2 citations · 3 across the 6 of their papers we have counts for
6 papers
AsyncVLA: An Asynchronous VLA for Fast and Robust Navigation on the Edge
Noriaki Hirose, Catherine Glossop, Dhruv Shah +1
Robotic foundation models achieve strong generalization by leveraging internet-scale vision-language representations, but their massive computational cost creates a fundamental bot…
OmniVLA: An Omni-Modal Vision-Language-Action Model for Robot Navigation
Noriaki Hirose, Catherine Glossop, Dhruv Shah +1
Humans can flexibly interpret and compose different goal specifications, such as language instructions, spatial coordinates, or visual references, when navigating to a destination.…
Towards Data-Driven Metrics for Social Robot Navigation Benchmarking
Pilar Bachiller-Burgos, Ulysses Bernardet, Luis V. Calderita +8
This paper presents a joint effort towards the development of a data-driven Social Robot Navigation metric to facilitate benchmarking and policy optimization for ground robots. We…
Learning to Drive Anywhere with Model-Based Reannotation
Noriaki Hirose, Lydia Ignatova, Kyle Stachowicz +3
Developing broadly generalizable visual navigation policies for robots is a significant challenge, primarily constrained by the availability of large-scale, diverse training data.…
LeLaN: Learning A Language-Conditioned Navigation Policy from In-the-Wild Videos
Noriaki Hirose, Catherine Glossop, Ajay Sridhar +3
The world is filled with a wide variety of objects. For robots to be useful, they need the ability to find arbitrary objects described by people. In this paper, we present LeLaN(Le…
SELFI: Autonomous Self-Improvement with Reinforcement Learning for Social Navigation
Noriaki Hirose, Dhruv Shah, Kyle Stachowicz +2
Autonomous self-improving robots that interact and improve with experience are key to the real-world deployment of robotic systems. In this paper, we propose an online learning met…