most citedMLLM-Search: A Zero-Shot Approach to Finding People using Multimodal Large Language Models

2 citations · 2 across the 1 of their papers we have counts for

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cs.RO2025

X-Nav: Learning End-to-End Cross-Embodiment Navigation for Mobile Robots

Haitong Wang, Aaron Hao Tan, Angus Fung +1

Existing navigation methods are primarily designed for specific robot embodiments, limiting their generalizability across diverse robot platforms. In this paper, we introduce X-Nav…

cs.RO2025

Mobile Robot Navigation Using Hand-Drawn Maps: A Vision Language Model Approach

Aaron Hao Tan, Angus Fung, Haitong Wang +1

Hand-drawn maps can be used to convey navigation instructions between humans and robots in a natural and efficient manner. However, these maps can often contain inaccuracies such a…

cs.RO20242 cited

MLLM-Search: A Zero-Shot Approach to Finding People using Multimodal Large Language Models

Angus Fung, Aaron Hao Tan, Haitong Wang +2

Robotic search of people in human-centered environments, including healthcare settings, is challenging as autonomous robots need to locate people without complete or any prior know…

cs.RO2024

Find Everything: A General Vision Language Model Approach to Multi-Object Search

Daniel Choi, Angus Fung, Haitong Wang +1

The Multi-Object Search (MOS) problem involves navigating to a sequence of locations to maximize the likelihood of finding target objects while minimizing travel costs. In this pap…

cs.RO2024

OLiVia-Nav: An Online Lifelong Vision Language Approach for Mobile Robot Social Navigation

Siddarth Narasimhan, Aaron Hao Tan, Daniel Choi +1

Service robots in human-centered environments such as hospitals, office buildings, and long-term care homes need to navigate while adhering to social norms to ensure the safety and…