38 citations
- University of TorontoCA12 papers
- University Health NetworkCA7 papers
- University of California, San FranciscoUS2 papers
- Alberta Bone and Joint Health InstituteCA1 paper
- American University of the Middle EastKW1 paper
- Arizona State UniversityUS1 paper
- Athinoula A. Martinos Center for Biomedical ImagingUS1 paper
- Baycrest Academy for Research and EducationCA1 paper
- Baycrest HospitalCA1 paper
- Bloomberg (United States)US1 paper
- Brampton Civic HospitalCA1 paper
- Erasmus University RotterdamNL1 paper
7 papers · 1 filter
OpenNav: Open-World Navigation with Multimodal Large Language Models
Mingfeng Yuan, Letian Wang, Steven L. Waslander
Pre-trained large language models (LLMs) have demonstrated strong common-sense reasoning abilities, making them promising for robotic navigation and planning tasks. However, despit…
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…
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…
A Photorealistic Dataset and Vision-Based Algorithm for Anomaly Detection During Proximity Operations in Lunar Orbit
Selina Leveugle, Chang Won Lee, Svetlana Stolpner +4
NASA's forthcoming Lunar Gateway space station, which will be uncrewed most of the time, will need to operate with an unprecedented level of autonomy. One key challenge is enabling…
GNSS/Multi-Sensor Fusion Using Continuous-Time Factor Graph Optimization for Robust Localization
Haoming Zhang, Chih-Chun Chen, Heike Vallery +1
Accurate and robust vehicle localization in highly urbanized areas is challenging. Sensors are often corrupted in those complicated and large-scale environments. This paper introdu…
Towards Open World NeRF-Based SLAM
Daniil Lisus, Connor Holmes, Steven Waslander
Neural Radiance Fields (NeRFs) offer versatility and robustness in map representations for Simultaneous Localization and Mapping (SLAM) tasks. This paper extends NICE-SLAM, a recen…