activity
20142023
most citedGrad-CAM: Why did you say that?

329 citations · 474 across the 16 of their papers we have counts for

collaborators

16 papers

cs.RO20232 cited

GOAT: GO to Any Thing

Matthew Chang, Theophile Gervet, Mukul Khanna +10

In deployment scenarios such as homes and warehouses, mobile robots are expected to autonomously navigate for extended periods, seamlessly executing tasks articulated in terms that…

cs.HC202315 cited

Habitat 3.0: A Co-Habitat for Humans, Avatars and Robots

Xavier Puig, Eric Undersander, Andrew Szot +20

We present Habitat 3.0: a simulation platform for studying collaborative human-robot tasks in home environments. Habitat 3.0 offers contributions across three dimensions: (1) Accur…

cs.LG20231 cited

Exploiting Generalization in Offline Reinforcement Learning via Unseen State Augmentations

Nirbhay Modhe, Qiaozi Gao, Ashwin Kalyan +3

Offline reinforcement learning (RL) methods strike a balance between exploration and exploitation by conservative value estimation -- penalizing values of unseen states and actions…

cs.LG20235 cited

Adaptive Coordination in Social Embodied Rearrangement

Andrew Szot, Unnat Jain, Dhruv Batra +3

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 mult…

cs.RO20231 cited

IndoorSim-to-OutdoorReal: Learning to Navigate Outdoors without any Outdoor Experience

Joanne Truong, April Zitkovich, Sonia Chernova +4

We present IndoorSim-to-OutdoorReal (I2O), an end-to-end learned visual navigation approach, trained solely in simulated short-range indoor environments, and demonstrates zero-shot…

cs.CV2023

Navigating to Objects Specified by Images

Jacob Krantz, Theophile Gervet, Karmesh Yadav +7

Images are a convenient way to specify which particular object instance an embodied agent should navigate to. Solving this task requires semantic visual reasoning and exploration o…