2 citations · 2 across the 2 of their papers we have counts for
5 papers
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 Understanding Contextual Information in Human-Centered Environments using Weakly Supervised Mask Data Distillation
Daniel Dworakowski, Goldie Nejat
Contextual information in human environments, such as signs, symbols, and objects provide important information for robots to use for exploration and navigation. To identify and se…