LLMs) can be adapted to be generalizable policies for embodied visual tasks.
3 code implementations • 19 Oct 2023 • Xavier Puig, Eric Undersander, Andrew Szot, Mikael Dallaire Cote, Tsung-Yen Yang, Ruslan Partsey, Ruta Desai, Alexander William Clegg, Michal Hlavac, So Yeon Min, Vladimír Vondruš, Theophile Gervet, Vincent-Pierre Berges, John M. Turner, Oleksandr Maksymets, Zsolt Kira, Mrinal Kalakrishnan, Jitendra Malik, Devendra Singh Chaplot, Unnat Jain, Dhruv Batra, Akshara Rai, Roozbeh Mottaghi
We present Habitat 3. 0: a simulation platform for studying collaborative human-robot tasks in home environments.
no code implementations • ICCV 2023 • Xiaoyu Huang, Dhruv Batra, Akshara Rai, Andrew Szot
We present Skill Transformer, an approach for solving long-horizon robotic tasks by combining conditional sequence modeling and skill modularity.
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.
no code implementations • 31 May 2023 • Andrew Szot, Unnat Jain, Dhruv Batra, Zsolt Kira, Ruta Desai, Akshara Rai
We present the task of "Social Rearrangement", consisting of cooperative everyday tasks like setting up the dinner table, tidying a house or unpacking groceries in a simulated multi-agent environment.
no code implementations • 28 Mar 2023 • Andrew Szot, Amy Zhang, Dhruv Batra, Zsolt Kira, Franziska Meier
How well do reward functions learned with inverse reinforcement learning (IRL) generalize?
no code implementations • 13 Oct 2022 • Matt Deitke, Dhruv Batra, Yonatan Bisk, Tommaso Campari, Angel X. Chang, Devendra Singh Chaplot, Changan Chen, Claudia Pérez D'Arpino, Kiana Ehsani, Ali Farhadi, Li Fei-Fei, Anthony Francis, Chuang Gan, Kristen Grauman, David Hall, Winson Han, Unnat Jain, Aniruddha Kembhavi, Jacob Krantz, Stefan Lee, Chengshu Li, Sagnik Majumder, Oleksandr Maksymets, Roberto Martín-Martín, Roozbeh Mottaghi, Sonia Raychaudhuri, Mike Roberts, Silvio Savarese, Manolis Savva, Mohit Shridhar, Niko Sünderhauf, Andrew Szot, Ben Talbot, Joshua B. Tenenbaum, Jesse Thomason, Alexander Toshev, Joanne Truong, Luca Weihs, Jiajun Wu
We present a retrospective on the state of Embodied AI research.
1 code implementation • 22 May 2022 • Yash Kant, Arun Ramachandran, Sriram Yenamandra, Igor Gilitschenski, Dhruv Batra, Andrew Szot, Harsh Agrawal
Instead, the agent must learn from and is evaluated against human preferences of which objects belong where in a tidy house.
no code implementations • NeurIPS 2021 • Youngwoon Lee, Andrew Szot, Shao-Hua Sun, Joseph J. Lim
Task progress is intuitive and readily available task information that can guide an agent closer to the desired goal.
6 code implementations • NeurIPS 2021 • Andrew Szot, Alex Clegg, Eric Undersander, Erik Wijmans, Yili Zhao, John Turner, Noah Maestre, Mustafa Mukadam, Devendra Chaplot, Oleksandr Maksymets, Aaron Gokaslan, Vladimir Vondrus, Sameer Dharur, Franziska Meier, Wojciech Galuba, Angel Chang, Zsolt Kira, Vladlen Koltun, Jitendra Malik, Manolis Savva, Dhruv Batra
We introduce Habitat 2. 0 (H2. 0), a simulation platform for training virtual robots in interactive 3D environments and complex physics-enabled scenarios.
no code implementations • 1 Jan 2021 • Andrew Szot, Youngwoon Lee, Shao-Hua Sun, Joseph J Lim
Humans can effectively learn to estimate how close they are to completing a desired task simply by watching others fulfill the task.
2 code implementations • ICML 2020 • Ayush Jain, Andrew Szot, Joseph J. Lim
A fundamental trait of intelligence is the ability to achieve goals in the face of novel circumstances, such as making decisions from new action choices.