15 citations · 17 across the 4 of their papers we have counts for
4 papers
Embodied AI with Foundation Models for Mobile Service Robots: A Systematic Review
Matthew Lisondra, Beno Benhabib, Goldie Nejat
Rapid advancements in foundation models, including Large Language Models, Vision-Language Models, Multimodal Large Language Models, and Vision-Language-Action Models, have opened n…
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…
LDTrack: Dynamic People Tracking by Service Robots using Diffusion Models
Angus Fung, Beno Benhabib, Goldie Nejat
Tracking of dynamic people in cluttered and crowded human-centered environments is a challenging robotics problem due to the presence of intraclass variations including occlusions,…
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…