2 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…
Robots Autonomously Detecting People: A Multimodal Deep Contrastive Learning Method Robust to Intraclass Variations
Angus Fung, Beno Benhabib, Goldie Nejat
Robotic detection of people in crowded and/or cluttered human-centered environments including hospitals, long-term care, stores and airports is challenging as people can become occ…