1 citations · 1 across the 3 of their papers we have counts for
5 papers
Meanings and Measurements: Multi-Agent Probabilistic Grounding for Vision-Language Navigation
Swagat Padhan, Lakshya Jain, Bhavya Minesh Shah +3
Robots collaborating with humans must convert natural language goals into actionable, physically grounded decisions. For example, executing a command such as "go two meters to the…
Language-Conditioned Observation Models for Visual Object Search
Thao Nguyen, Vladislav Hrosinkov, Eric Rosen +1
Object search is a challenging task because when given complex language descriptions (e.g., "find the white cup on the table"), the robot must move its camera through the environme…
Robot Object Retrieval with Contextual Natural Language Queries
Thao Nguyen, Nakul Gopalan, Roma Patel +3
Natural language object retrieval is a highly useful yet challenging task for robots in human-centric environments. Previous work has primarily focused on commands specifying the d…
Planning with State Abstractions for Non-Markovian Task Specifications
Yoonseon Oh, Roma Patel, Thao Nguyen +3
Often times, we specify tasks for a robot using temporal language that can also span different levels of abstraction. The example command ``go to the kitchen before going to the se…
Grounding Language Attributes to Objects using Bayesian Eigenobjects
Vanya Cohen, Benjamin Burchfiel, Thao Nguyen +3
We develop a system to disambiguate object instances within the same class based on simple physical descriptions. The system takes as input a natural language phrase and a depth im…