activity
20182020
most citedLearning to Map Natural Language Instructions to Physical Quadcopter Control using Simulated Flight

26 citations · 32 across the 2 of their papers we have counts for

collaborators

5 papers

cs.RO20206 cited

Few-shot Object Grounding and Mapping for Natural Language Robot Instruction Following

Valts Blukis, Ross A. Knepper, Yoav Artzi

We study the problem of learning a robot policy to follow natural language instructions that can be easily extended to reason about new objects. We introduce a few-shot language-co…

cs.RO201926 cited

Learning to Map Natural Language Instructions to Physical Quadcopter Control using Simulated Flight

Valts Blukis, Yannick Terme, Eyvind Niklasson +2

We propose a joint simulation and real-world learning framework for mapping navigation instructions and raw first-person observations to continuous control. Our model estimates the…

cs.RO2018

Mapping Navigation Instructions to Continuous Control Actions with Position-Visitation Prediction

Valts Blukis, Dipendra Misra, Ross A. Knepper +1

We propose an approach for mapping natural language instructions and raw observations to continuous control of a quadcopter drone. Our model predicts interpretable position-visitat…

cs.CL2018

Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction

Dipendra Misra, Andrew Bennett, Valts Blukis +3

We propose to decompose instruction execution to goal prediction and action generation. We design a model that maps raw visual observations to goals using LINGUNET, a language-cond…

cs.AI2018

Following High-level Navigation Instructions on a Simulated Quadcopter with Imitation Learning

Valts Blukis, Nataly Brukhim, Andrew Bennett +2

We introduce a method for following high-level navigation instructions by mapping directly from images, instructions and pose estimates to continuous low-level velocity commands fo…