37 citations · 115 across the 19 of their papers we have counts for
19 papers
PARAssist: A Framework for Personalized and Adaptive Robotic Assistance from Ambiguous User Requests
Pourya Aliasghari, Goldie Nejat
Service robots may encounter ambiguous user requests that require context-aware inference. Users may also have unique preferences with certain tasks when requesting robotic assista…
ExpressMM: Expressive Mobile Manipulation Behaviors in Human-Robot Interactions
Souren Pashangpour, Haitong Wang, Matthew Lisondra +1
Mobile manipulators are increasingly deployed in human-centered environments to perform tasks. While completing such tasks, they should also be able to communicate their intent to…
PovNet+: A Deep Learning Architecture for Socially Assistive Robots to Learn and Assist with Multiple Activities of Daily Living
Fraser Robinson, Souren Pashangpour, Matthew Lisondra +1
A significant barrier to the long-term deployment of autonomous socially assistive robots is their inability to both perceive and assist with multiple activities of daily living (A…
SplatSearch: Instance Image Goal Navigation for Mobile Robots using 3D Gaussian Splatting and Diffusion Models
Siddarth Narasimhan, Matthew Lisondra, Haitong Wang +1
The Instance Image Goal Navigation (IIN) problem requires mobile robots deployed in unknown environments to search for specific objects or people of interest using only a single re…
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…
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…
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…
The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcare
Souren Pashangpour, Goldie Nejat
The potential use of large language models (LLMs) in healthcare robotics can help address the significant demand put on healthcare systems around the world with respect to an aging…
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…
Investigating Persuasive Socially Assistive Robot Behavior Strategies for Sustained Engagement in Long-Term Care
Cristina Getson, Goldie Nejat
Socially assistive robots are increasingly being used to support the social, cognitive, and physical well-being of those who provide care (healthcare professionals) and those in ne…
4CNet: A Diffusion Approach to Map Prediction for Decentralized Multi-Robot Exploration
Aaron Hao Tan, Siddarth Narasimhan, Goldie Nejat
Mobile robots in unknown cluttered environments with irregularly shaped obstacles often face energy and communication challenges which directly affect their ability to explore thes…
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,…
NavFormer: A Transformer Architecture for Robot Target-Driven Navigation in Unknown and Dynamic Environments
Haitong Wang, Aaron Hao Tan, Goldie Nejat
In unknown cluttered and dynamic environments such as disaster scenes, mobile robots need to perform target-driven navigation in order to find people or objects of interest, while…
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…
Deep Reinforcement Learning for Decentralized Multi-Robot Exploration With Macro Actions
Aaron Hao Tan, Federico Pizarro Bejarano, Yuhan Zhu +2
Cooperative multi-robot teams need to be able to explore cluttered and unstructured environments while dealing with communication dropouts that prevent them from exchanging local i…
Multimodal Detection of COVID-19 Symptoms using Deep Learning & Probability-based Weighting of Modes
Meysam Effati, Yu-Chen Sun, Hani E. Naguib +1
The COVID-19 pandemic is one of the most challenging healthcare crises during the 21st century. As the virus continues to spread on a global scale, the majority of efforts have bee…
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…
Making Sense of the Robotized Pandemic Response: A Comparison of Global and Canadian Robot Deployments and Success Factors
T. Barfoot, J. Burgner-Kahrs, E. Diller +12
From disinfection and remote triage, to logistics and delivery, countries around the world are making use of robots to address the unique challenges presented by the COVID-19 pande…