81 citations · 102 across the 4 of their papers we have counts for
4 papers
Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning
Dhruv Shah, Michael Equi, Blazej Osinski +3
Navigation in unfamiliar environments presents a major challenge for robots: while mapping and planning techniques can be used to build up a representation of the world, quickly di…
NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration
Ajay Sridhar, Dhruv Shah, Catherine Glossop +1
Robotic learning for navigation in unfamiliar environments needs to provide policies for both task-oriented navigation (i.e., reaching a goal that the robot has located), and task-…
FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing
Kyle Stachowicz, Dhruv Shah, Arjun Bhorkar +2
We present a system that enables an autonomous small-scale RC car to drive aggressively from visual observations using reinforcement learning (RL). Our system, FastRLAP (faster lap…
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action
Dhruv Shah, Blazej Osinski, Brian Ichter +1
Goal-conditioned policies for robotic navigation can be trained on large, unannotated datasets, providing for good generalization to real-world settings. However, particularly in v…