activity
20172021
most citedCLIPort: What and Where Pathways for Robotic Manipulation

100 citations · 132 across the 3 of their papers we have counts for

collaborators

6 papers

cs.RO2021100 cited

CLIPort: What and Where Pathways for Robotic Manipulation

Mohit Shridhar, Lucas Manuelli, Dieter Fox

How can we imbue robots with the ability to manipulate objects precisely but also to reason about them in terms of abstract concepts? Recent works in manipulation have shown that e…

cs.CL202117 cited

Language Grounding with 3D Objects

Jesse Thomason, Mohit Shridhar, Yonatan Bisk +2

Seemingly simple natural language requests to a robot are generally underspecified, for example "Can you bring me the wireless mouse?" Flat images of candidate mice may not provide…

cs.CL2020

ALFWorld: Aligning Text and Embodied Environments for Interactive Learning

Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté +3

Given a simple request like Put a washed apple in the kitchen fridge, humans can reason in purely abstract terms by imagining action sequences and scoring their likelihood of succe…

cs.CV2019

ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

Mohit Shridhar, Jesse Thomason, Daniel Gordon +5

We present ALFRED (Action Learning From Realistic Environments and Directives), a benchmark for learning a mapping from natural language instructions and egocentric vision to seque…

cs.RO2018

Interactive Visual Grounding of Referring Expressions for Human-Robot Interaction

Mohit Shridhar, David Hsu

This paper presents INGRESS, a robot system that follows human natural language instructions to pick and place everyday objects. The core issue here is the grounding of referring e…

cs.RO201715 cited

Grounding Spatio-Semantic Referring Expressions for Human-Robot Interaction

Mohit Shridhar, David Hsu

The human language is one of the most natural interfaces for humans to interact with robots. This paper presents a robot system that retrieves everyday objects with unconstrained n…