107 citations · 390 across the 26 of their papers we have counts for
6 papers · 1 filter
Learning Articulated Motion Models from Visual and Lingual Signals
Zhengyang Wu, Mohit Bansal, Matthew R. Walter
In order for robots to operate effectively in homes and workplaces, they must be able to manipulate the articulated objects common within environments built for and by humans. Prev…
Accurate Vision-based Vehicle Localization using Satellite Imagery
Hang Chu, Hongyuan Mei, Mohit Bansal +1
We propose a method for accurately localizing ground vehicles with the aid of satellite imagery. Our approach takes a ground image as input, and outputs the location from which it…
What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment
Hongyuan Mei, Mohit Bansal, Matthew R. Walter
We propose an end-to-end, domain-independent neural encoder-aligner-decoder model for selective generation, i.e., the joint task of content selection and surface realization. Our m…
Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences
Hongyuan Mei, Mohit Bansal, Matthew R. Walter
We propose a neural sequence-to-sequence model for direction following, a task that is essential to realizing effective autonomous agents. Our alignment-based encoder-decoder model…
Learning Models for Following Natural Language Directions in Unknown Environments
Sachithra Hemachandra, Felix Duvallet, Thomas M. Howard +3
Natural language offers an intuitive and flexible means for humans to communicate with the robots that we will increasingly work alongside in our homes and workplaces. Recent advan…
Learning Articulated Motions From Visual Demonstration
Sudeep Pillai, Matthew R. Walter, Seth Teller
Many functional elements of human homes and workplaces consist of rigid components which are connected through one or more sliding or rotating linkages. Examples include doors and…